How Do I Link My OpenBB Bot Account?
+
+
-How Do I Link My OpenBB Bot Account?
After you signup for an OpenBB Bot plan you can link your accounts from hereCan I try an OpenBB Bot plan?
+
+
-
-Can I try an OpenBB Bot plan?
You can try a preview of any plan by just running commands on a server that has OpenBB Bot, like OpenBB Discord. We offer a limited amount of daily commands.Will my OpenBB Bot plan renew at the end of the billing cycle?
+
+
-
-Will my OpenBB Bot plan renew at the end of the billing cycle?
Yes, plans renew automatically at the end of the monthly and yearly billing cycles. You can cancel your plan at any time, before the end of the billing cycle, and it will not auto-renew anymore.Can I get a refund on my OpenBB Bot?
+
+
-
-Can I get a refund on my OpenBB Bot?
Since we offer a free command tier to try commands we don't offer refunds as you have had ample time to try the service and make a decision.If I sign up for OpenBB Bot do I get access on all platforms?
+
+
-If I sign up for OpenBB Bot do I get access on all platforms?
Yes! You will have access on Discord, and other platforms as we add support.If I cancel OpenBB Bot subscription do I still have access?
+
+
-
-If I cancel OpenBB Bot subscription do I still have access?
No, you will lose your access but you get a credit on your account of the prorated amount until the end of your current billing cycle.What's the difference between an individual plan and server plan on OpenBB Bot?
+
+
+What's the difference between an individual plan and server plan on OpenBB Bot?
An individual plan gives your account access to OpenBB Bot while a server plan gives the whole server access. An individual plan carries more perks with it than a server plan, which you can find by clicking on the plan.
+
+
Just head to Server Settings → Integrations and then click ‘Manage’ next to an app, where you will behold a new, shiny, and dare we say dazzling, new surface.
@@ -83,8 +90,11 @@ Just head to Server Settings → Integrations and then click ‘Manage
There’s also a command-specific list, where you can make customized permissions for each command.
+
![]()
-
-To see all the available commands, you can type ```/help``` in the chat. This will show you a list of commands and their descriptions. You can also tap on any command to use it directly. Some of the most popular commands are:
+To see all the available commands, you can type `/help` in the chat. This will show you a list of commands and their descriptions. You can also tap on any command to use it directly. Some of the most popular commands are:
-- ```/cd AMD``` Shows the daily chart for a given stock ticker.
-- ```/c3m AMD``` Shows the 3-month chart for a given stock ticker.
-- ```/flow AMD``` Shows the recent options flow for the given stock ticker.
-- ```/c DOGE``` Shows a chart for the crypto symbol provided.
+- `/cd AMD` Shows the daily chart for a given stock ticker.
+- `/c3m AMD` Shows the 3-month chart for a given stock ticker.
+- `/flow AMD` Shows the recent options flow for the given stock ticker.
+- `/c DOGE` Shows a chart for the crypto symbol provided.
That's it! You're ready to use OpenBB Telegram Bot and explore the markets. Have fun!
-Check out the Reference section for more commands or type ```/help``` in your chat to see what else we can do!
+Check out the Reference section for more commands or type `/help` in your chat to see what else we can do!
diff --git a/website/content/excel/data-connectors.md b/website/content/excel/data-connectors.md
index 0ddb5197bfab..376c8aa47b0f 100644
--- a/website/content/excel/data-connectors.md
+++ b/website/content/excel/data-connectors.md
@@ -3,15 +3,16 @@ title: Data connectors
sidebar_position: 3
description: Access your data connectors from OpenBB Terminal Pro inside OpenBB Add-in for Excel.
keywords:
-- Microsoft Excel
-- Add-in
-- Advanced
-- Data connectors
-- BYOD
-- Bring your own data
+ - Microsoft Excel
+ - Add-in
+ - Advanced
+ - Data connectors
+ - BYOD
+ - Bring your own data
---
+
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
.
+- Make sure your backend's CORS settings allow requests coming from [https://excel.openbb.co](https://excel.openbb.co).
- Requests via HTTP will be blocked by Excel. So if you are using the Add-in for Excel on Mac or Office on the web with Safari browser you need to run your backend via HTTPS.
:::
diff --git a/website/content/excel/getting-started/basics.md b/website/content/excel/getting-started/basics.md
index 64f8da4dc3f5..2a8a559f9a66 100644
--- a/website/content/excel/getting-started/basics.md
+++ b/website/content/excel/getting-started/basics.md
@@ -3,11 +3,11 @@ title: Basics
sidebar_position: 2
description: This page provides an overview of the basics of the OpenBB add-in for Microsoft Excel. It covers the basic usage of the add-in and the available functions.
keywords:
-- Microsoft Excel
-- Add-in
-- Basics
-- Examples
-- Functions
+ - Microsoft Excel
+ - Add-in
+ - Basics
+ - Examples
+ - Functions
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -19,28 +19,28 @@ The OpenBB Add-in for Excel provides direct access to the OpenBB platform, where
- `OBB.[MENU].[SUB_MENU].[COMMAND]`
:::tip
-Use the key to autocomplete the function name after typing `=OBB.`
+Use the <TAB> key to autocomplete the function name after typing `=OBB.`
:::
Examples:
1. Getting balance sheet data for a stock:
- ```excel
- =OBB.EQUITY.FUNDAMENTAL.BALANCE("AAPL")
- ```
+ ```excel
+ =OBB.EQUITY.FUNDAMENTAL.BALANCE("AAPL")
+ ```
2. Getting the latest news for a stock:
- ```excel
- =OBB.NEWS.COMPANY("AAPL")
- ```
+ ```excel
+ =OBB.NEWS.COMPANY("AAPL")
+ ```
3. Getting the earnings calendar:
- ```excel
- =OBB.EQUITY.CALENDAR.IPO(,"2023-11-20")
- ```
+ ```excel
+ =OBB.EQUITY.CALENDAR.IPO(,"2023-11-20")
+ ```
:::tip
If you want to skip a parameter use comma (or semi-colon depending on your number separator) without any value. In example iii. we are skipping the first parameter (symbol).
diff --git a/website/content/excel/help.md b/website/content/excel/help.md
index 46171a7f168b..3d65bceefe5f 100644
--- a/website/content/excel/help.md
+++ b/website/content/excel/help.md
@@ -3,57 +3,56 @@ title: Help
sidebar_position: 5
description: Help for OpenBB Add-in for Excel.
keywords:
-- Microsoft Excel
-- Add-in
-- Help
+ - Microsoft Excel
+ - Add-in
+ - Help
---
-
-import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
+import HeadTitle from "@site/src/components/General/HeadTitle.tsx";
.
+If you face specific issues while using the add-in and the solutions provided here don't resolve them, don't hesitate to reach out to us for further assistance. You can contact us through [support@openbb.finance](mailto:support@openbb.finance).
--record=all
Sometimes manual intervention is needed. For example, adjusting out-of-top level imports or adding specific arguments for a given fetcher.
:::
-
## Integration tests
The integration tests are a bit more complex than the unit tests, as we want to test both the Python interface and the API interface. For this, we have two scripts that will help you generate the integration tests.
@@ -93,7 +92,7 @@ pytest openbb_platform
We aim to have a short import time for the package. To measure that we use `tuna`.
--
I added the bot but still don't see slash commands, what do I do?
-I added the bot but still don't see slash commands, what do I do?
- -
+
Just head to Server Settings → Integrations and then click ‘Manage’ next to an app, where you will behold a new, shiny, and dare we say dazzling, new surface.
@@ -83,8 +90,11 @@ Just head to Server Settings → Integrations and then click ‘Manage
There’s also a command-specific list, where you can make customized permissions for each command.
+
-
-
- By default, these are all synced to the command permission at the top. +
- + By default, these are all synced to the command permission at the top. +
- You can unsync an individual command to make further customizations.
How do I select commands instead of typing?
+
+
+On desktop press `tab` to select the command.
+How do I select commands instead of typing?
+ If you are On mobile press and hold to select the command. -On desktop press ```tab``` to select the command. -
-
Running an OBB. function returns '#VALUE!'
+Running an OBB. function returns '#VALUE!'
-* Make sure you are using the correct syntax for the function. You can find the correct syntax for each function [here](https://docs.openbb.co/excel/reference) -* If you have just opened your workbook and the OBB. function returns '#VALUE!', try recalculating the cell again - this is an ongoing issue with Excel add-ins +- Make sure you are using the correct syntax for the function. You can find the correct syntax for each function [here](https://docs.openbb.co/excel/reference) +- If you have just opened your workbook and the OBB. function returns '#VALUE!', try recalculating the cell again - this is an ongoing issue with Excel add-ins
-
OBB. functions are not available after installing the add-in
+OBB. functions are not available after installing the add-in
-* Make sure OpenBB Add-in for Excel shows in the ribbon -* Go to **Insert** > **Get Add-ins** > **My Add-ins** > Click '...' when hovering OpenBB add-in > remove the add-in and install it again -* Restart your computer or manually [clear the Office cache](https://learn.microsoft.com/en-us/office/dev/add-ins/testing/clear-cache) +- Make sure OpenBB Add-in for Excel shows in the ribbon +- Go to **Insert** > **Get Add-ins** > **My Add-ins** > Click '...' when hovering OpenBB add-in > remove the add-in and install it again +- Restart your computer or manually [clear the Office cache](https://learn.microsoft.com/en-us/office/dev/add-ins/testing/clear-cache)
-
Task pane displays "You don’t have permission to use this add-in. Contact your system administrator to request access."
+Task pane displays "You don’t have permission to use this add-in. Contact your system administrator to request access."
-* Make sure your account has the necessary permissions to use add-in -* Restart your computer or manually [clear the Office cache](https://learn.microsoft.com/en-us/office/dev/add-ins/testing/clear-cache) +- Make sure your account has the necessary permissions to use add-in +- Restart your computer or manually [clear the Office cache](https://learn.microsoft.com/en-us/office/dev/add-ins/testing/clear-cache)
-
Editing a workbook in the browser and then on desktop app duplicates the 'OpenBB' tab in the ribbon
+Editing a workbook in the browser and then on desktop app duplicates the 'OpenBB' tab in the ribbon
This is a known Excel issue. Currently, there is no definitive fix for the problem, but there are workarounds you can apply to fix the file depending on your operating system: -* **Windows**: File > Info > Inspect Workbook > Check ‘Task Pane Add-ins’ > Click ‘OK’. This will scan your workbook and remove the stale add-in reference created by Excel in the browser -* **Mac**: rename your file from .xlsx to .zip > unzip it using WinZip for Mac (don’t use the default unzip tool, otherwise it won’t work) > look for webextensions folder and delete webextension1.xml > rename the file back to .xlsx +- **Windows**: File > Info > Inspect Workbook > Check ‘Task Pane Add-ins’ > Click ‘OK’. This will scan your workbook and remove the stale add-in reference created by Excel in the browser +- **Mac**: rename your file from .xlsx to .zip > unzip it using WinZip for Mac (don’t use the default unzip tool, otherwise it won’t work) > look for webextensions folder and delete webextension1.xml > rename the file back to .xlsx
-
diff --git a/website/content/platform/development/how-to/add_data_provider_extension.md b/website/content/platform/development/how-to/add_data_provider_extension.md
index f8d99af03322..a9ae9233ad07 100644
--- a/website/content/platform/development/how-to/add_data_provider_extension.md
+++ b/website/content/platform/development/how-to/add_data_provider_extension.md
@@ -3,25 +3,25 @@ title: How To Add Data Provider Extensions
sidebar_position: 3
description: This guide outlines the process for adding a new data provider extension to the OpenBB Platform.
keywords:
-- OpenBB Platform
-- Open source
-- Python interface
-- REST API
-- contribution
-- contributing
-- documentation
-- code
-- provider
-- data
-- endpoint
-- existing
-- OpenBB extensions
-- OpenBB provider
-- standard model
-- provider model
-- how to
-- new
-- template
+ - OpenBB Platform
+ - Open source
+ - Python interface
+ - REST API
+ - contribution
+ - contributing
+ - documentation
+ - code
+ - provider
+ - data
+ - endpoint
+ - existing
+ - OpenBB extensions
+ - OpenBB provider
+ - standard model
+ - provider model
+ - how to
+ - new
+ - template
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -46,18 +46,18 @@ The structure of the folder will look something like this:
```md
template/
├── openbb_template/
-│ ├── models/
-│ │ ├── __init__.py
-│ │ └── some_model.py
-│ ├── utils/
-│ │ ├── __init__.py
-│ │ └── helpers.py
-│ ├── tests/
-│ │ ├── record/
-│ │ ├── __init__.py
-│ │ └── test_template_fetchers.py
-│ ├── __init__.py
-├── __init__.py
+│ ├── models/
+│ │ ├── **init**.py
+│ │ └── some_model.py
+│ ├── utils/
+│ │ ├── **init**.py
+│ │ └── helpers.py
+│ ├── tests/
+│ │ ├── record/
+│ │ ├── **init**.py
+│ │ └── test_template_fetchers.py
+│ ├── **init**.py
+├── **init**.py
├── pyproject.toml
└── README.md
```
@@ -99,9 +99,10 @@ The cookiecutter tool will get you most of the way there, but it still requires
The `pyproject.toml` file defines the package itself.
:::tip
+
- Before adding any dependency, ensure it aligns with the Platform's existing dependencies.
- If possible, use loose versioning.
-:::
+ :::
```
[tool.poetry]
@@ -124,7 +125,7 @@ build-backend = "poetry.core.masonry.api"
template = "openbb_template:template_provider"
```
-The last line (poetry.plugins) maps to the provider defined in the __init__.py file.
+The last line (poetry.plugins) maps to the provider defined in the **init**.py file.
Additionally, for local extensions, you can add this line in the `LOCAL_DEPS` variable in the `dev_install.py` file, located in `~/OpenBBTerminal/openbb_platform/`:
@@ -226,14 +227,13 @@ The new extension can be self-published on PyPI and hosted in an independent Git
If not contributing directly to the OpenBB GitHub, we still want to know about your creation. Share it with us on social media, and add `openbb` as a topic tag in your GitHub repo.
-
## Publish Extension To PyPI
To publish your extension to PyPI, you'll need to have a PyPI account and a PyPI API token.
### Setup
-Create an account and get an API token from Cannot retrieve the data added to Terminal Pro through custom backend using OBB.BYOD
+Cannot retrieve the data added to Terminal Pro through custom backend using OBB.BYOD
-* Make sure your backend is running and accessible -* If you are using Mac or Safari make sure your backend is using HTTPS and has a valid SSL certificate +- Make sure your backend is running and accessible +- If you are using Mac or Safari make sure your backend is using HTTPS and has a valid SSL certificateDoes OpenBB have coverage for [insert type of data]?
+
+
-Does OpenBB have coverage for [insert type of data]?
Equity market coverage will vary by provider and subscription status with them. It is common for free tiers to be US-listings only. @@ -25,7 +26,8 @@ You can find all data models [here](/platform/data_models), or the [Reference](/The router appears to be missing functions.
+
+
-The router appears to be missing functions.
The router populates itself from the installed extensions. For example, if the Technical Analysis extension is not installed, the `obb.technical` router path will not be present. @@ -62,7 +64,8 @@ pip install openbb-nightlyWhy is the returned data not matching the start/end date I requested?
+
+
-Why is the returned data not matching the start/end date I requested?
The provider may not have data from the requested period, in which case the data will be what they return. For example, `provider='yfinance'` at one-minute intervals will not return beyond one week ago. @@ -70,7 +73,8 @@ Another reason could be the data entitlements of your API key. Check the provideHow do I load a ticker symbol from India?
+
+
-How do I load a ticker symbol from India?
Ticker symbols listed on exchanges outside of the US will have a suffix attached, for example, Rico Auto Industries Limited: @@ -83,19 +87,22 @@ The precise naming convention will differ by source, it's best to reference eachHow can I request a data provider or function?
+
+
-How can I request a data provider or function?
-Please [request a feature](https://openbb.co/request-a-feature), tell us about your use case. +Please [request a feature](https://openbb.co/request-a-feature), tell us about your use case.Can I contribute my own data provider extension?
+
+
-Can I contribute my own data provider extension?
Yes! Please take a look at our [Development](/platform/development) pages for more information.Can my company become a data partner?
+
+
Can my company become a data partner?
Yes! Please visit our website [here](https://openbb.co/use-cases/data-vendors) and fill out the form. diff --git a/website/content/sdk/data-available/crypto/discovery.md b/website/content/sdk/data-available/crypto/discovery.md index ffad6ef7d437..c77b5951b019 100644 --- a/website/content/sdk/data-available/crypto/discovery.md +++ b/website/content/sdk/data-available/crypto/discovery.md @@ -1,27 +1,28 @@ --- title: Discovery sidebar_position: 2 -description: This page provides detailed instructions on how to use the Discovery +description: + This page provides detailed instructions on how to use the Discovery sub-module within the ''openbb.crypto.disc'' to find new trends in Crypto markets. The module enables users to search coins on CoinGecko by category, access a list of coins available on CoinGecko, search CoinPaprika, view top coins, DeFi applications, NFTs, and games by daily volume and users, and more. It also provides examples in Python for better understanding. keywords: -- openbb.crypto.disc -- Crypto markets -- CoinGecko -- Coins search -- DeFi applications -- Python Examples -- NFTs -- Crypto trends -- Market insights -- Crypto trading pairs -- market_cap -- trending coins -- Top DeFi games -- CoinPaprika search + - openbb.crypto.disc + - Crypto markets + - CoinGecko + - Coins search + - DeFi applications + - Python Examples + - NFTs + - Crypto trends + - Market insights + - Crypto trading pairs + - market_cap + - trending coins + - Top DeFi games + - CoinPaprika search --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -32,21 +33,21 @@ The Discovery sub-module contains the tools for finding new trends in Crpyto mar ## How to Use -|Path |Description | -|:----|-----------:| -|openbb.crypto.disc.categories_keys |A List of Categories for Searching Coins | -|openbb.crypto.disc.coin_list |A List of Coins Available on CoinGecko | -|openbb.crypto.disc.coins |Search Coins on CoinGecko by Category | -|openbb.crypto.disc.coins_for_given_exchange |A Dictionary of all Trading Pairs on Binance | -|openbb.crypto.disc.cpsearch |Search CoinPaprika | -|openbb.crypto.disc.gainers |Top Gainers Over Different Periods | -|openbb.crypto.disc.losers |Top Losers Over Different Periods | -|openbb.crypto.disc.top_coins |The Top Movers | -|openbb.crypto.disc.top_dapps |The Top DeFi Applications by Daily Volume and Users | -|openbb.crypto.disc.top_dexes |The Top DeFi Exchanges | -|openbb.crypto.disc.top_games |The Top DeFi Games | -|openbb.crypto.disc.top_nfts |The Top NFTs | -|openbb.crypto.disc.trending |Trending Coins on CoinGecko | +| Path | Description | +| :------------------------------------------ | --------------------------------------------------: | +| openbb.crypto.disc.categories_keys | A List of Categories for Searching Coins | +| openbb.crypto.disc.coin_list | A List of Coins Available on CoinGecko | +| openbb.crypto.disc.coins | Search Coins on CoinGecko by Category | +| openbb.crypto.disc.coins_for_given_exchange | A Dictionary of all Trading Pairs on Binance | +| openbb.crypto.disc.cpsearch | Search CoinPaprika | +| openbb.crypto.disc.gainers | Top Gainers Over Different Periods | +| openbb.crypto.disc.losers | Top Losers Over Different Periods | +| openbb.crypto.disc.top_coins | The Top Movers | +| openbb.crypto.disc.top_dapps | The Top DeFi Applications by Daily Volume and Users | +| openbb.crypto.disc.top_dexes | The Top DeFi Exchanges | +| openbb.crypto.disc.top_games | The Top DeFi Games | +| openbb.crypto.disc.top_nfts | The Top NFTs | +| openbb.crypto.disc.trending | Trending Coins on CoinGecko | ## Examples @@ -64,13 +65,13 @@ Search coins on CoinGecko, or compare them all. openbb.crypto.disc.coins().head(5) ``` -| | id | symbol | name | image | current_price | market_cap | market_cap_rank | fully_diluted_valuation | total_volume | high_24h | low_24h | price_change_24h | price_change_percentage_24h | market_cap_change_24h | market_cap_change_percentage_24h | circulating_supply | total_supply | max_supply | ath | ath_change_percentage | ath_date | atl | atl_change_percentage | atl_date | roi | last_updated | price_change_percentage_14d_in_currency | price_change_percentage_1h_in_currency | price_change_percentage_1y_in_currency | price_change_percentage_200d_in_currency | price_change_percentage_24h_in_currency | price_change_percentage_30d_in_currency | price_change_percentage_7d_in_currency | -|----:|:--------------|:---------|:--------------|:--------------------------------------------------------------------------------------|----------------:|-------------:|------------------:|--------------------------:|---------------:|-------------:|-------------:|-------------------:|------------------------------:|------------------------:|-----------------------------------:|---------------------:|---------------:|-------------:|-------------:|------------------------:|:-------------------------|------------:|------------------------:|:-------------------------|:----------------------------------------------------------------------------------|:-------------------------|------------------------------------------:|-----------------------------------------:|-----------------------------------------:|-------------------------------------------:|------------------------------------------:|------------------------------------------:|-----------------------------------------:| -| 170 | 0x | zrx | 0x | https://assets.coingecko.com/coins/images/863/large/0x.png?1547034672 | 0.192066 | 162596592 | 171 | 1.91855e+08 | 7.92999e+06 | 0.198545 | 0.190939 | -0.00511834 | -2.59572 | -4.64766e+06 | -2.77897 | 8.47496e+08 | 1e+09 | 1e+09 | 2.5 | -92.3016 | 2018-01-13T00:00:00.000Z | 0.120667 | 59.3019 | 2020-03-13T02:27:49.563Z | {'times': 3.00137262387235, 'currency': 'usd', 'percentage': 300.137262387235} | 2022-12-05T22:57:31.604Z | 6.39773 | 0.236744 | -78.329 | -48.4052 | -2.59572 | -31.7183 | -0.08195 | -| 97 | zilliqa | zil | Zilliqa | https://assets.coingecko.com/coins/images/2687/large/Zilliqa-logo.png?1547036894 | 0.0227407 | 344299494 | 98 | 4.77046e+08 | 1.92004e+07 | 0.0235163 | 0.0226905 | -0.000172456 | -0.75265 | -2.93894e+06 | -0.84638 | 1.51564e+10 | 2.1e+10 | 2.1e+10 | 0.255376 | -91.0876 | 2021-05-06T17:33:45.940Z | 0.00239616 | 849.86 | 2020-03-13T02:22:55.161Z | {'times': 1.131460045428967, 'currency': 'eth', 'percentage': 113.14600454289669} | 2022-12-05T22:57:22.010Z | 7.01544 | -0.119826 | -67.7389 | -52.7247 | -0.752652 | -30.9379 | -0.991144 | -| 189 | zencash | zen | Horizen | https://assets.coingecko.com/coins/images/691/large/horizen.png?1555052241 | 10.64 | 139250373 | 190 | 2.22972e+08 | 5.44128e+06 | 11.07 | 10.62 | -0.264045 | -2.42165 | -3.61206e+06 | -2.52835 | 1.31149e+07 | 2.1e+07 | 2.1e+07 | 165.92 | -93.5817 | 2021-05-08T06:00:30.087Z | 3.26 | 226.208 | 2019-10-17T00:00:00.000Z | | 2022-12-05T22:57:34.376Z | 21.2037 | -0.57332 | -86.651 | -44.0292 | -2.42165 | -25.8735 | 11.1271 | -| 63 | zcash | zec | Zcash | https://assets.coingecko.com/coins/images/486/large/circle-zcash-color.png?1547034197 | 46.24 | 602735976 | 64 | 9.69752e+08 | 3.57518e+07 | 47.32 | 45.31 | 0.479718 | 1.04838 | 5.91658e+06 | 0.99135 | 1.30523e+07 | 2.1e+07 | 2.1e+07 | 3191.93 | -98.5521 | 2016-10-29T00:00:00.000Z | 19.75 | 133.959 | 2020-03-13T02:20:55.002Z | | 2022-12-05T22:57:30.607Z | 21.4551 | 0.502131 | -75.4374 | -53.9461 | 1.04838 | -14.1037 | 13.3262 | -| 141 | yearn-finance | yfi | yearn.finance | https://assets.coingecko.com/coins/images/11849/large/yfi-192x192.png?1598325330 | 7082.34 | 220754373 | 142 | 2.59099e+08 | 4.54938e+07 | 7472.6 | 7052.76 | -157.22 | -2.17168 | -5.96275e+06 | -2.63004 | 31239.8 | 36666 | 36666 | 90787 | -92.1948 | 2021-05-12T00:29:37.713Z | 31.65 | 22292.3 | 2020-07-18T12:26:27.150Z | | 2022-12-05T22:57:24.815Z | 15.7094 | -0.124164 | -71.239 | -22.0297 | -2.17168 | -15.4178 | 13.2592 | +| | id | symbol | name | image | current_price | market_cap | market_cap_rank | fully_diluted_valuation | total_volume | high_24h | low_24h | price_change_24h | price_change_percentage_24h | market_cap_change_24h | market_cap_change_percentage_24h | circulating_supply | total_supply | max_supply | ath | ath_change_percentage | ath_date | atl | atl_change_percentage | atl_date | roi | last_updated | price_change_percentage_14d_in_currency | price_change_percentage_1h_in_currency | price_change_percentage_1y_in_currency | price_change_percentage_200d_in_currency | price_change_percentage_24h_in_currency | price_change_percentage_30d_in_currency | price_change_percentage_7d_in_currency | +| --: | :------------ | :----- | :------------ | :------------------------------------------------------------------------------------ | ------------: | ---------: | --------------: | ----------------------: | -----------: | --------: | --------: | ---------------: | --------------------------: | --------------------: | -------------------------------: | -----------------: | -----------: | ---------: | -------: | --------------------: | :----------------------- | ---------: | --------------------: | :----------------------- | :---------------------------------------------------------------------------------- | :----------------------- | --------------------------------------: | -------------------------------------: | -------------------------------------: | ---------------------------------------: | --------------------------------------: | --------------------------------------: | -------------------------------------: | +| 170 | 0x | zrx | 0x | https://assets.coingecko.com/coins/images/863/large/0x.png?1547034672 | 0.192066 | 162596592 | 171 | 1.91855e+08 | 7.92999e+06 | 0.198545 | 0.190939 | -0.00511834 | -2.59572 | -4.64766e+06 | -2.77897 | 8.47496e+08 | 1e+09 | 1e+09 | 2.5 | -92.3016 | 2018-01-13T00:00:00.000Z | 0.120667 | 59.3019 | 2020-03-13T02:27:49.563Z | \{'times': 3.00137262387235, 'currency': 'usd', 'percentage': 300.137262387235\} | 2022-12-05T22:57:31.604Z | 6.39773 | 0.236744 | -78.329 | -48.4052 | -2.59572 | -31.7183 | -0.08195 | +| 97 | zilliqa | zil | Zilliqa | https://assets.coingecko.com/coins/images/2687/large/Zilliqa-logo.png?1547036894 | 0.0227407 | 344299494 | 98 | 4.77046e+08 | 1.92004e+07 | 0.0235163 | 0.0226905 | -0.000172456 | -0.75265 | -2.93894e+06 | -0.84638 | 1.51564e+10 | 2.1e+10 | 2.1e+10 | 0.255376 | -91.0876 | 2021-05-06T17:33:45.940Z | 0.00239616 | 849.86 | 2020-03-13T02:22:55.161Z | \{'times': 1.131460045428967, 'currency': 'eth', 'percentage': 113.14600454289669\} | 2022-12-05T22:57:22.010Z | 7.01544 | -0.119826 | -67.7389 | -52.7247 | -0.752652 | -30.9379 | -0.991144 | +| 189 | zencash | zen | Horizen | https://assets.coingecko.com/coins/images/691/large/horizen.png?1555052241 | 10.64 | 139250373 | 190 | 2.22972e+08 | 5.44128e+06 | 11.07 | 10.62 | -0.264045 | -2.42165 | -3.61206e+06 | -2.52835 | 1.31149e+07 | 2.1e+07 | 2.1e+07 | 165.92 | -93.5817 | 2021-05-08T06:00:30.087Z | 3.26 | 226.208 | 2019-10-17T00:00:00.000Z | | 2022-12-05T22:57:34.376Z | 21.2037 | -0.57332 | -86.651 | -44.0292 | -2.42165 | -25.8735 | 11.1271 | +| 63 | zcash | zec | Zcash | https://assets.coingecko.com/coins/images/486/large/circle-zcash-color.png?1547034197 | 46.24 | 602735976 | 64 | 9.69752e+08 | 3.57518e+07 | 47.32 | 45.31 | 0.479718 | 1.04838 | 5.91658e+06 | 0.99135 | 1.30523e+07 | 2.1e+07 | 2.1e+07 | 3191.93 | -98.5521 | 2016-10-29T00:00:00.000Z | 19.75 | 133.959 | 2020-03-13T02:20:55.002Z | | 2022-12-05T22:57:30.607Z | 21.4551 | 0.502131 | -75.4374 | -53.9461 | 1.04838 | -14.1037 | 13.3262 | +| 141 | yearn-finance | yfi | yearn.finance | https://assets.coingecko.com/coins/images/11849/large/yfi-192x192.png?1598325330 | 7082.34 | 220754373 | 142 | 2.59099e+08 | 4.54938e+07 | 7472.6 | 7052.76 | -157.22 | -2.17168 | -5.96275e+06 | -2.63004 | 31239.8 | 36666 | 36666 | 90787 | -92.1948 | 2021-05-12T00:29:37.713Z | 31.65 | 22292.3 | 2020-07-18T12:26:27.150Z | | 2022-12-05T22:57:24.815Z | 15.7094 | -0.124164 | -71.239 | -22.0297 | -2.17168 | -15.4178 | 13.2592 | Coins can be filtered by category. For a list of defined categories enter: @@ -84,13 +85,13 @@ The category chosen below is called, `big-data`. openbb.crypto.disc.coins(category = categories[10], sortby = 'market_cap').head(5) ``` -| | id | symbol | name | image | current_price | market_cap | market_cap_rank | fully_diluted_valuation | total_volume | high_24h | low_24h | price_change_24h | price_change_percentage_24h | market_cap_change_24h | market_cap_change_percentage_24h | circulating_supply | total_supply | max_supply | ath | ath_change_percentage | ath_date | atl | atl_change_percentage | atl_date | roi | last_updated | price_change_percentage_14d_in_currency | price_change_percentage_1h_in_currency | price_change_percentage_1y_in_currency | price_change_percentage_200d_in_currency | price_change_percentage_24h_in_currency | price_change_percentage_30d_in_currency | price_change_percentage_7d_in_currency | -|---:|:-----------------|:---------|:---------|:-----------------------------------------------------------------------------------------|----------------:|-------------:|------------------:|--------------------------:|-----------------:|-----------:|----------:|-------------------:|------------------------------:|------------------------:|-----------------------------------:|---------------------:|---------------:|-------------:|----------:|------------------------:|:-------------------------|-----------:|------------------------:|:-------------------------|:------------------------------------------------------------------------------------|:-------------------------|------------------------------------------:|-----------------------------------------:|-----------------------------------------:|-------------------------------------------:|------------------------------------------:|------------------------------------------:|-----------------------------------------:| -| 0 | dock | dock | Dock | https://assets.coingecko.com/coins/images/3978/large/dock-icon-dark-large.png?1623764407 | 0.0163913 | 7.04484e+07 | 295 | nan | 567668 | 0.0170636 | 0.0163263 | -0.00031004 | -1.85637 | -2.34457e+06 | -3.22088 | 0 | 1e+09 | nan | 0.241848 | -93.2225 | 2018-05-04T05:29:09.155Z | 0.00259319 | 532.083 | 2020-03-13T02:24:35.312Z | {'times': -0.8420344706449371, 'currency': 'eth', 'percentage': -84.20344706449372} | 2022-12-05T23:04:48.481Z | 11.105 | 0.113349 | -79.607 | -17.3245 | -1.85637 | -19.6563 | 0.481131 | -| 1 | covalent | cqt | Covalent | https://assets.coingecko.com/coins/images/14168/large/covalent-cqt.png?1624545218 | 0.099484 | 4.18854e+07 | 431 | 9.95348e+07 | 997478 | 0.112201 | 0.095826 | -0.0110446 | -9.99251 | -4.62241e+06 | -9.93901 | 4.20811e+08 | 1e+09 | 1e+09 | 2.08 | -95.2091 | 2021-08-14T05:30:40.858Z | 0.051932 | 91.5619 | 2022-08-01T23:38:54.301Z | | 2022-12-05T23:04:47.896Z | 16.5464 | 1.49149 | -87.4469 | -34.8706 | -9.99251 | -21.1618 | -16.3863 | -| 2 | gxchain | gxc | GXChain | https://assets.coingecko.com/coins/images/1089/large/26296223.png?1571192241 | 0.46468 | 3.48511e+07 | 476 | nan | 114097 | 0.797016 | 0.359858 | -0.331496 | -41.636 | -2.48954e+07 | -41.6683 | 7.5e+07 | 1e+08 | nan | 10.61 | -95.62 | 2018-01-13T00:00:00.000Z | 0.189778 | 144.839 | 2020-03-13T02:24:02.919Z | | 2022-12-05T23:04:01.358Z | 25.3322 | 3.68092 | -83.5683 | 13.1713 | -41.636 | -0.22209 | 31.9026 | -| 3 | insights-network | instar | INSTAR | https://assets.coingecko.com/coins/images/3504/large/2558.png?1547038269 | 0.0362529 | 2.85208e+07 | 534 | nan | 19.93 | 0.0370935 | 0.0359575 | -0.000214289 | -0.58762 | -5.51571e+06 | -16.2053 | 0 | 3e+08 | nan | 0.27882 | -86.9978 | 2022-10-02T09:16:16.012Z | 0.00467988 | 674.655 | 2020-03-13T02:22:38.395Z | {'times': -0.7583139455766651, 'currency': 'usd', 'percentage': -75.83139455766651} | 2022-12-05T18:39:15.686Z | -1.2191 | nan | 27.2158 | 113.695 | -0.587622 | -44.2698 | 3.3329 | -| 4 | bonfida | fida | Bonfida | https://assets.coingecko.com/coins/images/13395/large/bonfida.png?1658327819 | 0.392327 | 2.36672e+07 | 585 | 3.92307e+08 | 6.01989e+06 | 0.401193 | 0.386429 | -0.00802685 | -2.00494 | -441335 | -1.83062 | 6.03284e+07 | 1e+09 | 1e+09 | 18.77 | -97.9102 | 2021-11-03T20:34:33.492Z | 0.113165 | 246.695 | 2020-12-22T10:58:52.143Z | | 2022-12-05T23:04:56.497Z | -31.5948 | -0.13385 | -94.9581 | -30.7982 | -2.00494 | -5.84654 | -12.1443 | +| | id | symbol | name | image | current_price | market_cap | market_cap_rank | fully_diluted_valuation | total_volume | high_24h | low_24h | price_change_24h | price_change_percentage_24h | market_cap_change_24h | market_cap_change_percentage_24h | circulating_supply | total_supply | max_supply | ath | ath_change_percentage | ath_date | atl | atl_change_percentage | atl_date | roi | last_updated | price_change_percentage_14d_in_currency | price_change_percentage_1h_in_currency | price_change_percentage_1y_in_currency | price_change_percentage_200d_in_currency | price_change_percentage_24h_in_currency | price_change_percentage_30d_in_currency | price_change_percentage_7d_in_currency | +| --: | :--------------- | :----- | :------- | :--------------------------------------------------------------------------------------- | ------------: | ----------: | --------------: | ----------------------: | -----------: | --------: | --------: | ---------------: | --------------------------: | --------------------: | -------------------------------: | -----------------: | -----------: | ---------: | -------: | --------------------: | :----------------------- | ---------: | --------------------: | :----------------------- | :------------------------------------------------------------------------------------ | :----------------------- | --------------------------------------: | -------------------------------------: | -------------------------------------: | ---------------------------------------: | --------------------------------------: | --------------------------------------: | -------------------------------------: | +| 0 | dock | dock | Dock | https://assets.coingecko.com/coins/images/3978/large/dock-icon-dark-large.png?1623764407 | 0.0163913 | 7.04484e+07 | 295 | nan | 567668 | 0.0170636 | 0.0163263 | -0.00031004 | -1.85637 | -2.34457e+06 | -3.22088 | 0 | 1e+09 | nan | 0.241848 | -93.2225 | 2018-05-04T05:29:09.155Z | 0.00259319 | 532.083 | 2020-03-13T02:24:35.312Z | \{'times': -0.8420344706449371, 'currency': 'eth', 'percentage': -84.20344706449372\} | 2022-12-05T23:04:48.481Z | 11.105 | 0.113349 | -79.607 | -17.3245 | -1.85637 | -19.6563 | 0.481131 | +| 1 | covalent | cqt | Covalent | https://assets.coingecko.com/coins/images/14168/large/covalent-cqt.png?1624545218 | 0.099484 | 4.18854e+07 | 431 | 9.95348e+07 | 997478 | 0.112201 | 0.095826 | -0.0110446 | -9.99251 | -4.62241e+06 | -9.93901 | 4.20811e+08 | 1e+09 | 1e+09 | 2.08 | -95.2091 | 2021-08-14T05:30:40.858Z | 0.051932 | 91.5619 | 2022-08-01T23:38:54.301Z | | 2022-12-05T23:04:47.896Z | 16.5464 | 1.49149 | -87.4469 | -34.8706 | -9.99251 | -21.1618 | -16.3863 | +| 2 | gxchain | gxc | GXChain | https://assets.coingecko.com/coins/images/1089/large/26296223.png?1571192241 | 0.46468 | 3.48511e+07 | 476 | nan | 114097 | 0.797016 | 0.359858 | -0.331496 | -41.636 | -2.48954e+07 | -41.6683 | 7.5e+07 | 1e+08 | nan | 10.61 | -95.62 | 2018-01-13T00:00:00.000Z | 0.189778 | 144.839 | 2020-03-13T02:24:02.919Z | | 2022-12-05T23:04:01.358Z | 25.3322 | 3.68092 | -83.5683 | 13.1713 | -41.636 | -0.22209 | 31.9026 | +| 3 | insights-network | instar | INSTAR | https://assets.coingecko.com/coins/images/3504/large/2558.png?1547038269 | 0.0362529 | 2.85208e+07 | 534 | nan | 19.93 | 0.0370935 | 0.0359575 | -0.000214289 | -0.58762 | -5.51571e+06 | -16.2053 | 0 | 3e+08 | nan | 0.27882 | -86.9978 | 2022-10-02T09:16:16.012Z | 0.00467988 | 674.655 | 2020-03-13T02:22:38.395Z | \{'times': -0.7583139455766651, 'currency': 'usd', 'percentage': -75.83139455766651\} | 2022-12-05T18:39:15.686Z | -1.2191 | nan | 27.2158 | 113.695 | -0.587622 | -44.2698 | 3.3329 | +| 4 | bonfida | fida | Bonfida | https://assets.coingecko.com/coins/images/13395/large/bonfida.png?1658327819 | 0.392327 | 2.36672e+07 | 585 | 3.92307e+08 | 6.01989e+06 | 0.401193 | 0.386429 | -0.00802685 | -2.00494 | -441335 | -1.83062 | 6.03284e+07 | 1e+09 | 1e+09 | 18.77 | -97.9102 | 2021-11-03T20:34:33.492Z | 0.113165 | 246.695 | 2020-12-22T10:58:52.143Z | | 2022-12-05T23:04:56.497Z | -31.5948 | -0.13385 | -94.9581 | -30.7982 | -2.00494 | -5.84654 | -12.1443 | ### Trending @@ -100,16 +101,16 @@ Print the trending coins on CoinGecko: openbb.crypto.disc.trending() ``` -| | Symbol | Name | market_cap Cap Rank | -|---:|:--------------|:--------------|----------------------:| -| 0 | chainlink | Chainlink | 21 | -| 1 | magiccraft | MagicCraft | 806 | -| 2 | apollo | Apollo | 858 | -| 3 | gmx | GMX | 86 | -| 4 | dawn-protocol | Dawn Protocol | 406 | -| 5 | evmos | Evmos | 149 | -| 6 | maple | Maple | 443 | -| 7 | aptos | Aptos | 59 | +| | Symbol | Name | market_cap Cap Rank | +| --: | :------------ | :------------ | ------------------: | +| 0 | chainlink | Chainlink | 21 | +| 1 | magiccraft | MagicCraft | 806 | +| 2 | apollo | Apollo | 858 | +| 3 | gmx | GMX | 86 | +| 4 | dawn-protocol | Dawn Protocol | 406 | +| 5 | evmos | Evmos | 149 | +| 6 | maple | Maple | 443 | +| 7 | aptos | Aptos | 59 | ### Losers @@ -119,11 +120,11 @@ Filter coins by the changes over various windows of time, from an hour to a year openbb.crypto.disc.losers().head(3) ``` -| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 1h [%] | -|---:|:---------|:--------------------|---------------:|-------------:|------------------:|-------------:|----------------:| -| 34 | ape | ApeCoin | 3.95 | 1430668301 | 35 | 225914151 | -0.613265 | -| 48 | theta | Theta Network | 0.879573 | 880099193 | 49 | 19024380 | -0.159237 | -| 12 | ltc | Litecoin | 80.28 | 5764526837 | 13 | 1079151325 | -0.147648 | +| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 1h [%] | +| --: | :----- | :------------ | --------: | ---------: | --------------: | ---------: | ------------: | +| 34 | ape | ApeCoin | 3.95 | 1430668301 | 35 | 225914151 | -0.613265 | +| 48 | theta | Theta Network | 0.879573 | 880099193 | 49 | 19024380 | -0.159237 | +| 12 | ltc | Litecoin | 80.28 | 5764526837 | 13 | 1079151325 | -0.147648 | Compared to the last fourteen days: @@ -131,11 +132,11 @@ Compared to the last fourteen days: openbb.crypto.disc.losers(interval = '14d').head(3) ``` -| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 14d [%] | -|---:|:---------|:----------|------------:|-------------:|------------------:|-------------:|-----------------:| -| 31 | algo | Algorand | 0.237655 | 1691877131 | 32 | 79911891 | -3.84964 | -| 22 | leo | LEO Token | 3.79 | 3541787576 | 23 | 2082712 | -2.70556 | -| 38 | flow | Flow | 1.11 | 1150005942 | 39 | 44608861 | -2.16063 | +| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 14d [%] | +| --: | :----- | :-------- | --------: | ---------: | --------------: | ---------: | -------------: | +| 31 | algo | Algorand | 0.237655 | 1691877131 | 32 | 79911891 | -3.84964 | +| 22 | leo | LEO Token | 3.79 | 3541787576 | 23 | 2082712 | -2.70556 | +| 38 | flow | Flow | 1.11 | 1150005942 | 39 | 44608861 | -2.16063 | Over one-year: @@ -143,8 +144,8 @@ Over one-year: openbb.crypto.disc.losers(interval = '1y').head(3) ``` -| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 1y [%] | -|---:|:---------|:-------------------|------------:|-------------:|------------------:|-------------:|----------------:| -| 39 | lunc | Terra Luna Classic | 0.00017433 | 1042097683 | 40 | 75780496 | -99.9997 | -| 16 | sol | Solana | 13.87 | 5045641411 | 17 | 382220595 | -92.9463 | -| 43 | axs | Axie Infinity | 8.92 | 1004779023 | 44 | 707998935 | -91.6799 | +| | Symbol | Name | Price [$] | Market Cap | Market Cap Rank | Volume [$] | Change 1y [%] | +| --: | :----- | :----------------- | ---------: | ---------: | --------------: | ---------: | ------------: | +| 39 | lunc | Terra Luna Classic | 0.00017433 | 1042097683 | 40 | 75780496 | -99.9997 | +| 16 | sol | Solana | 13.87 | 5045641411 | 17 | 382220595 | -92.9463 | +| 43 | axs | Axie Infinity | 8.92 | 1004779023 | 44 | 707998935 | -91.6799 | diff --git a/website/content/sdk/data-available/crypto/index.md b/website/content/sdk/data-available/crypto/index.md index 3b63edc0b2e9..ac3cad040fed 100644 --- a/website/content/sdk/data-available/crypto/index.md +++ b/website/content/sdk/data-available/crypto/index.md @@ -1,7 +1,8 @@ --- title: Crypto sidebar_position: 0 -description: This Docusaurus page is dedicated to providing a detailed guide on how +description: + This Docusaurus page is dedicated to providing a detailed guide on how Cryptocurrency applications and dashboards can be built quickly using the OpenBB Terminal's Crypto Module. It provides an outline on how to use SDK functions at the 'openbb.crypto' level, rundown of functions and modules, along with sample Python @@ -9,18 +10,18 @@ description: This Docusaurus page is dedicated to providing a detailed guide on coins and more. This page can be useful for those working on Cryptocurrency applications, particularly those relying on Python or OpenBB Terminal. keywords: -- Docusaurus -- Cryptocurrency -- Web Application -- Crypto Module -- SDK Functions -- Digital Assets -- Onchain Metrics -- Data visualisation -- CCXT -- Trending Coins -- Liquidity Measurement -- Coin Ranking + - Docusaurus + - Cryptocurrency + - Web Application + - Crypto Module + - SDK Functions + - Digital Assets + - Onchain Metrics + - Data visualisation + - CCXT + - Trending Coins + - Liquidity Measurement + - Coin Ranking --- The Crypto module wraps the functions of the OpenBB Terminal menu. This allows web applications and dashboards to be built quickly on top of the existing infrastructure. Navigating the functions is similar to operating the OpenBB Terminal. @@ -95,7 +96,7 @@ Help on Operation in module openbb_terminal.core.library.operation: ```
-
+
| | Exchange |
| --- | -----------------: |
diff --git a/website/content/sdk/data-available/etf.md b/website/content/sdk/data-available/etf.md
index 3902ecda5597..9f72ed2e69ae 100644
--- a/website/content/sdk/data-available/etf.md
+++ b/website/content/sdk/data-available/etf.md
@@ -1,6 +1,7 @@
---
title: ETF
-description: This documentation page provides a comprehensive guide on how to use
+description:
+ This documentation page provides a comprehensive guide on how to use
the ETF module of the OpenBB Terminal SDK for programmatic access. It covers a list
of functions within the ETF module, how to import the SDK, how to print contents
of the SDK, how to use the ETF module in various situations such as getting list
@@ -8,15 +9,15 @@ description: This documentation page provides a comprehensive guide on how to us
holdings of a specific ETF, performing ETF screening, and retrieving current top
gainers, losers, and volume for ETFs.
keywords:
-- OpenBB Terminal SDK
-- ETF module
-- programmatic access
-- import SDK
-- perform ETF screening
-- get ETF holdings
-- compare performance metrics
-- retrieve top gainers and losers
-- retrieve top volume for ETFs
+ - OpenBB Terminal SDK
+ - ETF module
+ - programmatic access
+ - import SDK
+ - perform ETF screening
+ - get ETF holdings
+ - compare performance metrics
+ - retrieve top gainers and losers
+ - retrieve top volume for ETFs
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -38,22 +39,22 @@ import pandas as pd
Below is a brief description of each function within the ETF module:
-|Path |Type |Description |
-|:---------|:---------:|------------------------------:|
-|openbb.etf.candle |Function |Chart OHLC + Volume + Moving Averages |
-|openbb.etf.disc |Sub-Module |Best/Worst/Highest Volume ETFs Today |
-|openbb.etf.etf_by_category |Function |Lookup by Category |
-|openbb.etf.etf_by_name |Function |Lookup by Name |
-|openbb.etf.holdings |Function |Holdings and Weights |
-|openbb.etf.ld |Function |Lookup by Description |
-|openbb.etf.load |Function |Get Historical Price Data |
-|openbb.etf.ln |Function |Lookup by Name (More Details Than `by_name`) |
-|openbb.etf.news |Function |News Headlines for a Ticker |
-|openbb.etf.overview |Function |Basic Statistics for an ETF |
-|openbb.etf.scr |Sub-Module |ETF Screener |
-|openbb.etf.summary |Function |Text Description and Summary of an ETF |
-|openbb.etf.symbols |Dictionary |Dictionary of {Ticker:Name} |
-|openbb.etf.weights |Function |Table or Pie Graph of Sector Weightings |
+| Path | Type | Description |
+| :------------------------- | :--------: | -------------------------------------------: |
+| openbb.etf.candle | Function | Chart OHLC + Volume + Moving Averages |
+| openbb.etf.disc | Sub-Module | Best/Worst/Highest Volume ETFs Today |
+| openbb.etf.etf_by_category | Function | Lookup by Category |
+| openbb.etf.etf_by_name | Function | Lookup by Name |
+| openbb.etf.holdings | Function | Holdings and Weights |
+| openbb.etf.ld | Function | Lookup by Description |
+| openbb.etf.load | Function | Get Historical Price Data |
+| openbb.etf.ln | Function | Lookup by Name (More Details Than `by_name`) |
+| openbb.etf.news | Function | News Headlines for a Ticker |
+| openbb.etf.overview | Function | Basic Statistics for an ETF |
+| openbb.etf.scr | Sub-Module | ETF Screener |
+| openbb.etf.summary | Function | Text Description and Summary of an ETF |
+| openbb.etf.symbols | Dictionary | Dictionary of `{Ticker:Name}` |
+| openbb.etf.weights | Function | Table or Pie Graph of Sector Weightings |
Alternatively you can print the contents of the ETF SDK with:
@@ -78,14 +79,14 @@ categories = pd.DataFrame(categories[1::], columns = ['Type'])
categories.head(6)
```
-| Type |
-|:-----------------:|
-| Financials |
+| Type |
+| :--------------: |
+| Financials |
| Emerging Markets |
-| Industrials |
-| Factors |
-| Utilities |
-| Bonds |
+| Industrials |
+| Factors |
+| Utilities |
+| Bonds |
Replacing the empty category in the syntax above will return the ETFs within that category:
@@ -95,14 +96,13 @@ etf_category = pd.DataFrame.from_dict(openbb.etf.etf_by_category('Emerging Marke
etf_category.head(2)
```
-| symbol | name | currency | summary | category_group | category | family | exchange | market |
-|:---------|:----------------------------------------------|:-----------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|:-----------------|:---------------------------|:-----------|:----------|
-| AAXJ | iShares MSCI All Country Asia ex Japan ETF | USD | The investment seeks to track the investment results of the MSCI AC Asia ex Japan Index. | Equities | Emerging Markets | BlackRock Asset Management | NMS | us_market |
-| | | | The fund will invest at least 90% of its assets in the component securities of the index and in investments that have economic characteristics that are substantially identical to the component securities of the index. The index is a free float-adjusted market capitalization index designed to measure equity market performance of securities from the following 11 developed and emerging market countries or regions: China, Hong Kong, India, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, South Korea, Taiwan and Thailand. | | | | | |
-| JHEM | John Hancock Multifactor Emerging Markets ETF | USD | The investment seeks to provide investment results that closely correspond, before fees and expenses, to the performance of the John Hancock Dimensional Emerging Markets Index (the index). | Equities | Emerging Markets | John Hancock | PCX | us_market |
-| | | | The fund normally invests at least 80% of its net assets (plus any borrowings for investment purposes) in securities included in the index, in depositary receipts representing securities included in the index, and in underlying stocks in respect of depositary receipts included in the index. The index is designed to comprise a subset of securities associated with emerging markets, which may include frontier markets (emerging markets in an earlier stage of development). | | | | | |
+| symbol | name | currency | summary | category_group | category | family | exchange | market |
+| :----- | :-------------------------------------------- | :------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | :--------------- | :------------------------- | :------- | :-------- |
+| AAXJ | iShares MSCI All Country Asia ex Japan ETF | USD | The investment seeks to track the investment results of the MSCI AC Asia ex Japan Index. | Equities | Emerging Markets | BlackRock Asset Management | NMS | us_market |
+| | | | The fund will invest at least 90% of its assets in the component securities of the index and in investments that have economic characteristics that are substantially identical to the component securities of the index. The index is a free float-adjusted market capitalization index designed to measure equity market performance of securities from the following 11 developed and emerging market countries or regions: China, Hong Kong, India, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, South Korea, Taiwan and Thailand. | | | | | |
+| JHEM | John Hancock Multifactor Emerging Markets ETF | USD | The investment seeks to provide investment results that closely correspond, before fees and expenses, to the performance of the John Hancock Dimensional Emerging Markets Index (the index). | Equities | Emerging Markets | John Hancock | PCX | us_market |
+| | | | The fund normally invests at least 80% of its net assets (plus any borrowings for investment purposes) in securities included in the index, in depositary receipts representing securities included in the index, and in underlying stocks in respect of depositary receipts included in the index. The index is designed to comprise a subset of securities associated with emerging markets, which may include frontier markets (emerging markets in an earlier stage of development). | | | | | |
-
### ETF Tickers
A list of all tickers in the specific category can be generated from the index of the above DataFrame, `etf_category`:
@@ -121,13 +121,13 @@ performance = performance.sort_values(by=['3M'], ascending=False)
performance.head(5)
```
-| Ticker | 1W | 1M | 3M | 6M | 1Y | YTD | 1W Volatility | 1M Volatility | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
-|:---------|-------:|--------:|-------:|-------:|--------:|--------:|----------------:|----------------:|:--------|-------------:|-------------:|--------:|---------:|-----------------:|
-| CHB | 0.0301 | -0.015 | 0.1123 | 0.0086 | -0.132 | -0.1277 | 0.0105 | 0.0048 | | 1130 | 0.04 | 8.22 | 0.0123 | 21 |
-| INCO | 0.0193 | 0.0716 | 0.1092 | 0.1543 | 0.2706 | 0.3171 | 0.0066 | 0.0049 | | 17810 | 1.62 | 59.77 | 0.0073 | 14060 |
-| GLIN | 0.0251 | 0.0733 | 0.1083 | 0.221 | 0.2704 | 0.3319 | 0.0105 | 0.0079 | | 20360 | 0.89 | 43.5 | 0.0133 | 8833 |
-| ILF | 0.0497 | 0.0631 | 0.1032 | 0.062 | 0.3082 | 0.2768 | 0.0141 | 0.0135 | | 1.18e+06 | 2.16 | 29.23 | 0.0215 | 1237337 |
-| SMIN | 0.0174 | 0.0573 | 0.0914 | 0.2128 | 0.2848 | 0.3447 | 0.0078 | 0.0074 | | 99980 | 5.61 | 69.6 | 0.0053 | 272774 |
+| Ticker | 1W | 1M | 3M | 6M | 1Y | YTD | 1W Volatility | 1M Volatility | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
+| :----- | -----: | -----: | -----: | -----: | -----: | ------: | ------------: | ------------: | :---- | ---------: | ---------: | ----: | -----: | ------: |
+| CHB | 0.0301 | -0.015 | 0.1123 | 0.0086 | -0.132 | -0.1277 | 0.0105 | 0.0048 | | 1130 | 0.04 | 8.22 | 0.0123 | 21 |
+| INCO | 0.0193 | 0.0716 | 0.1092 | 0.1543 | 0.2706 | 0.3171 | 0.0066 | 0.0049 | | 17810 | 1.62 | 59.77 | 0.0073 | 14060 |
+| GLIN | 0.0251 | 0.0733 | 0.1083 | 0.221 | 0.2704 | 0.3319 | 0.0105 | 0.0079 | | 20360 | 0.89 | 43.5 | 0.0133 | 8833 |
+| ILF | 0.0497 | 0.0631 | 0.1032 | 0.062 | 0.3082 | 0.2768 | 0.0141 | 0.0135 | | 1.18e+06 | 2.16 | 29.23 | 0.0215 | 1237337 |
+| SMIN | 0.0174 | 0.0573 | 0.0914 | 0.2128 | 0.2848 | 0.3447 | 0.0078 | 0.0074 | | 99980 | 5.61 | 69.6 | 0.0053 | 272774 |
### Holdings
@@ -138,13 +138,13 @@ holdings = openbb.etf.holdings('DIA').reset_index()
holdings.head(5)
```
-| | Symbol | Name | % Of Etf | Shares |
-|---:|:---------|:--------------------------------|:-----------|---------:|
-| 0 | UNH | UnitedHealth Group Incorporated | 10.09% | 5985297 |
-| 1 | GS | The Goldman Sachs Group, Inc. | 7.51% | 5985297 |
-| 2 | HD | The Home Depot, Inc. | 6.03% | 5985297 |
-| 3 | AMGN | Amgen Inc. | 5.61% | 5985297 |
-| 4 | MCD | McDonald's Corporation | 5.35% | 5985297 |
+| | Symbol | Name | % Of Etf | Shares |
+| --: | :----- | :------------------------------ | :------- | ------: |
+| 0 | UNH | UnitedHealth Group Incorporated | 10.09% | 5985297 |
+| 1 | GS | The Goldman Sachs Group, Inc. | 7.51% | 5985297 |
+| 2 | HD | The Home Depot, Inc. | 6.03% | 5985297 |
+| 3 | AMGN | Amgen Inc. | 5.61% | 5985297 |
+| 4 | MCD | McDonald's Corporation | 5.35% | 5985297 |
### Disc
@@ -165,10 +165,10 @@ movers = openbb.etf.disc.mover()
movers.head(5)
```
-| | | Price | Chg | %Chg | Vol |
-|---:|:---------------------------------------------------------|--------:|-------:|-------:|:-------|
-| 0 | Direxion Daily Semiconductor Bear 3X Shares | 35.3101 | 3.3101 | 10.34 | 24.5M |
-| 1 | ProShares UltraShort Bloomberg Natural Gas | 18.09 | 1.19 | 7.04 | 4.4M |
-| 2 | MicroSectors FANG & Innovation -3x Inverse Leveraged ETN | 28.98 | 1.83 | 6.74 | 160.1K |
-| 3 | Direxion Daily Dow Jones Internet Bear 3X Shares | 32.14 | 1.91 | 6.32 | 554.2K |
-| 4 | Direxion Daily S&P 500 High Beta Bear 3X Shares | 6.4652 | 0.3752 | 6.16 | 1.2M |
+| | | Price | Chg | %Chg | Vol |
+| --: | :------------------------------------------------------- | ------: | -----: | ----: | :----- |
+| 0 | Direxion Daily Semiconductor Bear 3X Shares | 35.3101 | 3.3101 | 10.34 | 24.5M |
+| 1 | ProShares UltraShort Bloomberg Natural Gas | 18.09 | 1.19 | 7.04 | 4.4M |
+| 2 | MicroSectors FANG & Innovation -3x Inverse Leveraged ETN | 28.98 | 1.83 | 6.74 | 160.1K |
+| 3 | Direxion Daily Dow Jones Internet Bear 3X Shares | 32.14 | 1.91 | 6.32 | 554.2K |
+| 4 | Direxion Daily S&P 500 High Beta Bear 3X Shares | 6.4652 | 0.3752 | 6.16 | 1.2M |
diff --git a/website/content/sdk/faqs/bugs_support_feedback.md b/website/content/sdk/faqs/bugs_support_feedback.md
index f078e484eee6..70e508e47577 100644
--- a/website/content/sdk/faqs/bugs_support_feedback.md
+++ b/website/content/sdk/faqs/bugs_support_feedback.md
@@ -1,20 +1,21 @@
---
title: Bugs, Support, and Feedback
sidebar_position: 6
-description: This page provides information on how to deal with bugs, get support,
+description:
+ This page provides information on how to deal with bugs, get support,
and provide feedback for the OpenBB Terminal. It includes details on the release
process for patches, how to report a bug, and ways to request new features or provide
suggestions for improvements.
keywords:
-- bug reporting
-- support
-- feedback
-- patches
-- GitHub
-- open source platform
-- investors
-- feature request
-- machine learning
+ - bug reporting
+ - support
+ - feedback
+ - patches
+ - GitHub
+ - open source platform
+ - investors
+ - feature request
+ - machine learning
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -23,7 +24,8 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
When an error is encountered, it is always a good idea to check the open issues on [GitHub](https://github.com/OpenBB-finance/OpenBBTerminal/issues). There may be a workaround solution for the specific problem until a patch is released.
-
CCXT Exchange List (expand to see list of exchanges supported by CCXT)
+ CCXT Exchange List (expand to see list of exchanges supported by CCXT)
| | Exchange |
| --- | -----------------: |
diff --git a/website/content/sdk/data-available/etf.md b/website/content/sdk/data-available/etf.md
index 3902ecda5597..9f72ed2e69ae 100644
--- a/website/content/sdk/data-available/etf.md
+++ b/website/content/sdk/data-available/etf.md
@@ -1,6 +1,7 @@
---
title: ETF
-description: This documentation page provides a comprehensive guide on how to use
+description:
+ This documentation page provides a comprehensive guide on how to use
the ETF module of the OpenBB Terminal SDK for programmatic access. It covers a list
of functions within the ETF module, how to import the SDK, how to print contents
of the SDK, how to use the ETF module in various situations such as getting list
@@ -8,15 +9,15 @@ description: This documentation page provides a comprehensive guide on how to us
holdings of a specific ETF, performing ETF screening, and retrieving current top
gainers, losers, and volume for ETFs.
keywords:
-- OpenBB Terminal SDK
-- ETF module
-- programmatic access
-- import SDK
-- perform ETF screening
-- get ETF holdings
-- compare performance metrics
-- retrieve top gainers and losers
-- retrieve top volume for ETFs
+ - OpenBB Terminal SDK
+ - ETF module
+ - programmatic access
+ - import SDK
+ - perform ETF screening
+ - get ETF holdings
+ - compare performance metrics
+ - retrieve top gainers and losers
+ - retrieve top volume for ETFs
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -38,22 +39,22 @@ import pandas as pd
Below is a brief description of each function within the ETF module:
-|Path |Type |Description |
-|:---------|:---------:|------------------------------:|
-|openbb.etf.candle |Function |Chart OHLC + Volume + Moving Averages |
-|openbb.etf.disc |Sub-Module |Best/Worst/Highest Volume ETFs Today |
-|openbb.etf.etf_by_category |Function |Lookup by Category |
-|openbb.etf.etf_by_name |Function |Lookup by Name |
-|openbb.etf.holdings |Function |Holdings and Weights |
-|openbb.etf.ld |Function |Lookup by Description |
-|openbb.etf.load |Function |Get Historical Price Data |
-|openbb.etf.ln |Function |Lookup by Name (More Details Than `by_name`) |
-|openbb.etf.news |Function |News Headlines for a Ticker |
-|openbb.etf.overview |Function |Basic Statistics for an ETF |
-|openbb.etf.scr |Sub-Module |ETF Screener |
-|openbb.etf.summary |Function |Text Description and Summary of an ETF |
-|openbb.etf.symbols |Dictionary |Dictionary of {Ticker:Name} |
-|openbb.etf.weights |Function |Table or Pie Graph of Sector Weightings |
+| Path | Type | Description |
+| :------------------------- | :--------: | -------------------------------------------: |
+| openbb.etf.candle | Function | Chart OHLC + Volume + Moving Averages |
+| openbb.etf.disc | Sub-Module | Best/Worst/Highest Volume ETFs Today |
+| openbb.etf.etf_by_category | Function | Lookup by Category |
+| openbb.etf.etf_by_name | Function | Lookup by Name |
+| openbb.etf.holdings | Function | Holdings and Weights |
+| openbb.etf.ld | Function | Lookup by Description |
+| openbb.etf.load | Function | Get Historical Price Data |
+| openbb.etf.ln | Function | Lookup by Name (More Details Than `by_name`) |
+| openbb.etf.news | Function | News Headlines for a Ticker |
+| openbb.etf.overview | Function | Basic Statistics for an ETF |
+| openbb.etf.scr | Sub-Module | ETF Screener |
+| openbb.etf.summary | Function | Text Description and Summary of an ETF |
+| openbb.etf.symbols | Dictionary | Dictionary of `{Ticker:Name}` |
+| openbb.etf.weights | Function | Table or Pie Graph of Sector Weightings |
Alternatively you can print the contents of the ETF SDK with:
@@ -78,14 +79,14 @@ categories = pd.DataFrame(categories[1::], columns = ['Type'])
categories.head(6)
```
-| Type |
-|:-----------------:|
-| Financials |
+| Type |
+| :--------------: |
+| Financials |
| Emerging Markets |
-| Industrials |
-| Factors |
-| Utilities |
-| Bonds |
+| Industrials |
+| Factors |
+| Utilities |
+| Bonds |
Replacing the empty category in the syntax above will return the ETFs within that category:
@@ -95,14 +96,13 @@ etf_category = pd.DataFrame.from_dict(openbb.etf.etf_by_category('Emerging Marke
etf_category.head(2)
```
-| symbol | name | currency | summary | category_group | category | family | exchange | market |
-|:---------|:----------------------------------------------|:-----------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|:-----------------|:---------------------------|:-----------|:----------|
-| AAXJ | iShares MSCI All Country Asia ex Japan ETF | USD | The investment seeks to track the investment results of the MSCI AC Asia ex Japan Index. | Equities | Emerging Markets | BlackRock Asset Management | NMS | us_market |
-| | | | The fund will invest at least 90% of its assets in the component securities of the index and in investments that have economic characteristics that are substantially identical to the component securities of the index. The index is a free float-adjusted market capitalization index designed to measure equity market performance of securities from the following 11 developed and emerging market countries or regions: China, Hong Kong, India, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, South Korea, Taiwan and Thailand. | | | | | |
-| JHEM | John Hancock Multifactor Emerging Markets ETF | USD | The investment seeks to provide investment results that closely correspond, before fees and expenses, to the performance of the John Hancock Dimensional Emerging Markets Index (the index). | Equities | Emerging Markets | John Hancock | PCX | us_market |
-| | | | The fund normally invests at least 80% of its net assets (plus any borrowings for investment purposes) in securities included in the index, in depositary receipts representing securities included in the index, and in underlying stocks in respect of depositary receipts included in the index. The index is designed to comprise a subset of securities associated with emerging markets, which may include frontier markets (emerging markets in an earlier stage of development). | | | | | |
+| symbol | name | currency | summary | category_group | category | family | exchange | market |
+| :----- | :-------------------------------------------- | :------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | :--------------- | :------------------------- | :------- | :-------- |
+| AAXJ | iShares MSCI All Country Asia ex Japan ETF | USD | The investment seeks to track the investment results of the MSCI AC Asia ex Japan Index. | Equities | Emerging Markets | BlackRock Asset Management | NMS | us_market |
+| | | | The fund will invest at least 90% of its assets in the component securities of the index and in investments that have economic characteristics that are substantially identical to the component securities of the index. The index is a free float-adjusted market capitalization index designed to measure equity market performance of securities from the following 11 developed and emerging market countries or regions: China, Hong Kong, India, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, South Korea, Taiwan and Thailand. | | | | | |
+| JHEM | John Hancock Multifactor Emerging Markets ETF | USD | The investment seeks to provide investment results that closely correspond, before fees and expenses, to the performance of the John Hancock Dimensional Emerging Markets Index (the index). | Equities | Emerging Markets | John Hancock | PCX | us_market |
+| | | | The fund normally invests at least 80% of its net assets (plus any borrowings for investment purposes) in securities included in the index, in depositary receipts representing securities included in the index, and in underlying stocks in respect of depositary receipts included in the index. The index is designed to comprise a subset of securities associated with emerging markets, which may include frontier markets (emerging markets in an earlier stage of development). | | | | | |
-
### ETF Tickers
A list of all tickers in the specific category can be generated from the index of the above DataFrame, `etf_category`:
@@ -121,13 +121,13 @@ performance = performance.sort_values(by=['3M'], ascending=False)
performance.head(5)
```
-| Ticker | 1W | 1M | 3M | 6M | 1Y | YTD | 1W Volatility | 1M Volatility | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
-|:---------|-------:|--------:|-------:|-------:|--------:|--------:|----------------:|----------------:|:--------|-------------:|-------------:|--------:|---------:|-----------------:|
-| CHB | 0.0301 | -0.015 | 0.1123 | 0.0086 | -0.132 | -0.1277 | 0.0105 | 0.0048 | | 1130 | 0.04 | 8.22 | 0.0123 | 21 |
-| INCO | 0.0193 | 0.0716 | 0.1092 | 0.1543 | 0.2706 | 0.3171 | 0.0066 | 0.0049 | | 17810 | 1.62 | 59.77 | 0.0073 | 14060 |
-| GLIN | 0.0251 | 0.0733 | 0.1083 | 0.221 | 0.2704 | 0.3319 | 0.0105 | 0.0079 | | 20360 | 0.89 | 43.5 | 0.0133 | 8833 |
-| ILF | 0.0497 | 0.0631 | 0.1032 | 0.062 | 0.3082 | 0.2768 | 0.0141 | 0.0135 | | 1.18e+06 | 2.16 | 29.23 | 0.0215 | 1237337 |
-| SMIN | 0.0174 | 0.0573 | 0.0914 | 0.2128 | 0.2848 | 0.3447 | 0.0078 | 0.0074 | | 99980 | 5.61 | 69.6 | 0.0053 | 272774 |
+| Ticker | 1W | 1M | 3M | 6M | 1Y | YTD | 1W Volatility | 1M Volatility | Recom | Avg Volume | Rel Volume | Price | Change | Volume |
+| :----- | -----: | -----: | -----: | -----: | -----: | ------: | ------------: | ------------: | :---- | ---------: | ---------: | ----: | -----: | ------: |
+| CHB | 0.0301 | -0.015 | 0.1123 | 0.0086 | -0.132 | -0.1277 | 0.0105 | 0.0048 | | 1130 | 0.04 | 8.22 | 0.0123 | 21 |
+| INCO | 0.0193 | 0.0716 | 0.1092 | 0.1543 | 0.2706 | 0.3171 | 0.0066 | 0.0049 | | 17810 | 1.62 | 59.77 | 0.0073 | 14060 |
+| GLIN | 0.0251 | 0.0733 | 0.1083 | 0.221 | 0.2704 | 0.3319 | 0.0105 | 0.0079 | | 20360 | 0.89 | 43.5 | 0.0133 | 8833 |
+| ILF | 0.0497 | 0.0631 | 0.1032 | 0.062 | 0.3082 | 0.2768 | 0.0141 | 0.0135 | | 1.18e+06 | 2.16 | 29.23 | 0.0215 | 1237337 |
+| SMIN | 0.0174 | 0.0573 | 0.0914 | 0.2128 | 0.2848 | 0.3447 | 0.0078 | 0.0074 | | 99980 | 5.61 | 69.6 | 0.0053 | 272774 |
### Holdings
@@ -138,13 +138,13 @@ holdings = openbb.etf.holdings('DIA').reset_index()
holdings.head(5)
```
-| | Symbol | Name | % Of Etf | Shares |
-|---:|:---------|:--------------------------------|:-----------|---------:|
-| 0 | UNH | UnitedHealth Group Incorporated | 10.09% | 5985297 |
-| 1 | GS | The Goldman Sachs Group, Inc. | 7.51% | 5985297 |
-| 2 | HD | The Home Depot, Inc. | 6.03% | 5985297 |
-| 3 | AMGN | Amgen Inc. | 5.61% | 5985297 |
-| 4 | MCD | McDonald's Corporation | 5.35% | 5985297 |
+| | Symbol | Name | % Of Etf | Shares |
+| --: | :----- | :------------------------------ | :------- | ------: |
+| 0 | UNH | UnitedHealth Group Incorporated | 10.09% | 5985297 |
+| 1 | GS | The Goldman Sachs Group, Inc. | 7.51% | 5985297 |
+| 2 | HD | The Home Depot, Inc. | 6.03% | 5985297 |
+| 3 | AMGN | Amgen Inc. | 5.61% | 5985297 |
+| 4 | MCD | McDonald's Corporation | 5.35% | 5985297 |
### Disc
@@ -165,10 +165,10 @@ movers = openbb.etf.disc.mover()
movers.head(5)
```
-| | | Price | Chg | %Chg | Vol |
-|---:|:---------------------------------------------------------|--------:|-------:|-------:|:-------|
-| 0 | Direxion Daily Semiconductor Bear 3X Shares | 35.3101 | 3.3101 | 10.34 | 24.5M |
-| 1 | ProShares UltraShort Bloomberg Natural Gas | 18.09 | 1.19 | 7.04 | 4.4M |
-| 2 | MicroSectors FANG & Innovation -3x Inverse Leveraged ETN | 28.98 | 1.83 | 6.74 | 160.1K |
-| 3 | Direxion Daily Dow Jones Internet Bear 3X Shares | 32.14 | 1.91 | 6.32 | 554.2K |
-| 4 | Direxion Daily S&P 500 High Beta Bear 3X Shares | 6.4652 | 0.3752 | 6.16 | 1.2M |
+| | | Price | Chg | %Chg | Vol |
+| --: | :------------------------------------------------------- | ------: | -----: | ----: | :----- |
+| 0 | Direxion Daily Semiconductor Bear 3X Shares | 35.3101 | 3.3101 | 10.34 | 24.5M |
+| 1 | ProShares UltraShort Bloomberg Natural Gas | 18.09 | 1.19 | 7.04 | 4.4M |
+| 2 | MicroSectors FANG & Innovation -3x Inverse Leveraged ETN | 28.98 | 1.83 | 6.74 | 160.1K |
+| 3 | Direxion Daily Dow Jones Internet Bear 3X Shares | 32.14 | 1.91 | 6.32 | 554.2K |
+| 4 | Direxion Daily S&P 500 High Beta Bear 3X Shares | 6.4652 | 0.3752 | 6.16 | 1.2M |
diff --git a/website/content/sdk/faqs/bugs_support_feedback.md b/website/content/sdk/faqs/bugs_support_feedback.md
index f078e484eee6..70e508e47577 100644
--- a/website/content/sdk/faqs/bugs_support_feedback.md
+++ b/website/content/sdk/faqs/bugs_support_feedback.md
@@ -1,20 +1,21 @@
---
title: Bugs, Support, and Feedback
sidebar_position: 6
-description: This page provides information on how to deal with bugs, get support,
+description:
+ This page provides information on how to deal with bugs, get support,
and provide feedback for the OpenBB Terminal. It includes details on the release
process for patches, how to report a bug, and ways to request new features or provide
suggestions for improvements.
keywords:
-- bug reporting
-- support
-- feedback
-- patches
-- GitHub
-- open source platform
-- investors
-- feature request
-- machine learning
+ - bug reporting
+ - support
+ - feedback
+ - patches
+ - GitHub
+ - open source platform
+ - investors
+ - feature request
+ - machine learning
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -23,7 +24,8 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
When an error is encountered, it is always a good idea to check the open issues on [GitHub](https://github.com/OpenBB-finance/OpenBBTerminal/issues). There may be a workaround solution for the specific problem until a patch is released.
-How often are patches for bugs released?
+
+
-How often are patches for bugs released?
The installer versions are packaged approximately every two-weeks. Those working with a cloned GitHub version can checkout the Develop branch to get the latest fixes and releases before they are pushed to the main branch. @@ -33,19 +35,22 @@ git checkout developHow do I report a bug?
+
+
-How do I report a bug?
First, search the open issues for another report. If one already exists, attach any relevant information and screenshots as a comment. If one does not exist, start one with this [link](https://github.com/OpenBB-finance/OpenBBTerminal/issues/new?assignees=&labels=type%3Abug&template=bug_report.md&title=%5BBug%5D)How can I get help with OpenBB Terminal?
+
+
-How can I get help with OpenBB Terminal?
You can get help with OpenBB Terminal by joining our [Discord server](https://openbb.co/discord) or contact us in our support form [here](https://openbb.co/support).How can I give feedback about the OpenBB Terminal, or request specific functionality?
+
+
How can I give feedback about the OpenBB Terminal, or request specific functionality?
Being an open source platform that wishes to tailor to the needs of any type of investor, we highly encourage anyone to share with us their experience and/or how we can further improve the OpenBB Terminal. This can be anything from a very small bug, a new feature, or the implementation of a highly advanced Machine Learning model. diff --git a/website/content/sdk/faqs/data_sources.md b/website/content/sdk/faqs/data_sources.md index 124eb1b09f11..217917956362 100644 --- a/website/content/sdk/faqs/data_sources.md +++ b/website/content/sdk/faqs/data_sources.md @@ -1,19 +1,20 @@ --- title: Data and Sources sidebar_position: 4 -description: OpenBB is a data aggregator that provides access to data from various +description: + OpenBB is a data aggregator that provides access to data from various sources. It is important to understand how to load ticker symbols, end-of-day daily data, and handle certain limitations like accessing the Binance API. Feature request options are available for specific data source endpoints. keywords: -- data aggregators -- data providers -- ticker symbols -- end-of-day daily data -- Binance API -- feature request -- live feeds -- load function + - data aggregators + - data providers + - ticker symbols + - end-of-day daily data + - Binance API + - feature request + - live feeds + - load function --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -22,13 +23,15 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; Please note that OpenBB does not provide any data, it is an aggregator which provides users access to data from a variety of sources. OpenBB does not maintain or have any control over the raw data supplied. If there is a specific problem with the output from a data provider, please consider contacting them first. -Is there a list of all data providers?
+
+
-Is there a list of all data providers?
The complete list is found [here](/terminal/usage/data/api-keys)How do I load a ticker symbol from India?
+
+
-How do I load a ticker symbol from India?
Ticker symbols listed on exchanges outside of the US will have a suffix attached, for example, Rico Auto Industries Limited: @@ -40,7 +43,8 @@ The precise naming convention will differ by source, reference each source's ownData from today is missing.
+
+
-Data from today is missing.
By default, the load function requests end-of-day daily data and is not included until the EOD summary has been published. The current day's data is considered intraday and is loaded when the `interval` argument is present. @@ -50,13 +54,15 @@ df = openbb.stocks.load(SPY, interval = 60)Can I stream live prices and news feeds?
+
+
-Can I stream live prices and news feeds?
It is not currently possible to stream live feeds with the OpenBB SDK."Pair BTC/USDT not found in binance"
+
+
-"Pair BTC/USDT not found in binance"
US-based users are currently unable to access the Binance API. Please try loading the pair from a different source, for example: @@ -64,7 +70,8 @@ US-based users are currently unable to access the Binance API. Please try loadinHow can I request adding endpoints from a specific data source?
+
+
How can I request adding endpoints from a specific data source?
Please [request a feature](https://openbb.co/request-a-feature) by submitting a new request. diff --git a/website/content/sdk/faqs/developer_issues.md b/website/content/sdk/faqs/developer_issues.md index 6a7510edbac1..72bac3d858c8 100644 --- a/website/content/sdk/faqs/developer_issues.md +++ b/website/content/sdk/faqs/developer_issues.md @@ -1,29 +1,31 @@ --- title: Developer Issues sidebar_position: 7 -description: A comprehensive troubleshooting guide for developers regarding common +description: + A comprehensive troubleshooting guide for developers regarding common issues such as launching in debug mode, dealing with GitHub pull requests, git pull errors, missing 'wheel', non-existent .whl files, handling JSONDecodeError, correcting CRLF errors, running OpenBB via VS Code integrated terminal, and more. keywords: -- Developer Issues -- Debug mode -- GitHub pull requests -- git pull error -- wheel missing -- whl files -- JSONDecodeError -- CRLF error -- VS Code integrated terminal + - Developer Issues + - Debug mode + - GitHub pull requests + - git pull error + - wheel missing + - whl files + - JSONDecodeError + - CRLF error + - VS Code integrated terminal --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';How do I launch in debug mode?
+
+
-How do I launch in debug mode?
-The PyWry window can be run in debug mode for identifying specific issues. Use the code block below - with the `obb` Python environment active - to import the OpenBB SDK in debug mode. +The PyWry window can be run in debug mode for identifying specific issues. Use the code block below - with the `obb` Python environment active - to import the OpenBB SDK in debug mode. ```python import os @@ -39,7 +41,8 @@ The charts and tables will now include a developer tools button, located at theWhat branch on GitHub should pull requests be submitted to?
+
+
-What branch on GitHub should pull requests be submitted to?
Pull requests submitted to the Main branch will not be merged, please create branches from the `develop` branch. @@ -58,7 +61,8 @@ Branches must also follow the naming convention:Error: "git pull" fails because of a hot fix: cannot lock ref
+
+
-Error: "git pull" fails because of a hot fix: cannot lock ref
If the error message looks something like: @@ -75,7 +79,8 @@ git pullWhat does it mean if it says wheel is missing?
+
+
-What does it mean if it says wheel is missing?
If you receive any notifications regarding `wheel` missing, this could be due to this dependency missing. @@ -83,7 +88,8 @@ If you receive any notifications regarding `wheel` missing, this could be due toWhy do these .whl files not exist?
+
+
-Why do these .whl files not exist?
If you get errors about .whl files not existing (usually on Windows) you have to reinitialize the following folder. Just removing the 'artifacts' folder could also be enough: @@ -114,12 +120,14 @@ If you run into trouble with Poetry, and the advice above did not help, your bes - `conda env remove -n obb` - `conda clean -a` - Make a new environment and install dependencies again. + - Reboot your computer and try again - Submit a ticket on GitHubWhat does the JSONDecodeError mean during poetry install?
+
+
-What does the JSONDecodeError mean during poetry install?
Sometimes poetry can throw a `JSONDecodeError` on random packages while running `poetry install`. This can be observed on macOS 10.14+ running python 3.8+. This is because of the use of an experimental installer that can be switched off to avoid the mentioned error. Run the code below as advised [here](https://github.com/python-poetry/poetry/issues/4210) and it should fix the installation process. @@ -135,7 +143,8 @@ _Commands that may help you in case of an error:_How do I deal with errors regarding CRLF?
+
+
-How do I deal with errors regarding CRLF?
When trying to commit code changes, pylint will prevent you from doing so if your line break settings are set to CRLF (default for Windows). @@ -158,7 +167,8 @@ git reset --hardWhy can't I run OpenBB via the VS Code integrated terminal?
+
+
Why can't I run OpenBB via the VS Code integrated terminal?
This occurs when VS Code terminal python version/path is different from the terminal version. diff --git a/website/content/sdk/faqs/general_operation.md b/website/content/sdk/faqs/general_operation.md index 38d88c316a14..6cb87e785c60 100644 --- a/website/content/sdk/faqs/general_operation.md +++ b/website/content/sdk/faqs/general_operation.md @@ -1,27 +1,28 @@ --- title: General Operation sidebar_position: 3 -description: A page providing comprehensive tutorial and help information on enabling +description: + A page providing comprehensive tutorial and help information on enabling developer mode and resolving system-related issues on both Windows and MacOS for OpenBB's software. keywords: -- OpenBB software -- Developer mode -- System-related issues -- Windows -- MacOS -- Security policy -- Software troubleshooting -- Firewall & Network Protection -- OpenBB's tutorials -- Software installation -- Coding tools -- Terminal.app -- Visual Studio Code -- User manuals -- FAQs -- Instructions -- How-to guide + - OpenBB software + - Developer mode + - System-related issues + - Windows + - MacOS + - Security policy + - Software troubleshooting + - Firewall & Network Protection + - OpenBB's tutorials + - Software installation + - Coding tools + - Terminal.app + - Visual Studio Code + - User manuals + - FAQs + - Instructions + - How-to guide --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -41,13 +42,15 @@ From the Windows Security menu, click on the Firewall & Network Protection tab, - VcXsrv - Windows Terminal -An example code block does not work.
+
+
-An example code block does not work.
We try to keep example code up-to-date, but sometimes a specific example is left behind. Please submit a bug report and so that we are aware of the issue. Submit a bug report [here](https://openbb.co/support)Why does a specific menu or command not exist?
+
+
-Why does a specific menu or command not exist?
It could be that you are running an outdated version in which the menu or command is not yet available. Please check the [installation guide](https://my.openbb.co/app/sdk/installation) to download the most recent release. @@ -55,19 +58,22 @@ Do note that it is also possible that the menu or command has been deprecated. IWhat is the correct format for entering dates to function variables?
+
+
-What is the correct format for entering dates to function variables?
Dates should be entered as a string variable, inside of quotation marks, formatted as `%Y-%m-%d` - YYYY-MM-DD.Does the portfolio menu allow for dividends, interest, or other distributions?
+
+
-Does the portfolio menu allow for dividends, interest, or other distributions?
Currently, this is only possible by manually updating the portfolio file.Why does my Portfolio file fail to load?
+
+
-Why does my Portfolio file fail to load?
This can be the result of a formatting error, check the file in a simple text editor to observe any abnormalities in the formatting; or, it could be a bug - check the [GitHub issues page](https://github.com/OpenBB-finance/OpenBBTerminal/issues) for similar errors. @@ -87,7 +93,8 @@ See the guide [here](/sdk/data-available/portfolio/introduction) for more informHow do I change the chart styles?
+
+
-How do I change the chart styles?
Place style sheets in this folder: `OpenBBUserData/styles/user` @@ -107,7 +114,8 @@ theme = TerminalStyle("dark", "dark", "dark")Where are the included stock screener presets located?
+
+
Where are the included stock screener presets located?
The files are located in the folder with the code, under: diff --git a/website/content/sdk/faqs/import_errors.md b/website/content/sdk/faqs/import_errors.md index 9b1688b0c97a..e692b75d080b 100644 --- a/website/content/sdk/faqs/import_errors.md +++ b/website/content/sdk/faqs/import_errors.md @@ -1,23 +1,24 @@ --- title: Import Errors sidebar_position: 2 -description: This page provides solutions for common import errors when installing +description: + This page provides solutions for common import errors when installing the OpenBB SDK, including guidance on managing virtual environments, handling ModuleNotFoundError, dealing with SSL certificate authorization, and configuring proxy connections. keywords: -- Import Errors -- SciPy -- ModuleNotFoundError -- virtual environment -- poetry install -- conda activate -- Jupyter -- GitHub -- SSL certificates -- firewall -- pip-system-certs -- proxy connection -- .env file + - Import Errors + - SciPy + - ModuleNotFoundError + - virtual environment + - poetry install + - conda activate + - Jupyter + - GitHub + - SSL certificates + - firewall + - pip-system-certs + - proxy connection + - .env file --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -26,7 +27,8 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; When packages not included in the OpenBB installation are installed to the same environment as the SDK, it is possible that an incompatible build of a specific library (like SciPy) has overwritten the existing and creating a conflict. In this event, try creating a new environment containing only the OpenBB dependencies. -ModuleNotFoundError: No module named '______'
+
+
-ModuleNotFoundError: No module named '______'
Before troubleshooting please verify that the recommended installation instructions were followed. These errors often can occur when the virtual environment has not been activated, or the `poetry install` command was skipped. Activate the OpenBB virtual environment created during the installation process prior to launching or importing the SDK. @@ -61,13 +63,14 @@ poetry install -E allSSL certificates fail to authorize
+
+
-SSL certificates fail to authorize
```console SSL: CERTIFICATE_VERIFY_FAILED ``` -An error message, similar to above, is usually encountered while attempting to use the OpenBB Platform from behind a firewall. A workplace environment is typically the most common occurrence. Try connecting to the internet directly through a home network to test the connection. If using a work computer and/or network, we recommend speaking with the company's IT department prior to installing or running any software. +An error message, similar to above, is usually encountered while attempting to use the OpenBB Platform from behind a firewall. A workplace environment is typically the most common occurrence. Try connecting to the internet directly through a home network to test the connection. If using a work computer and/or network, we recommend speaking with the company's IT department prior to installing or running any software. A potential solution is to try: @@ -77,7 +80,8 @@ pip install pip-system-certsCannot connect due to proxy connection.
+
+
Cannot connect due to proxy connection.
Find the `.env` file (located at the root of the user account folder: (`~/.openbb_terminal/.env`), and add a line at the bottom of the file with: diff --git a/website/content/sdk/faqs/installation_updates.md b/website/content/sdk/faqs/installation_updates.md index 7482dbb28e54..f611c9b14d2d 100644 --- a/website/content/sdk/faqs/installation_updates.md +++ b/website/content/sdk/faqs/installation_updates.md @@ -1,29 +1,31 @@ --- title: Installation and Updates sidebar_position: 1 -description: This page provides detailed instructions for the installation and updating +description: + This page provides detailed instructions for the installation and updating processes for software, addressing frequently encountered installation issues. These instructions include resolving Microsoft Visual C++ 14.0 dependencies, benefits of using Miniconda for package management, methods to update installations, and solutions for other common installation errors. keywords: -- Installation -- Updates -- Microsoft Visual C++ 14.0 -- Miniconda -- pip install -- PyPi Nightly -- C++ Build Tools -- Homebrew -- bt wheel build failure -- ARM/Linux Raspberry Pi machines + - Installation + - Updates + - Microsoft Visual C++ 14.0 + - Miniconda + - pip install + - PyPi Nightly + - C++ Build Tools + - Homebrew + - bt wheel build failure + - ARM/Linux Raspberry Pi machines --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';"Microsoft Visual C++ 14.0 or greater is required"
+
+
-"Microsoft Visual C++ 14.0 or greater is required"
Download and install [C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/), restart the machine, then try again. @@ -33,13 +35,15 @@ Download and install [C++ Build Tools](https://visualstudio.microsoft.com/visualDo I have to use Miniconda?
+
+
-Do I have to use Miniconda?
There are certain dependencies which are sourced exclusively from the `conda-forge` directory. Other virtual environment managers, such a `venv`, may not solve the environment properly, resulting in failed package installations or incorrect builds. We highly recommend using Miniconda as the Python virtual environment manager for installing the OpenBB SDK.How do I update my installation to the latest version?
+
+
How do I update my installation to the latest version?
The code is constantly being updated with new features and bug fixes. The process for updating will vary by the installation type: @@ -66,13 +70,15 @@ pip install openbb-terminal-nightly[all] **Note**: This version may not be stable and should not be used in a production setting. -"Microsoft Visual C++ 14.0 or greater is required"
+
+
-"Microsoft Visual C++ 14.0 or greater is required"
Download and install [C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/), restart the machine, then try again.Error: failed building wheel for bt
+
+
-Error: failed building wheel for bt
There may be an additional message that is printed from this error, stating: "Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools". @@ -99,13 +105,15 @@ softwareupdate --install-rosettaMiniconda3 will not install on ARM/Linux Raspberry Pi machines.
+
+
-Miniconda3 will not install on ARM/Linux Raspberry Pi machines.
Refer to this issue on the Conda [GitHub](https://github.com/conda/conda/issues/10723) page.Error: Library not loaded: '/usr/local/opt/libomp/lib/libomp.dylib'
+
+
{'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...] | +| Type | Description | +| ---- | ------------------------------------------------------------------------------------------------------- | +| dict | All quote assets for given coin
\{'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...]\} | + --- diff --git a/website/content/sdk/reference/crypto/dd/trading_pairs.md b/website/content/sdk/reference/crypto/dd/trading_pairs.md index 5a0c65433fac..26a962d54051 100644 --- a/website/content/sdk/reference/crypto/dd/trading_pairs.md +++ b/website/content/sdk/reference/crypto/dd/trading_pairs.md @@ -1,21 +1,22 @@ --- title: trading_pairs -description: Information and code snippet on how to get all trading pairs on binance +description: + Information and code snippet on how to get all trading pairs on binance using openbb.crypto.dd.trading_pairs(). Details parameters and returns. keywords: -- trading pairs -- binance -- openbb.crypto.dd -- cryptocurrency -- due diligence -- openbb terminal -- trading parameters -- API -- ETHBTC symbol -- trading functionality + - trading pairs + - binance + - openbb.crypto.dd + - cryptocurrency + - due diligence + - openbb terminal + - trading parameters + - API + - ETHBTC symbol + - trading functionality --- -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; +import HeadTitle from "@site/src/components/General/HeadTitle.tsx";
[
{'symbol': 'ETHBTC', 'status': 'TRADING', 'baseAsset': 'ETH', 'baseAssetPrecision': 8,
'quoteAsset': 'BTC', 'quotePrecision': 8, 'quoteAssetPrecision': 8,
'baseCommissionPrecision': 8, 'quoteCommissionPrecision': 8,
'orderTypes': ['LIMIT', 'LIMIT_MAKER', 'MARKET', 'STOP_LOSS_LIMIT', 'TAKE_PROFIT_LIMIT'],
'icebergAllowed': True,
'ocoAllowed': True,
'quoteOrderQtyMarketAllowed': True,
'isSpotTradingAllowed': True,
'isMarginTradingAllowed': True,
'filters': [{'filterType': 'PRICE_FILTER', 'minPrice': '0.00000100',
'maxPrice': '922327.00000000', 'tickSize': '0.00000100'},
{'filterType': 'PERCENT_PRICE', 'multiplierUp': '5', 'multiplierDown': '0.2', 'avgPriceMins': 5},
{'filterType': 'LOT_SIZE', 'minQty': '0.00100000', 'maxQty': '100000.00000000', 'stepSize': '0.00100000'},
{'filterType': 'MIN_NOTIONAL', 'minNotional': '0.00010000', 'applyToMarket': True, 'avgPriceMins': 5},
{'filterType': 'ICEBERG_PARTS', 'limit': 10}, {'filterType': 'MARKET_LOT_SIZE', 'minQty': '0.00000000',
'maxQty': '930.49505347', 'stepSize': '0.00000000'}, {'filterType': 'MAX_NUM_ORDERS', 'maxNumOrders': 200},
{'filterType': 'MAX_NUM_ALGO_ORDERS', 'maxNumAlgoOrders': 5}], 'permissions': ['SPOT', 'MARGIN']},
...
] | +
+
+
---
diff --git a/website/content/sdk/reference/crypto/defi/anchor_data.md b/website/content/sdk/reference/crypto/defi/anchor_data.md
index 696658718cd8..46a7543bcd2b 100644
--- a/website/content/sdk/reference/crypto/defi/anchor_data.md
+++ b/website/content/sdk/reference/crypto/defi/anchor_data.md
@@ -1,21 +1,22 @@
---
title: anchor_data
-description: Improve your understanding of the Anchor protocol with the help of our
+description:
+ Improve your understanding of the Anchor protocol with the help of our
documentation providing detailed instructions on how to retrieve and plot earnings
data for a specific Terra address. Skim through the parameters, the types, the given
descriptions, and the functionality.
keywords:
-- docusaurus
-- anchor protocol
-- earnings data
-- terra address
-- parameters
-- returns
-- model
-- view chart
-- plot
-- transactions history
-- export
+ - docusaurus
+ - anchor protocol
+ - earnings data
+ - terra address
+ - parameters
+ - returns
+ - model
+ - view chart
+ - plot
+ - transactions history
+ - export
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -40,18 +41,18 @@ openbb.crypto.defi.anchor_data(address: str = "")
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| address | str | Terra address. Valid terra addresses start with 'terra' | | True |
-
+| Name | Type | Description | Default | Optional |
+| ------- | ---- | ------------------------------------------------------- | ------- | -------- |
+| address | str | Terra address. Valid terra addresses start with 'terra' | | True |
---
## Returns
-| Type | Description |
-| ---- | ----------- |
-| Tuple[pd.DataFrame, pd.DataFrame, str] | - pd.DataFrame: Earnings over time in UST
- pd.DataFrame: History of transactions
- str: Overall statistics | +| Type | Description | +| -------------------------------------- | ------------------------------------------------------------------------------------------------------------------- | +| Tuple[pd.DataFrame, pd.DataFrame, str] | - pd.DataFrame: Earnings over time in UST
- pd.DataFrame: History of transactions
- str: Overall statistics | + --- @@ -69,14 +70,13 @@ openbb.crypto.defi.anchor_data_chart(address: str = "", export: str = "", show_t ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | None | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | | True | -| show_transactions | bool | Flag to show history of transactions in Anchor protocol for address. Default False | False | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ----------------- | ------------------------ | ---------------------------------------------------------------------------------- | ------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | None | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | | True | +| show_transactions | bool | Flag to show history of transactions in Anchor protocol for address. Default False | False | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/crypto/defi/aterra.md b/website/content/sdk/reference/crypto/defi/aterra.md index 58de67c57cd5..45f7569193a0 100644 --- a/website/content/sdk/reference/crypto/defi/aterra.md +++ b/website/content/sdk/reference/crypto/defi/aterra.md @@ -1,18 +1,19 @@ --- title: aterra -description: This document provides information about how to fetch historical data +description: + This document provides information about how to fetch historical data for a specific Terra asset, plot the 30-day history of that asset and explains the usage of each function. Also includes source code links. keywords: -- Terra assets -- historical data -- address -- GET request -- Draw chart -- aterra -- meta data -- parameters -- returns + - Terra assets + - historical data + - address + - GET request + - Draw chart + - aterra + - meta data + - parameters + - returns --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -37,19 +38,19 @@ openbb.crypto.defi.aterra(asset: str = "ust", address: str = "terra1tmnqgvg567yp ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | ust | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | terra1tmnqgvg567ypvsvk6rwsga3srp7e3lg6u0elp8 | True | - +| Name | Type | Description | Default | Optional | +| ------- | ---- | ------------------------------------------------------- | -------------------------------------------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | ust | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | terra1tmnqgvg567ypvsvk6rwsga3srp7e3lg6u0elp8 | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------ | --------------- | | pd.DataFrame | historical data | + --- @@ -67,13 +68,12 @@ openbb.crypto.defi.aterra_chart(asset: str = "", address: str = "", export: str ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ------------- | ------------------------ | --------------------------------------------------------------- | ------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/crypto/disc/gainers.md b/website/content/sdk/reference/crypto/disc/gainers.md index abb1315bb1bf..1f9854d0027a 100644 --- a/website/content/sdk/reference/crypto/disc/gainers.md +++ b/website/content/sdk/reference/crypto/disc/gainers.md @@ -1,19 +1,20 @@ --- title: gainers -description: The page provides functionalities regarding Largest Gainers in cryptocurrency, +description: + The page provides functionalities regarding Largest Gainers in cryptocurrency, powered by CoinGecko's API. It contains Python models and charts to display the coins which gain the most in a given period. Additionally, it provides details on how to sort and display data, and export data to different file formats. keywords: -- gainers -- crypto -- coingecko -- model -- chart -- dataframe -- price -- volume -- export + - gainers + - crypto + - coingecko + - model + - chart + - dataframe + - price + - volume + - export --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -38,20 +39,20 @@ openbb.crypto.disc.gainers(interval: str = "1h", limit: int = 50, sortby: str = ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 50 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 50 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | --- ## Returns -| Type | Description | -| ---- | ----------- | -| pd.DataFrame | Top Gainers - coins which gain most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change_{interval}, Url | +| Type | Description | +| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------ | +| pd.DataFrame | Top Gainers - coins which gain most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change\_\{interval\}, Url | + --- @@ -69,13 +70,12 @@ openbb.crypto.disc.gainers_chart(interval: str = "1h", limit: int = 20, sortby: ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 20 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 20 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | --- diff --git a/website/content/sdk/reference/crypto/disc/losers.md b/website/content/sdk/reference/crypto/disc/losers.md index 184bef0c90d6..9d2faef29912 100644 --- a/website/content/sdk/reference/crypto/disc/losers.md +++ b/website/content/sdk/reference/crypto/disc/losers.md @@ -1,16 +1,17 @@ --- title: losers -description: The 'Losers' page on OpenBBTerminal provides functions that allow users +description: + The 'Losers' page on OpenBBTerminal provides functions that allow users to find out which cryptocurrencies suffered the largest losses during a given time period. Documentation includes information on parameters, return types, and source code. keywords: -- Cryptocurrency -- Losers -- Price changes -- CoinGecko -- API -- Crypto analysis + - Cryptocurrency + - Losers + - Price changes + - CoinGecko + - API + - Crypto analysis --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -35,20 +36,20 @@ openbb.crypto.disc.losers(interval: str = "1h", limit: int = 50, sortby: str = " ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 50 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 50 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | --- ## Returns -| Type | Description | -| ---- | ----------- | -| pd.DataFrame | Top Losers - coins which lost most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change_{interval}, Url | +| Type | Description | +| ------------ | ----------------------------------------------------------------------------------------------------------------------------------------- | +| pd.DataFrame | Top Losers - coins which lost most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change\_\{interval\}, Url | + --- @@ -66,13 +67,12 @@ openbb.crypto.disc.losers_chart(interval: str = "1h", limit: int = 20, export: s ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 20 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | Market Cap Rank | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 20 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | Market Cap Rank | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | --- diff --git a/website/content/sdk/reference/crypto/ov/cr.md b/website/content/sdk/reference/crypto/ov/cr.md index 33807cb76dd3..14c6a79708a7 100644 --- a/website/content/sdk/reference/crypto/ov/cr.md +++ b/website/content/sdk/reference/crypto/ov/cr.md @@ -1,16 +1,17 @@ --- title: cr -description: Documentation for two functions providing cryptocurrency interest rates +description: + Documentation for two functions providing cryptocurrency interest rates for both borrowing and supplying.You can use the functions to export data or generate charts. Several platforms are covered including BlockFi, Ledn, SwissBorg, and Youhodler. keywords: -- Cryptocurrency -- Crypto Interest Rates -- Crypto Borrowing -- Crypto Supplying -- Interest Rate Platforms -- Crypto Charts -- Crypto Data Export + - Cryptocurrency + - Crypto Interest Rates + - Crypto Borrowing + - Crypto Supplying + - Interest Rate Platforms + - Crypto Charts + - Crypto Data Export --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -23,7 +24,7 @@ import TabItem from '@theme/TabItem';
-Returns crypto {borrow,supply} interest rates for cryptocurrencies across several platforms
+Returns crypto \{borrow,supply\} interest rates for cryptocurrencies across several platforms
Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/cryptocurrency/overview/loanscan_model.py#L267)]
@@ -35,24 +36,24 @@ openbb.crypto.ov.cr(rate_type: str = "borrow")
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| rate_type | str | Interest rate type: {borrow, supply}. Default: supply | borrow | True |
-
+| Name | Type | Description | Default | Optional |
+| --------- | ---- | ------------------------------------------------------- | ------- | -------- |
+| rate_type | str | Interest rate type: \{borrow, supply\}. Default: supply | borrow | True |
---
## Returns
-| Type | Description |
-| ---- | ----------- |
+| Type | Description |
+| ------------ | ---------------------------------- |
| pd.DataFrame | crypto interest rates per platform |
+
---
-Displays crypto {borrow,supply} interest rates for cryptocurrencies across several platforms
+Displays crypto \{borrow, supply\} interest rates for cryptocurrencies across several platforms
Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/cryptocurrency/overview/loanscan_view.py#L24)]
@@ -64,14 +65,13 @@ openbb.crypto.ov.cr_chart(symbols: str, platforms: str, rate_type: str = "borrow
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| rate_type | str | Interest rate type: {borrow, supply}. Default: supply | borrow | True |
-| symbols | str | Crypto separated by commas. Default: BTC,ETH,USDT,USDC | None | False |
-| platforms | str | Platforms separated by commas. Default: BlockFi,Ledn,SwissBorg,Youhodler | None | False |
-| limit | int | Number of records to show | 10 | True |
-| export | str | Export dataframe data to csv,json,xlsx file | | True |
-
+| Name | Type | Description | Default | Optional |
+| --------- | ---- | ------------------------------------------------------------------------ | ------- | -------- |
+| rate_type | str | Interest rate type: \{borrow, supply\}. Default: supply | borrow | True |
+| symbols | str | Crypto separated by commas. Default: BTC,ETH,USDT,USDC | None | False |
+| platforms | str | Platforms separated by commas. Default: BlockFi,Ledn,SwissBorg,Youhodler | None | False |
+| limit | int | Number of records to show | 10 | True |
+| export | str | Export dataframe data to csv,json,xlsx file | | True |
---
diff --git a/website/content/sdk/reference/crypto/ov/crypto_hacks.md b/website/content/sdk/reference/crypto/ov/crypto_hacks.md
index 33fce677a15a..29e1ca20fc52 100644
--- a/website/content/sdk/reference/crypto/ov/crypto_hacks.md
+++ b/website/content/sdk/reference/crypto/ov/crypto_hacks.md
@@ -1,15 +1,16 @@
---
title: crypto_hacks
-description: Deep dive into major cryptocurrency-related hacks with OpenBB's crypto
+description:
+ Deep dive into major cryptocurrency-related hacks with OpenBB's crypto
hacks models. Evaluate, sort by key parameters and view intricate details about
each crypto hack.
keywords:
-- Crypto hacks
-- Crypto security
-- Cryptocurrency
-- OpenBB crypto
-- Crypto hack data
-- Crypto data sorting
+ - Crypto hacks
+ - Crypto security
+ - Cryptocurrency
+ - OpenBB crypto
+ - Crypto hack data
+ - Crypto data sorting
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -34,19 +35,19 @@ openbb.crypto.ov.crypto_hacks(sortby: str = "Platform", ascend: bool = False)
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| sortby | str | Key by which to sort data {Platform,Date,Amount [$],Audit,Slug,URL} | Platform | True |
-| ascend | bool | Flag to sort data ascending | False | True |
-
+| Name | Type | Description | Default | Optional |
+| ------ | ---- | --------------------------------------------------------------------- | -------- | -------- |
+| sortby | str | Key by which to sort data \{Platform,Date,Amount [$],Audit,Slug,URL\} | Platform | True |
+| ascend | bool | Flag to sort data ascending | False | True |
---
## Returns
-| Type | Description |
-| ---- | ----------- |
-| pd.DataFrame | Hacks with columns {Platform,Date,Amount [$],Audited,Slug,URL} |
+| Type | Description |
+| ------------ | ---------------------------------------------------------------- |
+| pd.DataFrame | Hacks with columns \{Platform,Date,Amount [$],Audited,Slug,URL\} |
+
---
@@ -64,14 +65,13 @@ openbb.crypto.ov.crypto_hacks_chart(limit: int = 15, sortby: str = "Platform", a
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| slug | str | Crypto hack slug to check (e.g., polynetwork-rekt) | polyntwork-rekt | True |
-| limit | int | Number of hacks to search | 15 | True |
-| sortby | str | Key by which to sort data {Platform,Date,Amount [$],Audit,Slug,URL} | Platform | True |
-| ascend | bool | Flag to sort data ascending | False | True |
-| export | str | Export dataframe data to csv,json,xlsx file | | True |
-
+| Name | Type | Description | Default | Optional |
+| ------ | ---- | --------------------------------------------------------------------- | --------------- | -------- |
+| slug | str | Crypto hack slug to check (e.g., polynetwork-rekt) | polyntwork-rekt | True |
+| limit | int | Number of hacks to search | 15 | True |
+| sortby | str | Key by which to sort data \{Platform,Date,Amount [$],Audit,Slug,URL\} | Platform | True |
+| ascend | bool | Flag to sort data ascending | False | True |
+| export | str | Export dataframe data to csv,json,xlsx file | | True |
---
diff --git a/website/content/sdk/reference/portfolio/po/blacklitterman.md b/website/content/sdk/reference/portfolio/po/blacklitterman.md
index 60aed8e9237e..e57755c630c4 100644
--- a/website/content/sdk/reference/portfolio/po/blacklitterman.md
+++ b/website/content/sdk/reference/portfolio/po/blacklitterman.md
@@ -1,18 +1,19 @@
---
title: blacklitterman
-description: The page describes the Python method for the Black Litterman model implemented
+description:
+ The page describes the Python method for the Black Litterman model implemented
in the OpenBB library for optimizing portfolio weights. This method provides an
advanced approach in risk management and return estimation by taking into account
various parameters like risk-free rate, risk aversion factor, and objectives like
maximizing Sharpe ratio or minimizing risk.
keywords:
-- Black Litterman model
-- Portfolio optimization
-- Portfolio weights
-- Risk management
-- Return estimates
-- Sharpe ratio
-- Equilibrium portfolio
+ - Black Litterman model
+ - Portfolio optimization
+ - Portfolio weights
+ - Risk management
+ - Return estimates
+ - Sharpe ratio
+ - Equilibrium portfolio
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -31,38 +32,38 @@ openbb.portfolio.po.blacklitterman(portfolio_engine: portfolio_optimization.po_e
## Parameters
-| Name | Type | Description | Default | Optional |
-| ---- | ---- | ----------- | ------- | -------- |
-| portfolio_engine | PoEngine | Portfolio optimization engine, by default None
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`__. | None | True |
-| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
-| value_short | float | Amount to allocate to portfolio in short positions, by default 0.0 | None | True |
-| benchmark | Dict | Dict of portfolio weights, by default None | None | True |
-| p_views | List | Matrix P of views that shows relationships among assets and returns, by default None | None | True |
-| q_views | List | Matrix Q of expected returns of views, by default None | None | True |
-| objective | str | Objective function of the optimization model, by default 'Sharpe'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| delta | float | Risk aversion factor of Black Litterman model, by default None | None | True | -| equilibrium | bool | If True excess returns are based on equilibrium market portfolio, if False
excess returns are calculated as historical returns minus risk free rate, by default True | None | True | -| optimize | bool | If True Black Litterman estimates are used as inputs of mean variance model,
if False returns equilibrium weights from Black Litterman model, by default True | None | True | - +| Name | Type | Description | Default | Optional | +| ---------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------- | -------- | +| portfolio_engine | PoEngine | Portfolio optimization engine, by default None
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see [`interpolate`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.interpolate.html). | None | True | +| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True | +| value_short | float | Amount to allocate to portfolio in short positions, by default 0.0 | None | True | +| benchmark | Dict | Dict of portfolio weights, by default None | None | True | +| p_views | List | Matrix P of views that shows relationships among assets and returns, by default None | None | True | +| q_views | List | Matrix Q of expected returns of views, by default None | None | True | +| objective | str | Objective function of the optimization model, by default 'Sharpe'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| delta | float | Risk aversion factor of Black Litterman model, by default None | None | True | +| equilibrium | bool | If True excess returns are based on equilibrium market portfolio, if False
excess returns are calculated as historical returns minus risk free rate, by default True | None | True | +| optimize | bool | If True Black Litterman estimates are used as inputs of mean variance model,
if False returns equilibrium weights from Black Litterman model, by default True | None | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------------------- | --------------------------------------------- | | Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + --- ## Examples @@ -81,6 +82,7 @@ openbb.portfolio.po.blacklitterman(symbols=["AAPL", "MSFT", "AMZN"]) 'Volatility': 0.33132073874339424, 'Sharpe ratio': 0.7736615325784322}) ``` + ```python from openbb_terminal.sdk import openbb p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") diff --git a/website/content/sdk/reference/portfolio/po/hcp.md b/website/content/sdk/reference/portfolio/po/hcp.md deleted file mode 100644 index 822ba7eca283..000000000000 --- a/website/content/sdk/reference/portfolio/po/hcp.md +++ /dev/null @@ -1,75 +0,0 @@ ---- -title: hcp -description: The page provides details on hierarchical clustering based portfolios - (HCP) in the OpenBBTerminal, a python tool for advanced investment strategies. It - describes parameters for portfolio optimization including risk measures, covariance - estimations, and clustering techniques. The return outcomes include portfolio weights - and stock returns. -keywords: -- portfolio optimization -- hierarchical clustering -- stock returns -- Hierarchical Risk Parity -- Nested Clustered Optimization -- covariance matrix -- risk measures -- stocks -- portfolio management ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
weekday. | None | True | -| log_returns | bool | If True calculate log returns, else arithmetic returns. Default value
is False | None | True | -| freq | str | The frequency used to calculate returns. Default value is 'D'. Possible
values are:
- 'D' for daily returns.
- 'W' for weekly returns.
- 'M' for monthly returns. | None | True | -| maxnan | float | Max percentage of nan values accepted per asset to be included in
returns. | None | True | -| threshold | float | Value used to replace outliers that are higher to threshold. | None | True | -| method | str | Method used to fill nan values. Default value is 'time'. For more information see `interpolate`__. | None | True |
-| model | str | The hierarchical cluster portfolio model used for optimize the
portfolio. The default is 'HRP'. Possible values are:
- 'HRP': Hierarchical Risk Parity.
- 'HERC': Hierarchical Equal Risk Contribution.
- 'NCO': Nested Clustered Optimization. | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}}. | None | True | -| covariance | str | The method used to estimate the covariance matrix:
The default is 'hist'. Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`__.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`__.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `c-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `c-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `c-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `c-MLforAM`. | None | True | -| objective | str | Objective function used by the NCO model.
The default is 'MinRisk'. Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'ERC': Equally risk contribution portfolio of the selected risk measure. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio. If model is 'NCO',
the risk measures available depends on the objective function.
The default is 'MV'. Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, must be in annual frequency.
Used for 'FLPM' and 'SLPM'. The default is 0. | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function.
The default is 1. | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses.
The default is 0.05. | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses. The default is 100. | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value.
The default is None. | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
The default is None. | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic.
The default is None. | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters. The default is 10. | None | True | -| bins_info | str | Number of bins used to calculate variation of information. The default
value is 'KN'. Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`__.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`__.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`__.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index. The default is 0.05. | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal. The default is True. | None | True | -| d_ewma | float | The smoothing factor of ewma methods.
The default is 0.94. | None | True | -| value | float | Amount of money to allocate. The default is 1. | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[Optional[dict], pd.DataFrame] | Dictionary of portfolio weights,
DataFrame of stock returns. | ---- diff --git a/website/content/sdk/reference/portfolio/po/hcp.mdx b/website/content/sdk/reference/portfolio/po/hcp.mdx new file mode 100644 index 000000000000..d2f372f85d43 --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/hcp.mdx @@ -0,0 +1,76 @@ +--- +title: hcp +description: + The page provides details on hierarchical clustering based portfolios + (HCP) in the OpenBBTerminal, a python tool for advanced investment strategies. It + describes parameters for portfolio optimization including risk measures, covariance + estimations, and clustering techniques. The return outcomes include portfolio weights + and stock returns. +keywords: + - portfolio optimization + - hierarchical clustering + - stock returns + - Hierarchical Risk Parity + - Nested Clustered Optimization + - covariance matrix + - risk measures + - stocks + - portfolio management +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
weekday. | None | True | +| log_returns | bool | If True calculate log returns, else arithmetic returns. Default value
is False | None | True | +| freq | str | The frequency used to calculate returns. Default value is 'D'. Possible
values are:
- 'D' for daily returns.
- 'W' for weekly returns.
- 'M' for monthly returns. | None | True | +| maxnan | float | Max percentage of nan values accepted per asset to be included in
returns. | None | True | +| threshold | float | Value used to replace outliers that are higher to threshold. | None | True | +| method | str | Method used to fill nan values. Default value is 'time'. For more information see `interpolate`\_\_. | None | True |
+| model | str | The hierarchical cluster portfolio model used for optimize the
portfolio. The default is 'HRP'. Possible values are:
- 'HRP': Hierarchical Risk Parity.
- 'HERC': Hierarchical Equal Risk Contribution.
- 'NCO': Nested Clustered Optimization. | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{pearson}*{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{spearman}*{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\rho^{distance}*{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$. | None | True | +| covariance | str | The method used to estimate the covariance matrix:
The default is 'hist'. Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`**.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`**.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `c-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `c-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `c-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `c-MLforAM`. | None | True | +| objective | str | Objective function used by the NCO model.
The default is 'MinRisk'. Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'ERC': Equally risk contribution portfolio of the selected risk measure. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio. If model is 'NCO',
the risk measures available depends on the objective function.
The default is 'MV'. Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, must be in annual frequency.
Used for 'FLPM' and 'SLPM'. The default is 0. | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function.
The default is 1. | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses.
The default is 0.05. | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses. The default is 100. | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value.
The default is None. | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
The default is None. | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic.
The default is None. | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters. The default is 10. | None | True | +| bins_info | str | Number of bins used to calculate variation of information. The default
value is 'KN'. Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`**.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`**.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`\_\_.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index. The default is 0.05. | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal. The default is True. | None | True | +| d_ewma | float | The smoothing factor of ewma methods.
The default is 0.94. | None | True | +| value | float | Amount of money to allocate. The default is 1. | None | True | + +--- + +## Returns + +| Type | Description | +| ----------------------------------- | ---------------------------------------------------------------- | +| Tuple[Optional[dict], pd.DataFrame] | Dictionary of portfolio weights,
DataFrame of stock returns. | + +--- diff --git a/website/content/sdk/reference/portfolio/po/herc.md b/website/content/sdk/reference/portfolio/po/herc.md deleted file mode 100644 index f854460ccd5e..000000000000 --- a/website/content/sdk/reference/portfolio/po/herc.md +++ /dev/null @@ -1,95 +0,0 @@ ---- -title: herc -description: The page provides detailed documentation for the Hierarchical Equal Risk - Contribution (HERC) method in the OpenBB Terminal's portfolio optimization module. - The method is used for the optimized allocation of resources in a portfolio to minimize - risk. The page includes a detailed explanation of input parameters, return types, - and code examples. -keywords: -- HERC Method -- Portfolio Optimization -- Risk Management -- Hierarchical Equal Risk Contribution -- Financial Modelling ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`__. | None | True |
-| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
-| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`__.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`__.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`__.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`__.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`__.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.herc(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.17521 - MSFT 0.19846 - AMZN 0.62633, - {'Return': 0.16899696275924703, - 'Volatility': 0.34337400112782096, - 'Sharpe ratio': 0.49216586638525933}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.herc(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/herc.mdx b/website/content/sdk/reference/portfolio/po/herc.mdx new file mode 100644 index 000000000000..a6d00ae5938c --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/herc.mdx @@ -0,0 +1,97 @@ +--- +title: herc +description: + The page provides detailed documentation for the Hierarchical Equal Risk + Contribution (HERC) method in the OpenBB Terminal's portfolio optimization module. + The method is used for the optimized allocation of resources in a portfolio to minimize + risk. The page includes a detailed explanation of input parameters, return types, + and code examples. +keywords: + - HERC Method + - Portfolio Optimization + - Risk Management + - Hierarchical Equal Risk Contribution + - Financial Modelling +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`\_\_. | None | True |
+| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
+| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`**.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`**.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`**.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`**.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`\_\_.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.herc(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.17521 + MSFT 0.19846 + AMZN 0.62633, + {'Return': 0.16899696275924703, + 'Volatility': 0.34337400112782096, + 'Sharpe ratio': 0.49216586638525933}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.herc(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/reference/portfolio/po/hrp.md b/website/content/sdk/reference/portfolio/po/hrp.md deleted file mode 100644 index 9930993ad2e7..000000000000 --- a/website/content/sdk/reference/portfolio/po/hrp.md +++ /dev/null @@ -1,96 +0,0 @@ ---- -title: hrp -description: This page provides information about the Hierarchical Risk Parity (HRP) - function in the openbb.portfolio.po module. This function allows for portfolio optimization - using HRP. Detailed parameter explanations, return values, and usage examples are - provided. -keywords: -- portfolio optimization -- Hierarchical Risk Parity -- openbb.portfolio.po -- risk management -- asset allocation -- portfolio management -- financial modeling ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`__. | None | True |
-| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
-| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`__.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`__.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`__.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`__.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`__.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.hrp(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.26729 - MSFT 0.30277 - AMZN 0.42994, - {'Return': 0.20463517260107467, - 'Volatility': 0.3313935169747041, - 'Sharpe ratio': 0.6174990219156727}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.hrp(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/hrp.mdx b/website/content/sdk/reference/portfolio/po/hrp.mdx new file mode 100644 index 000000000000..afb15d15f9e6 --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/hrp.mdx @@ -0,0 +1,98 @@ +--- +title: hrp +description: + This page provides information about the Hierarchical Risk Parity (HRP) + function in the openbb.portfolio.po module. This function allows for portfolio optimization + using HRP. Detailed parameter explanations, return values, and usage examples are + provided. +keywords: + - portfolio optimization + - Hierarchical Risk Parity + - openbb.portfolio.po + - risk management + - asset allocation + - portfolio management + - financial modeling +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`\_\_. | None | True |
+| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
+| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`**.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`**.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`**.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`**.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`\_\_.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.hrp(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.26729 + MSFT 0.30277 + AMZN 0.42994, + {'Return': 0.20463517260107467, + 'Volatility': 0.3313935169747041, + 'Sharpe ratio': 0.6174990219156727}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.hrp(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/reference/portfolio/po/nco.md b/website/content/sdk/reference/portfolio/po/nco.md deleted file mode 100644 index dbf6407ff61d..000000000000 --- a/website/content/sdk/reference/portfolio/po/nco.md +++ /dev/null @@ -1,97 +0,0 @@ ---- -title: nco -description: This page is about the Non-Convex Optimization (NCO) model used for portfolio - optimization. It includes a detailed explanation of the function parameters, return - values, and examples of usage using the OpenBB financial software. -keywords: -- Non-Convex Optimization -- portfolio optimization -- financial software -- financial modeling -- risk measures -- portfolio performance measures -- Sharpe ratio -- Value at Risk -- Maximum Drawdown ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`__. | None | True |
-| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
-| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`__.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`__.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`__.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`__.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`__.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.nco(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.25044 - MSFT 0.49509 - AMZN 0.25447, - {'Return': 0.2248615963428331, - 'Volatility': 0.32736590080425004, - 'Sharpe ratio': 0.6868815468880802}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.nco(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/nco.mdx b/website/content/sdk/reference/portfolio/po/nco.mdx new file mode 100644 index 000000000000..81f188f22d1b --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/nco.mdx @@ -0,0 +1,99 @@ +--- +title: nco +description: + This page is about the Non-Convex Optimization (NCO) model used for portfolio + optimization. It includes a detailed explanation of the function parameters, return + values, and examples of usage using the OpenBB financial software. +keywords: + - Non-Convex Optimization + - portfolio optimization + - financial software + - financial modeling + - risk measures + - portfolio performance measures + - Sharpe ratio + - Value at Risk + - Maximum Drawdown +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate`\_\_. | None | True |
+| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True |
+| objective | str | Objective function of the optimization model, by default 'MinRisk'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM`**.
- 'ewma2': use ewma with adjust=False. For more information see `EWM`**.
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{spearman}*{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\rho^{distance}*{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width`**.
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width`**.
- 'SC': Scotts' choice method. For more information see `scott_bin_width`\_\_.
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.nco(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.25044 + MSFT 0.49509 + AMZN 0.25447, + {'Return': 0.2248615963428331, + 'Volatility': 0.32736590080425004, + 'Sharpe ratio': 0.6868815468880802}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.nco(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/usage/api-keys.md b/website/content/sdk/usage/api-keys.md index 740c7d893e00..5a687a50decc 100644 --- a/website/content/sdk/usage/api-keys.md +++ b/website/content/sdk/usage/api-keys.md @@ -3,17 +3,16 @@ title: Setting API Keys sidebar_position: 2 description: This documentation page describes how you can set your own API keys from each data vendor on OpenBB to leverage their datasets. keywords: -- API keys -- datasets -- data vendors -- subscription + - API keys + - datasets + - data vendors + - subscription --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
Error: Library not loaded: '/usr/local/opt/libomp/lib/libomp.dylib'
This error is resolved by installing libomp from Homebrew: diff --git a/website/content/sdk/reference/alt/oss/ross.md b/website/content/sdk/reference/alt/oss/ross.md index 24270b138b18..fc7335e282c9 100644 --- a/website/content/sdk/reference/alt/oss/ross.md +++ b/website/content/sdk/reference/alt/oss/ross.md @@ -1,19 +1,20 @@ --- title: ross -description: This documentation page provides detailed information about the 'ross' +description: + This documentation page provides detailed information about the 'ross' functions of the OpenBB Terminal. These functions help to retrieve and visualize data about startups from the ROSS index. keywords: -- ross function -- data retrieval -- startups data -- ROSS index -- visualization -- dataframe -- chart -- data sort -- growth line chart -- data export + - ross function + - data retrieval + - startups data + - ROSS index + - visualization + - dataframe + - chart + - data sort + - growth line chart + - data export --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -44,9 +45,10 @@ This function does not take any parameters. ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------ | ---------------- | | pd.DataFrame | list of startups | + --- @@ -64,17 +66,16 @@ openbb.alt.oss.ross_chart(limit: int = 10, sortby: str = "Stars AGR [%]", ascend ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| limit | int | Number of startups to search | 10 | True | -| sortby | str | Key by which to sort data. Default: Stars AGR [%] | Stars AGR [%] | True | -| ascend | bool | Flag to sort data descending | False | True | -| show_chart | bool | Flag to show chart with startups | False | True | -| show_growth | bool | Flag to show growth line chart | True | True | -| chart_type | str | Chart type {stars,forks} | stars | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ------------- | ------------------------ | --------------------------------------------------------------- | ------------- | -------- | +| limit | int | Number of startups to search | 10 | True | +| sortby | str | Key by which to sort data. Default: Stars AGR [%] | Stars AGR [%] | True | +| ascend | bool | Flag to sort data descending | False | True | +| show_chart | bool | Flag to show chart with startups | False | True | +| show_growth | bool | Flag to show growth line chart | True | True | +| chart_type | str | Chart type \{stars,forks\} | stars | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/alt/oss/search.md b/website/content/sdk/reference/alt/oss/search.md index 8a2ff8ec7b3b..b746f799ae86 100644 --- a/website/content/sdk/reference/alt/oss/search.md +++ b/website/content/sdk/reference/alt/oss/search.md @@ -1,17 +1,18 @@ --- title: search -description: Discover OpenBB's robust functionality to sort repos by stars or forks, +description: + Discover OpenBB's robust functionality to sort repos by stars or forks, with an additional category filter feature. The result is straightforwardly produced as a DataFrame. Source code available. keywords: -- OpenBB finance -- Repo sorter -- Star ranking -- Fork ranking -- Category filter -- Python API -- Financial data extraction -- Dataframe results + - OpenBB finance + - Repo sorter + - Star ranking + - Fork ranking + - Category filter + - Python API + - Financial data extraction + - Dataframe results --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -30,18 +31,18 @@ openbb.alt.oss.search(sortby: str = "stars", page: int = 1, categories: str = "" ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| sortby | str | Sort repos by {stars, forks} | stars | True | -| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | -| page | int | Page number to get repos | 1 | True | - +| Name | Type | Description | Default | Optional | +| ---------- | ---- | ---------------------------------------------------------------------------------------------------------- | ------- | -------- | +| sortby | str | Sort repos by \{stars, forks\} | stars | True | +| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | +| page | int | Page number to get repos | 1 | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------ | -------------------- | | pd.DataFrame | Dataframe with repos | + --- diff --git a/website/content/sdk/reference/alt/oss/top.md b/website/content/sdk/reference/alt/oss/top.md index e77cdcff042d..592a019e95d5 100644 --- a/website/content/sdk/reference/alt/oss/top.md +++ b/website/content/sdk/reference/alt/oss/top.md @@ -1,23 +1,23 @@ --- title: top -description: 'This content describes two features: ''Model'' and ''Chart''. ''Model'' - gets repositories sorted by stars or forks with possible category filtering. ''Chart'' - plots a repo summary. Both procedures involve parameters like ''sortby'', ''categories'', - ''limit'', ''export'', and ''external_axes''.' +description: "This content describes two features: 'Model' and 'Chart'. 'Model' + gets repositories sorted by stars or forks with possible category filtering. 'Chart' + plots a repo summary. Both procedures involve parameters like 'sortby', 'categories', + 'limit', 'export', and 'external_axes'." keywords: -- Documentation -- Model -- Chart -- Repositories -- Stars -- Forks -- Filtering -- Parameters -- Sortby -- Categories -- Limit -- Export -- External_axes + - Documentation + - Model + - Chart + - Repositories + - Stars + - Forks + - Filtering + - Parameters + - Sortby + - Categories + - Limit + - Export + - External_axes --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -42,20 +42,20 @@ openbb.alt.oss.top(sortby: str, limit: int = 50, categories: str = "") ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| sortby | str | Sort repos by {stars, forks} | None | False | -| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | -| limit | int | Number of repos to search for | 50 | True | - +| Name | Type | Description | Default | Optional | +| ---------- | ---- | ---------------------------------------------------------------------------------------------------------- | ------- | -------- | +| sortby | str | Sort repos by \{stars, forks\} | None | False | +| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | +| limit | int | Number of repos to search for | 50 | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------ | -------------------- | | pd.DataFrame | Dataframe with repos | + --- @@ -73,14 +73,13 @@ openbb.alt.oss.top_chart(sortby: str, categories: str = "", limit: int = 10, exp ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| sortby | str | Sort repos by {stars, forks} | None | False | -| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | -| limit | int | Number of repos to look at | 10 | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ------------- | ------------------------ | ---------------------------------------------------------------------------------------------------------- | ------- | -------- | +| sortby | str | Sort repos by \{stars, forks\} | None | False | +| categories | str | Check for repo categories. If more than one separate with a comma: e.g., finance,investment. Default: None | | True | +| limit | int | Number of repos to look at | 10 | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/crypto/dd/binance_available_quotes_for_each_coin.md b/website/content/sdk/reference/crypto/dd/binance_available_quotes_for_each_coin.md index 05398caf76fd..caeacc8d3643 100644 --- a/website/content/sdk/reference/crypto/dd/binance_available_quotes_for_each_coin.md +++ b/website/content/sdk/reference/crypto/dd/binance_available_quotes_for_each_coin.md @@ -1,17 +1,18 @@ --- title: binance_available_quotes_for_each_coin -description: This page provides a detailed guide to the helper methods in OpenBB Terminal +description: + This page provides a detailed guide to the helper methods in OpenBB Terminal that, for every coin available on Binance, add all quote assets. It includes how to use the function and what it will return. keywords: -- Binance -- cryptocurrency -- quote assets -- helper methods -- coin -- function -- parameters -- returns + - Binance + - cryptocurrency + - quote assets + - helper methods + - coin + - function + - parameters + - returns --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -36,7 +37,8 @@ This function does not take any parameters. ## Returns -| Type | Description | -| ---- | ----------- | -| dict | All quote assets for given coin{'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...] | +| Type | Description | +| ---- | ------------------------------------------------------------------------------------------------------- | +| dict | All quote assets for given coin
\{'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...]\} | + --- diff --git a/website/content/sdk/reference/crypto/dd/trading_pairs.md b/website/content/sdk/reference/crypto/dd/trading_pairs.md index 5a0c65433fac..26a962d54051 100644 --- a/website/content/sdk/reference/crypto/dd/trading_pairs.md +++ b/website/content/sdk/reference/crypto/dd/trading_pairs.md @@ -1,21 +1,22 @@ --- title: trading_pairs -description: Information and code snippet on how to get all trading pairs on binance +description: + Information and code snippet on how to get all trading pairs on binance using openbb.crypto.dd.trading_pairs(). Details parameters and returns. keywords: -- trading pairs -- binance -- openbb.crypto.dd -- cryptocurrency -- due diligence -- openbb terminal -- trading parameters -- API -- ETHBTC symbol -- trading functionality + - trading pairs + - binance + - openbb.crypto.dd + - cryptocurrency + - due diligence + - openbb terminal + - trading parameters + - API + - ETHBTC symbol + - trading functionality --- -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; +import HeadTitle from "@site/src/components/General/HeadTitle.tsx";
[
{'symbol': 'ETHBTC', 'status': 'TRADING', 'baseAsset': 'ETH', 'baseAssetPrecision': 8,
'quoteAsset': 'BTC', 'quotePrecision': 8, 'quoteAssetPrecision': 8,
'baseCommissionPrecision': 8, 'quoteCommissionPrecision': 8,
'orderTypes': ['LIMIT', 'LIMIT_MAKER', 'MARKET', 'STOP_LOSS_LIMIT', 'TAKE_PROFIT_LIMIT'],
'icebergAllowed': True,
'ocoAllowed': True,
'quoteOrderQtyMarketAllowed': True,
'isSpotTradingAllowed': True,
'isMarginTradingAllowed': True,
'filters': [{'filterType': 'PRICE_FILTER', 'minPrice': '0.00000100',
'maxPrice': '922327.00000000', 'tickSize': '0.00000100'},
{'filterType': 'PERCENT_PRICE', 'multiplierUp': '5', 'multiplierDown': '0.2', 'avgPriceMins': 5},
{'filterType': 'LOT_SIZE', 'minQty': '0.00100000', 'maxQty': '100000.00000000', 'stepSize': '0.00100000'},
{'filterType': 'MIN_NOTIONAL', 'minNotional': '0.00010000', 'applyToMarket': True, 'avgPriceMins': 5},
{'filterType': 'ICEBERG_PARTS', 'limit': 10}, {'filterType': 'MARKET_LOT_SIZE', 'minQty': '0.00000000',
'maxQty': '930.49505347', 'stepSize': '0.00000000'}, {'filterType': 'MAX_NUM_ORDERS', 'maxNumOrders': 200},
{'filterType': 'MAX_NUM_ALGO_ORDERS', 'maxNumAlgoOrders': 5}], 'permissions': ['SPOT', 'MARGIN']},
...
] | +
| Type | +Description | +
| List[dict] | ++list of dictionaries in format: + +```python +[ + { + 'symbol': 'ETHBTC', 'status': 'TRADING', 'baseAsset': 'ETH', 'baseAssetPrecision': 8, + 'quoteAsset': 'BTC', 'quotePrecision': 8, 'quoteAssetPrecision': 8, + 'baseCommissionPrecision': 8, 'quoteCommissionPrecision': 8, + 'orderTypes': ['LIMIT', 'LIMIT_MAKER', 'MARKET', 'STOP_LOSS_LIMIT', 'TAKE_PROFIT_LIMIT'], + 'icebergAllowed': True, + 'ocoAllowed': True, + 'quoteOrderQtyMarketAllowed': True, + 'isSpotTradingAllowed': True, + 'isMarginTradingAllowed': True, + 'filters': [ + {'filterType': 'PRICE_FILTER', 'minPrice': '0.00000100', 'maxPrice': '922327.00000000', 'tickSize': '0.00000100'}, + {'filterType': 'PERCENT_PRICE', 'multiplierUp': '5', 'multiplierDown': '0.2', 'avgPriceMins': 5}, + {'filterType': 'LOT_SIZE', 'minQty': '0.00100000', 'maxQty': '100000.00000000', 'stepSize': '0.00100000'}, + {'filterType': 'MIN_NOTIONAL', 'minNotional': '0.00010000', 'applyToMarket': True, 'avgPriceMins': 5}, + {'filterType': 'ICEBERG_PARTS', 'limit': 10}, + {'filterType': 'MARKET_LOT_SIZE', 'minQty': '0.00000000', 'maxQty': '930.49505347', 'stepSize': '0.00000000'}, + {'filterType': 'MAX_NUM_ORDERS', 'maxNumOrders': 200}, + {'filterType': 'MAX_NUM_ALGO_ORDERS', 'maxNumAlgoOrders': 5} + ], + 'permissions': ['SPOT', 'MARGIN'] + } +] + +``` + + | +
- pd.DataFrame: History of transactions
- str: Overall statistics | +| Type | Description | +| -------------------------------------- | ------------------------------------------------------------------------------------------------------------------- | +| Tuple[pd.DataFrame, pd.DataFrame, str] | - pd.DataFrame: Earnings over time in UST
- pd.DataFrame: History of transactions
- str: Overall statistics | + --- @@ -69,14 +70,13 @@ openbb.crypto.defi.anchor_data_chart(address: str = "", export: str = "", show_t ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | None | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | | True | -| show_transactions | bool | Flag to show history of transactions in Anchor protocol for address. Default False | False | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ----------------- | ------------------------ | ---------------------------------------------------------------------------------- | ------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | None | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | | True | +| show_transactions | bool | Flag to show history of transactions in Anchor protocol for address. Default False | False | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/crypto/defi/aterra.md b/website/content/sdk/reference/crypto/defi/aterra.md index 58de67c57cd5..45f7569193a0 100644 --- a/website/content/sdk/reference/crypto/defi/aterra.md +++ b/website/content/sdk/reference/crypto/defi/aterra.md @@ -1,18 +1,19 @@ --- title: aterra -description: This document provides information about how to fetch historical data +description: + This document provides information about how to fetch historical data for a specific Terra asset, plot the 30-day history of that asset and explains the usage of each function. Also includes source code links. keywords: -- Terra assets -- historical data -- address -- GET request -- Draw chart -- aterra -- meta data -- parameters -- returns + - Terra assets + - historical data + - address + - GET request + - Draw chart + - aterra + - meta data + - parameters + - returns --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -37,19 +38,19 @@ openbb.crypto.defi.aterra(asset: str = "ust", address: str = "terra1tmnqgvg567yp ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | ust | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | terra1tmnqgvg567ypvsvk6rwsga3srp7e3lg6u0elp8 | True | - +| Name | Type | Description | Default | Optional | +| ------- | ---- | ------------------------------------------------------- | -------------------------------------------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | ust | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | terra1tmnqgvg567ypvsvk6rwsga3srp7e3lg6u0elp8 | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------ | --------------- | | pd.DataFrame | historical data | + --- @@ -67,13 +68,12 @@ openbb.crypto.defi.aterra_chart(asset: str = "", address: str = "", export: str ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| asset | str | Terra asset {ust,luna,sdt} | | True | -| address | str | Terra address. Valid terra addresses start with 'terra' | | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | -| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | - +| Name | Type | Description | Default | Optional | +| ------------- | ------------------------ | --------------------------------------------------------------- | ------- | -------- | +| asset | str | Terra asset \{ust,luna,sdt\} | | True | +| address | str | Terra address. Valid terra addresses start with 'terra' | | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | +| external_axes | Optional[List[plt.Axes]] | External axes (1 axis is expected in the list), by default None | None | True | --- diff --git a/website/content/sdk/reference/crypto/disc/gainers.md b/website/content/sdk/reference/crypto/disc/gainers.md index abb1315bb1bf..1f9854d0027a 100644 --- a/website/content/sdk/reference/crypto/disc/gainers.md +++ b/website/content/sdk/reference/crypto/disc/gainers.md @@ -1,19 +1,20 @@ --- title: gainers -description: The page provides functionalities regarding Largest Gainers in cryptocurrency, +description: + The page provides functionalities regarding Largest Gainers in cryptocurrency, powered by CoinGecko's API. It contains Python models and charts to display the coins which gain the most in a given period. Additionally, it provides details on how to sort and display data, and export data to different file formats. keywords: -- gainers -- crypto -- coingecko -- model -- chart -- dataframe -- price -- volume -- export + - gainers + - crypto + - coingecko + - model + - chart + - dataframe + - price + - volume + - export --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -38,20 +39,20 @@ openbb.crypto.disc.gainers(interval: str = "1h", limit: int = 50, sortby: str = ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 50 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 50 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | --- ## Returns -| Type | Description | -| ---- | ----------- | -| pd.DataFrame | Top Gainers - coins which gain most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change_{interval}, Url | +| Type | Description | +| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------ | +| pd.DataFrame | Top Gainers - coins which gain most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change\_\{interval\}, Url | + --- @@ -69,13 +70,12 @@ openbb.crypto.disc.gainers_chart(interval: str = "1h", limit: int = 20, sortby: ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 20 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 20 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | --- diff --git a/website/content/sdk/reference/crypto/disc/losers.md b/website/content/sdk/reference/crypto/disc/losers.md index 184bef0c90d6..9d2faef29912 100644 --- a/website/content/sdk/reference/crypto/disc/losers.md +++ b/website/content/sdk/reference/crypto/disc/losers.md @@ -1,16 +1,17 @@ --- title: losers -description: The 'Losers' page on OpenBBTerminal provides functions that allow users +description: + The 'Losers' page on OpenBBTerminal provides functions that allow users to find out which cryptocurrencies suffered the largest losses during a given time period. Documentation includes information on parameters, return types, and source code. keywords: -- Cryptocurrency -- Losers -- Price changes -- CoinGecko -- API -- Crypto analysis + - Cryptocurrency + - Losers + - Price changes + - CoinGecko + - API + - Crypto analysis --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -35,20 +36,20 @@ openbb.crypto.disc.losers(interval: str = "1h", limit: int = 50, sortby: str = " ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 50 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time interval by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 50 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | market_cap_rank | True | --- ## Returns -| Type | Description | -| ---- | ----------- | -| pd.DataFrame | Top Losers - coins which lost most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change_{interval}, Url | +| Type | Description | +| ------------ | ----------------------------------------------------------------------------------------------------------------------------------------- | +| pd.DataFrame | Top Losers - coins which lost most in price in given period of time.
Columns: Symbol, Name, Volume, Price, %Change\_\{interval\}, Url | + --- @@ -66,13 +67,12 @@ openbb.crypto.disc.losers_chart(interval: str = "1h", limit: int = 20, export: s ## Parameters -| Name | Type | Description | Default | Optional | -| ---- | ---- | ----------- | ------- | -------- | -| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | -| limit | int | Number of records to display | 20 | True | -| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | Market Cap Rank | True | -| export | str | Export dataframe data to csv,json,xlsx file | | True | - +| Name | Type | Description | Default | Optional | +| -------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------- | -------- | +| interval | str | Time period by which data is displayed. One from [1h, 24h, 7d, 14d, 30d, 60d, 1y] | 1h | True | +| limit | int | Number of records to display | 20 | True | +| sortby | str | Key to sort data. The table can be sorted by every of its columns. Refer to
API documentation (see /coins/markets in https://www.coingecko.com/en/api/documentation) | Market Cap Rank | True | +| export | str | Export dataframe data to csv,json,xlsx file | | True | --- diff --git a/website/content/sdk/reference/crypto/ov/cr.md b/website/content/sdk/reference/crypto/ov/cr.md index 33807cb76dd3..14c6a79708a7 100644 --- a/website/content/sdk/reference/crypto/ov/cr.md +++ b/website/content/sdk/reference/crypto/ov/cr.md @@ -1,16 +1,17 @@ --- title: cr -description: Documentation for two functions providing cryptocurrency interest rates +description: + Documentation for two functions providing cryptocurrency interest rates for both borrowing and supplying.You can use the functions to export data or generate charts. Several platforms are covered including BlockFi, Ledn, SwissBorg, and Youhodler. keywords: -- Cryptocurrency -- Crypto Interest Rates -- Crypto Borrowing -- Crypto Supplying -- Interest Rate Platforms -- Crypto Charts -- Crypto Data Export + - Cryptocurrency + - Crypto Interest Rates + - Crypto Borrowing + - Crypto Supplying + - Interest Rate Platforms + - Crypto Charts + - Crypto Data Export --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -23,7 +24,7 @@ import TabItem from '@theme/TabItem';
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| delta | float | Risk aversion factor of Black Litterman model, by default None | None | True | -| equilibrium | bool | If True excess returns are based on equilibrium market portfolio, if False
excess returns are calculated as historical returns minus risk free rate, by default True | None | True | -| optimize | bool | If True Black Litterman estimates are used as inputs of mean variance model,
if False returns equilibrium weights from Black Litterman model, by default True | None | True | - +| Name | Type | Description | Default | Optional | +| ---------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------- | -------- | +| portfolio_engine | PoEngine | Portfolio optimization engine, by default None
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see [`interpolate`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.interpolate.html). | None | True | +| value | float | Amount to allocate to portfolio in long positions, by default 1.0 | None | True | +| value_short | float | Amount to allocate to portfolio in short positions, by default 0.0 | None | True | +| benchmark | Dict | Dict of portfolio weights, by default None | None | True | +| p_views | List | Matrix P of views that shows relationships among assets and returns, by default None | None | True | +| q_views | List | Matrix Q of expected returns of views, by default None | None | True | +| objective | str | Objective function of the optimization model, by default 'Sharpe'
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| delta | float | Risk aversion factor of Black Litterman model, by default None | None | True | +| equilibrium | bool | If True excess returns are based on equilibrium market portfolio, if False
excess returns are calculated as historical returns minus risk free rate, by default True | None | True | +| optimize | bool | If True Black Litterman estimates are used as inputs of mean variance model,
if False returns equilibrium weights from Black Litterman model, by default True | None | True | --- ## Returns -| Type | Description | -| ---- | ----------- | +| Type | Description | +| ------------------------- | --------------------------------------------- | | Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + --- ## Examples @@ -81,6 +82,7 @@ openbb.portfolio.po.blacklitterman(symbols=["AAPL", "MSFT", "AMZN"]) 'Volatility': 0.33132073874339424, 'Sharpe ratio': 0.7736615325784322}) ``` + ```python from openbb_terminal.sdk import openbb p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") diff --git a/website/content/sdk/reference/portfolio/po/hcp.md b/website/content/sdk/reference/portfolio/po/hcp.md deleted file mode 100644 index 822ba7eca283..000000000000 --- a/website/content/sdk/reference/portfolio/po/hcp.md +++ /dev/null @@ -1,75 +0,0 @@ ---- -title: hcp -description: The page provides details on hierarchical clustering based portfolios - (HCP) in the OpenBBTerminal, a python tool for advanced investment strategies. It - describes parameters for portfolio optimization including risk measures, covariance - estimations, and clustering techniques. The return outcomes include portfolio weights - and stock returns. -keywords: -- portfolio optimization -- hierarchical clustering -- stock returns -- Hierarchical Risk Parity -- Nested Clustered Optimization -- covariance matrix -- risk measures -- stocks -- portfolio management ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
weekday. | None | True | -| log_returns | bool | If True calculate log returns, else arithmetic returns. Default value
is False | None | True | -| freq | str | The frequency used to calculate returns. Default value is 'D'. Possible
values are:
- 'D' for daily returns.
- 'W' for weekly returns.
- 'M' for monthly returns. | None | True | -| maxnan | float | Max percentage of nan values accepted per asset to be included in
returns. | None | True | -| threshold | float | Value used to replace outliers that are higher to threshold. | None | True | -| method | str | Method used to fill nan values. Default value is 'time'. For more information see `interpolate
portfolio. The default is 'HRP'. Possible values are:
- 'HRP': Hierarchical Risk Parity.
- 'HERC': Hierarchical Equal Risk Contribution.
- 'NCO': Nested Clustered Optimization. | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}}. | None | True | -| covariance | str | The method used to estimate the covariance matrix:
The default is 'hist'. Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `c-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `c-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `c-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `c-MLforAM`. | None | True | -| objective | str | Objective function used by the NCO model.
The default is 'MinRisk'. Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'ERC': Equally risk contribution portfolio of the selected risk measure. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio. If model is 'NCO',
the risk measures available depends on the objective function.
The default is 'MV'. Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, must be in annual frequency.
Used for 'FLPM' and 'SLPM'. The default is 0. | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function.
The default is 1. | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses.
The default is 0.05. | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses. The default is 100. | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value.
The default is None. | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
The default is None. | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic.
The default is None. | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters. The default is 10. | None | True | -| bins_info | str | Number of bins used to calculate variation of information. The default
value is 'KN'. Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index. The default is 0.05. | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal. The default is True. | None | True | -| d_ewma | float | The smoothing factor of ewma methods.
The default is 0.94. | None | True | -| value | float | Amount of money to allocate. The default is 1. | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[Optional[dict], pd.DataFrame] | Dictionary of portfolio weights,
DataFrame of stock returns. | ---- diff --git a/website/content/sdk/reference/portfolio/po/hcp.mdx b/website/content/sdk/reference/portfolio/po/hcp.mdx new file mode 100644 index 000000000000..d2f372f85d43 --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/hcp.mdx @@ -0,0 +1,76 @@ +--- +title: hcp +description: + The page provides details on hierarchical clustering based portfolios + (HCP) in the OpenBBTerminal, a python tool for advanced investment strategies. It + describes parameters for portfolio optimization including risk measures, covariance + estimations, and clustering techniques. The return outcomes include portfolio weights + and stock returns. +keywords: + - portfolio optimization + - hierarchical clustering + - stock returns + - Hierarchical Risk Parity + - Nested Clustered Optimization + - covariance matrix + - risk measures + - stocks + - portfolio management +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
weekday. | None | True | +| log_returns | bool | If True calculate log returns, else arithmetic returns. Default value
is False | None | True | +| freq | str | The frequency used to calculate returns. Default value is 'D'. Possible
values are:
- 'D' for daily returns.
- 'W' for weekly returns.
- 'M' for monthly returns. | None | True | +| maxnan | float | Max percentage of nan values accepted per asset to be included in
returns. | None | True | +| threshold | float | Value used to replace outliers that are higher to threshold. | None | True | +| method | str | Method used to fill nan values. Default value is 'time'. For more information see `interpolate
portfolio. The default is 'HRP'. Possible values are:
- 'HRP': Hierarchical Risk Parity.
- 'HERC': Hierarchical Equal Risk Contribution.
- 'NCO': Nested Clustered Optimization. | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{pearson}*{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{spearman}*{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\rho^{distance}*{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$. | None | True | +| covariance | str | The method used to estimate the covariance matrix:
The default is 'hist'. Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `c-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `c-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `c-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `c-MLforAM`. | None | True | +| objective | str | Objective function used by the NCO model.
The default is 'MinRisk'. Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'ERC': Equally risk contribution portfolio of the selected risk measure. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio. If model is 'NCO',
the risk measures available depends on the objective function.
The default is 'MV'. Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, must be in annual frequency.
Used for 'FLPM' and 'SLPM'. The default is 0. | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function.
The default is 1. | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses.
The default is 0.05. | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses. The default is 100. | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value.
The default is None. | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value.
The default is None. | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic.
The default is None. | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters. The default is 10. | None | True | +| bins_info | str | Number of bins used to calculate variation of information. The default
value is 'KN'. Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index. The default is 0.05. | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal. The default is True. | None | True | +| d_ewma | float | The smoothing factor of ewma methods.
The default is 0.94. | None | True | +| value | float | Amount of money to allocate. The default is 1. | None | True | + +--- + +## Returns + +| Type | Description | +| ----------------------------------- | ---------------------------------------------------------------- | +| Tuple[Optional[dict], pd.DataFrame] | Dictionary of portfolio weights,
DataFrame of stock returns. | + +--- diff --git a/website/content/sdk/reference/portfolio/po/herc.md b/website/content/sdk/reference/portfolio/po/herc.md deleted file mode 100644 index f854460ccd5e..000000000000 --- a/website/content/sdk/reference/portfolio/po/herc.md +++ /dev/null @@ -1,95 +0,0 @@ ---- -title: herc -description: The page provides detailed documentation for the Hierarchical Equal Risk - Contribution (HERC) method in the OpenBB Terminal's portfolio optimization module. - The method is used for the optimized allocation of resources in a portfolio to minimize - risk. The page includes a detailed explanation of input parameters, return types, - and code examples. -keywords: -- HERC Method -- Portfolio Optimization -- Risk Management -- Hierarchical Equal Risk Contribution -- Financial Modelling ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.herc(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.17521 - MSFT 0.19846 - AMZN 0.62633, - {'Return': 0.16899696275924703, - 'Volatility': 0.34337400112782096, - 'Sharpe ratio': 0.49216586638525933}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.herc(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/herc.mdx b/website/content/sdk/reference/portfolio/po/herc.mdx new file mode 100644 index 000000000000..a6d00ae5938c --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/herc.mdx @@ -0,0 +1,97 @@ +--- +title: herc +description: + The page provides detailed documentation for the Hierarchical Equal Risk + Contribution (HERC) method in the OpenBB Terminal's portfolio optimization module. + The method is used for the optimized allocation of resources in a portfolio to minimize + risk. The page includes a detailed explanation of input parameters, return types, + and code examples. +keywords: + - HERC Method + - Portfolio Optimization + - Risk Management + - Hierarchical Equal Risk Contribution + - Financial Modelling +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.herc(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.17521 + MSFT 0.19846 + AMZN 0.62633, + {'Return': 0.16899696275924703, + 'Volatility': 0.34337400112782096, + 'Sharpe ratio': 0.49216586638525933}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.herc(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/reference/portfolio/po/hrp.md b/website/content/sdk/reference/portfolio/po/hrp.md deleted file mode 100644 index 9930993ad2e7..000000000000 --- a/website/content/sdk/reference/portfolio/po/hrp.md +++ /dev/null @@ -1,96 +0,0 @@ ---- -title: hrp -description: This page provides information about the Hierarchical Risk Parity (HRP) - function in the openbb.portfolio.po module. This function allows for portfolio optimization - using HRP. Detailed parameter explanations, return values, and usage examples are - provided. -keywords: -- portfolio optimization -- Hierarchical Risk Parity -- openbb.portfolio.po -- risk management -- asset allocation -- portfolio management -- financial modeling ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.hrp(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.26729 - MSFT 0.30277 - AMZN 0.42994, - {'Return': 0.20463517260107467, - 'Volatility': 0.3313935169747041, - 'Sharpe ratio': 0.6174990219156727}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.hrp(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/hrp.mdx b/website/content/sdk/reference/portfolio/po/hrp.mdx new file mode 100644 index 000000000000..afb15d15f9e6 --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/hrp.mdx @@ -0,0 +1,98 @@ +--- +title: hrp +description: + This page provides information about the Hierarchical Risk Parity (HRP) + function in the openbb.portfolio.po module. This function allows for portfolio optimization + using HRP. Detailed parameter explanations, return values, and usage examples are + provided. +keywords: + - portfolio optimization + - Hierarchical Risk Parity + - openbb.portfolio.po + - risk management + - asset allocation + - portfolio management + - financial modeling +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.hrp(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.26729 + MSFT 0.30277 + AMZN 0.42994, + {'Return': 0.20463517260107467, + 'Volatility': 0.3313935169747041, + 'Sharpe ratio': 0.6174990219156727}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.hrp(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/reference/portfolio/po/nco.md b/website/content/sdk/reference/portfolio/po/nco.md deleted file mode 100644 index dbf6407ff61d..000000000000 --- a/website/content/sdk/reference/portfolio/po/nco.md +++ /dev/null @@ -1,97 +0,0 @@ ---- -title: nco -description: This page is about the Non-Convex Optimization (NCO) model used for portfolio - optimization. It includes a detailed explanation of the function parameters, return - values, and examples of usage using the OpenBB financial software. -keywords: -- Non-Convex Optimization -- portfolio optimization -- financial software -- financial modeling -- risk measures -- portfolio performance measures -- Sharpe ratio -- Value at Risk -- Maximum Drawdown ---- - -import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; - -
Use `portfolio.po.load` to load a portfolio engine | None | True | -| symbols | List[str] | List of symbols, by default None | None | True | -| interval | str | Interval to get data, by default '3y' | None | True | -| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | -| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | -| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | -| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | -| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | -| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | -| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | -| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | -| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | -| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | -| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | -| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | -| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | -| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | -| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | -| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | -| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{0.5(1-\rho^{spearman}_{i,j})}
- 'abs_pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{pearson}_{i,j}|)}
- 'abs_spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-|\rho^{spearman}_{i,j}|)}
- 'distance': distance correlation matrix. Distance formula:
.. math:: D_{i,j} = \sqrt{(1-\rho^{distance}_{i,j})}
- 'mutual_info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: D_{i,j} = -\log{\lambda_{i,j}} | None | True | -| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | -| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | -| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | -| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | -| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | -| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | - - ---- - -## Returns - -| Type | Description | -| ---- | ----------- | -| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | ---- - -## Examples - -```python -from openbb_terminal.sdk import openbb -openbb.portfolio.po.nco(symbols=["AAPL", "MSFT", "AMZN"]) -``` - -``` -( value - AAPL 0.25044 - MSFT 0.49509 - AMZN 0.25447, - {'Return': 0.2248615963428331, - 'Volatility': 0.32736590080425004, - 'Sharpe ratio': 0.6868815468880802}) -``` -```python -from openbb_terminal.sdk import openbb -p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") -weights, performance = openbb.portfolio.po.nco(portfolio_engine=p) -``` - ---- diff --git a/website/content/sdk/reference/portfolio/po/nco.mdx b/website/content/sdk/reference/portfolio/po/nco.mdx new file mode 100644 index 000000000000..81f188f22d1b --- /dev/null +++ b/website/content/sdk/reference/portfolio/po/nco.mdx @@ -0,0 +1,99 @@ +--- +title: nco +description: + This page is about the Non-Convex Optimization (NCO) model used for portfolio + optimization. It includes a detailed explanation of the function parameters, return + values, and examples of usage using the OpenBB financial software. +keywords: + - Non-Convex Optimization + - portfolio optimization + - financial software + - financial modeling + - risk measures + - portfolio performance measures + - Sharpe ratio + - Value at Risk + - Maximum Drawdown +--- + +import HeadTitle from "@site/src/components/General/HeadTitle.tsx"; + +
Use `portfolio.po.load` to load a portfolio engine | None | True | +| symbols | List[str] | List of symbols, by default None | None | True | +| interval | str | Interval to get data, by default '3y' | None | True | +| start_date | str | If not using interval, start date string (YYYY-MM-DD), by default "" | None | True | +| end_date | str | If not using interval, end date string (YYYY-MM-DD). If empty use last weekday, by default "" | None | True | +| log_returns | bool | If True use log returns, else arithmetic returns, by default False | None | True | +| freq | str | Frequency of returns, by default 'D'. Options: 'D' for daily, 'W' for weekly, 'M' for monthly | None | True | +| maxnan | float | Maximum percentage of NaNs allowed in the data, by default 0.05 | None | True | +| threshold | float | Value used to replace outliers that are higher than threshold, by default 0.0 | None | True | +| method | str | Method used to fill nan values, by default 'time'
For more information see `interpolate
Possible values are:
- 'MinRisk': Minimize the selected risk measure.
- 'Utility': Maximize the risk averse utility function.
- 'Sharpe': Maximize the risk adjusted return ratio based on the selected risk measure.
- 'MaxRet': Maximize the expected return of the portfolio. | None | True | +| risk_measure | str | The risk measure used to optimize the portfolio, by default 'MV'
If model is 'NCO', the risk measures available depends on the objective function.
Possible values are:
- 'MV': Variance.
- 'MAD': Mean Absolute Deviation.
- 'MSV': Semi Standard Deviation.
- 'FLPM': First Lower Partial Moment (Omega Ratio).
- 'SLPM': Second Lower Partial Moment (Sortino Ratio).
- 'VaR': Value at Risk.
- 'CVaR': Conditional Value at Risk.
- 'TG': Tail Gini.
- 'EVaR': Entropic Value at Risk.
- 'WR': Worst Realization (Minimax).
- 'RG': Range of returns.
- 'CVRG': CVaR range of returns.
- 'TGRG': Tail Gini range of returns.
- 'MDD': Maximum Drawdown of uncompounded cumulative returns (Calmar Ratio).
- 'ADD': Average Drawdown of uncompounded cumulative returns.
- 'DaR': Drawdown at Risk of uncompounded cumulative returns.
- 'CDaR': Conditional Drawdown at Risk of uncompounded cumulative returns.
- 'EDaR': Entropic Drawdown at Risk of uncompounded cumulative returns.
- 'UCI': Ulcer Index of uncompounded cumulative returns.
- 'MDD_Rel': Maximum Drawdown of compounded cumulative returns (Calmar Ratio).
- 'ADD_Rel': Average Drawdown of compounded cumulative returns.
- 'DaR_Rel': Drawdown at Risk of compounded cumulative returns.
- 'CDaR_Rel': Conditional Drawdown at Risk of compounded cumulative returns.
- 'EDaR_Rel': Entropic Drawdown at Risk of compounded cumulative returns.
- 'UCI_Rel': Ulcer Index of compounded cumulative returns. | None | True | +| risk_free_rate | float | Risk free rate, annualized. Used for 'FLPM' and 'SLPM' and Sharpe objective function, by default 0.0 | None | True | +| risk_aversion | float | Risk aversion factor of the 'Utility' objective function, by default 1.0 | None | True | +| alpha | float | Significance level of VaR, CVaR, EDaR, DaR, CDaR, EDaR, Tail Gini of losses, by default 0.05 | None | True | +| a_sim | float | Number of CVaRs used to approximate Tail Gini of losses, by default 100 | None | True | +| beta | float | Significance level of CVaR and Tail Gini of gains. If None it duplicates alpha value, by default None | None | True | +| b_sim | float | Number of CVaRs used to approximate Tail Gini of gains. If None it duplicates a_sim value, by default None | None | True | +| covariance | str | The method used to estimate the covariance matrix, by default 'hist'
Possible values are:
- 'hist': use historical estimates.
- 'ewma1': use ewma with adjust=True. For more information see `EWM
- 'ewma2': use ewma with adjust=False. For more information see `EWM
- 'ledoit': use the Ledoit and Wolf Shrinkage method.
- 'oas': use the Oracle Approximation Shrinkage method.
- 'shrunk': use the basic Shrunk Covariance method.
- 'gl': use the basic Graphical Lasso Covariance method.
- 'jlogo': use the j-LoGo Covariance method. For more information see: `a-jLogo`.
- 'fixed': denoise using fixed method. For more information see chapter 2 of `a-MLforAM`.
- 'spectral': denoise using spectral method. For more information see chapter 2 of `a-MLforAM`.
- 'shrink': denoise using shrink method. For more information see chapter 2 of `a-MLforAM`. | None | True | +| d_ewma | float | The smoothing factor of ewma methods, by default 0.94 | None | True | +| codependence | str | The codependence or similarity matrix used to build the distance
metric and clusters. The default is 'pearson'. Possible values are:
- 'pearson': pearson correlation matrix. Distance formula:
.. math:: $D_{i,j} = \sqrt{0.5(1-\rho^{pearson}_{i,j})}$
- 'spearman': spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{0.5(1-\rho^{spearman}*{i,j})}$
- 'abs*pearson': absolute value pearson correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{pearson}\_{i,j}\|)}$
- 'abs*spearman': absolute value spearman correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\|\rho^{spearman}\_{i,j}\|)}$
- 'distance': distance correlation matrix. Distance formula:
.. math:: $D*{i,j} = \sqrt{(1-\rho^{distance}*{i,j})}$
- 'mutual*info': mutual information matrix. Distance used is variation information matrix.
- 'tail': lower tail dependence index matrix. Dissimilarity formula:
.. math:: $D*{i,j} = -\log{\lambda\_{i,j}}$ | None | True | +| linkage | str | Linkage method of hierarchical clustering. For more information see `linkage
The default is 'single'. Possible values are:
- 'single'.
- 'complete'.
- 'average'.
- 'weighted'.
- 'centroid'.
- 'median'.
- 'ward'.
- 'dbht': Direct Bubble Hierarchical Tree. | None | True | +| k | int | Number of clusters. This value is took instead of the optimal number
of clusters calculated with the two difference gap statistic, by default None | None | True | +| max_k | int | Max number of clusters used by the two difference gap statistic
to find the optimal number of clusters, by default 10 | None | True | +| bins_info | str | Number of bins used to calculate variation of information, by default 'KN'.
Possible values are:
- 'KN': Knuth's choice method. For more information see `knuth_bin_width
- 'FD': Freedman–Diaconis' choice method. For more information see `freedman_bin_width
- 'SC': Scotts' choice method. For more information see `scott_bin_width
- 'HGR': Hacine-Gharbi and Ravier' choice method. | None | True | +| alpha_tail | float | Significance level for lower tail dependence index, by default 0.05 | None | True | +| leaf_order | bool | Indicates if the cluster are ordered so that the distance between
successive leaves is minimal, by default True | None | True | + +--- + +## Returns + +| Type | Description | +| ------------------------- | --------------------------------------------- | +| Tuple[pd.DataFrame, Dict] | Tuple with weights and performance dictionary | + +--- + +## Examples + +```python +from openbb_terminal.sdk import openbb +openbb.portfolio.po.nco(symbols=["AAPL", "MSFT", "AMZN"]) +``` + +``` +( value + AAPL 0.25044 + MSFT 0.49509 + AMZN 0.25447, + {'Return': 0.2248615963428331, + 'Volatility': 0.32736590080425004, + 'Sharpe ratio': 0.6868815468880802}) +``` + +```python +from openbb_terminal.sdk import openbb +p = openbb.portfolio.po.load(symbols_file_path="~/openbb_terminal/miscellaneous/portfolio_examples/allocation/60_40_Portfolio.xlsx") +weights, performance = openbb.portfolio.po.nco(portfolio_engine=p) +``` + +--- diff --git a/website/content/sdk/usage/api-keys.md b/website/content/sdk/usage/api-keys.md index 740c7d893e00..5a687a50decc 100644 --- a/website/content/sdk/usage/api-keys.md +++ b/website/content/sdk/usage/api-keys.md @@ -3,17 +3,16 @@ title: Setting API Keys sidebar_position: 2 description: This documentation page describes how you can set your own API keys from each data vendor on OpenBB to leverage their datasets. keywords: -- API keys -- datasets -- data vendors -- subscription + - API keys + - datasets + - data vendors + - subscription --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
-
Instructions
+Instructions
Go to: https://www.alphavantage.co/support/#api-key @@ -107,7 +106,7 @@ openbb.keys.av(key = 'REPLACE_WITH_KEY', persist = True) > Binance cryptocurrency exchange - We operate the worlds biggest bitcoin exchange and altcoin crypto exchange in the world by volume
-
Instructions
+Instructions
Go to: https://www.binance.com/en/support/faq/how-to-create-api-360002502072 @@ -130,9 +129,9 @@ openbb.keys.binance( > Bitquery is an API-first product company dedicated to power and solve blockchain data problems using the ground truth of on-chain data.
-
Instructions
+Instructions
-Go to: https://bitquery.io/< +Go to: [https://bitquery.io/](https://bitquery.io/)  @@ -157,17 +156,17 @@ openbb.keys.bitquery(key = 'REPLACE_WITH_KEY', persist = True) > BizToc is the one-stop business and finance news hub, encapsulating the top 200 US news providers in real time.
-
Instructions
+Instructions
-The BizToc API is hosted on RapidAPI. To set up, go to: https://rapidapi.com/thma/api/biztoc. +The BizToc API is hosted on RapidAPI. To set up, go to: https://rapidapi.com/thma/api/biztoc.  -In the top right, select "Sign Up". After answering some questions, you will be prompted to select one of their plans. +In the top right, select "Sign Up". After answering some questions, you will be prompted to select one of their plans.  -After signing up, navigate back to https://rapidapi.com/thma/api/biztoc. If you are logged in, you will see a header called X-RapidAPI-Key. +After signing up, navigate back to https://rapidapi.com/thma/api/biztoc. If you are logged in, you will see a header called X-RapidAPI-Key.  @@ -184,7 +183,7 @@ openbb.keys.biztoc(key = "REPLACE_WITH_KEY", persist=True) > CoinMarketCap is the world's most-referenced price-tracking website for cryptoassets in the rapidly growing cryptocurrency space. Its mission is to make crypto discoverable and efficient globally by empowering retail users with unbiased, high quality and accurate information for drawing their own informed conclusions.
-
Instructions
+Instructions
Go to: https://coinmarketcap.com/api @@ -211,7 +210,7 @@ openbb.keys.cmc(key = 'REPLACE_WITH_KEY', persist = True) > Coinbase is a secure online platform for buying, selling, transferring, and storing cryptocurrency.
-
Instructions
+Instructions
Go to: https://help.coinbase.com/en/exchange/managing-my-account/how-to-create-an-api-key @@ -235,7 +234,7 @@ openbb.keys.coinbase( > Coinglass is a cryptocurrency futures trading & information platform,where you can find the Bitcoin Liquidations ,Bitcoin open interest, Grayscale Bitcoin Trust，Bitcoin longs vs shorts ratio and actively compare funding rates for crypto futures.Above all the quantities are shown as per their respective contract value.
-
Instructions
+Instructions
Go to: https://www.coinglass.com/ @@ -255,20 +254,20 @@ openbb.keys.coinglass(key = 'REPLACE_WITH_KEY', persist = True) ### Companies House -> The Companies House API lets you retrieve information about limited companies (and other companies that fall within the Companies Act 2006). The data returned is live and real-time, and is simple to use and understand. +> The Companies House API lets you retrieve information about limited companies (and other companies that fall within the Companies Act 2006). The data returned is live and real-time, and is simple to use and understand.
-
Instructions
+Instructions
Setup an account by following the instructions [here](https://developer-specs.company-information.service.gov.uk/guides/gettingStarted#set-up-a-companies-house-account).  -After creating the account and logging in, click on, [Create an Application](https://developer.company-information.service.gov.uk/manage-applications/add). Fill out the form and then click the `Create` button at the bottom of the page. +After creating the account and logging in, click on, [Create an Application](https://developer.company-information.service.gov.uk/manage-applications/add). Fill out the form and then click the `Create` button at the bottom of the page.  -Once the application is created, an API key can be generated by clicking on `View all Applications`, and then the `Create new key` button at the bottom. Copy the API key value to the clipboard and then enter it into the OpenBB SDK with: +Once the application is created, an API key can be generated by clicking on `View all Applications`, and then the `Create new key` button at the bottom. Copy the API key value to the clipboard and then enter it into the OpenBB SDK with: ```console openbb.keys.companieshouse('REPLACE_WITH_KEY', persist = True) @@ -281,7 +280,7 @@ openbb.keys.companieshouse('REPLACE_WITH_KEY', persist = True) > CryptoPanic is a news aggregator platform indicating impact on price and market for traders and cryptocurrency enthusiasts.
-
Instructions
+Instructions
Go to: https://cryptopanic.com/developers/api/ @@ -304,7 +303,7 @@ openbb.keys.cpanic(key = 'REPLACE_WITH_KEY', persist = True) > Databento eliminates tens of thousands of dollars in upfront expenses per dataset without sacrificing data integrity. We give you the flexibility to pick up real-time full exchange feeds and terabytes of historical data, whenever you need it.
-
Instructions
+Instructions
Go to: https://docs.databento.com/getting-started @@ -327,7 +326,7 @@ openbb.keys.databento(key = 'REPLACE_WITH_KEY') > DEGIRO is Europe's fastest growing online stock broker. DEGIRO distinguishes itself from its competitors by offering extremely low trading commissions.
-
Instructions
+Instructions
Go to: https://www.degiro.com/ @@ -352,7 +351,7 @@ Instructions for setting up 2FA authorization are [here](https://github.com/Chav > Historical End of Day, Intraday, and Live prices API, with Fundamental Financial data API for more than 120000 stocks, ETFs and funds all over the world.
-
Instructions
+Instructions
Go to: https://eodhistoricaldata.com/r/?ref=869U7F4J @@ -379,7 +378,7 @@ openbb.keys.eodhd(key = 'REPLACE_WITH_KEY', persist = True) > With the sole mission of democratizing financial data, we are proud to offer a FREE realtime API for stocks, forex and cryptocurrency.
-
Instructions
+Instructions
Go to: https://finnhub.io/ @@ -406,7 +405,7 @@ openbb.keys.finnhub(key = 'REPLACE_WITH_KEY', persist = True) > Enhance your application with our data that goes up to 30 years back in history. Earnings calendar, financial statements, multiple exchanges and more!
-
Instructions
+Instructions
Go to: https://site.financialmodelingprep.com/developer/docs @@ -435,7 +434,7 @@ openbb.keys.fmp(key = 'REPLACE_WITH_KEY', persist = True) > FRED is the trusted source for economic data since 1991. Download, graph, and track 819,000 US and international time series from 110 sources.
-
Instructions
+Instructions
Go to: https://fred.stlouisfed.org @@ -466,7 +465,7 @@ openbb.keys.fred(key = 'REPLACE_WITH_KEY', persist = True) > GitHub is where over 100 million developers shape the future of software.
-
Instructions
+Instructions
 @@ -491,7 +490,7 @@ openbb.keys.github(key = 'REPLACE_WITH_KEY', persist = True) > Glassnode makes blockchain data accessible for everyone. We source and carefully dissect on-chain data, to deliver contextualized and actionable insights.
-
Instructions
+Instructions
Go to: https://studio.glassnode.com @@ -518,7 +517,7 @@ openbb.keys.glassnode(key = 'REPLACE_WITH_KEY', persist = True) > Intrinio is more than a financial data API provider – we're a real time data partner. That means we're your guide to every step of the financial data.
-
Instructions
+Instructions
Go to: https://intrinio.com/starter-plan @@ -537,7 +536,7 @@ openbb.keys.intrinio(key = 'REPLACE_WITH_KEY', persist = True) > Gain an edge over the crypto market with professional grade data, tools, and research.
-
Instructions
+Instructions
Go to: https://messari.io @@ -564,7 +563,7 @@ openbb.keys.messari(key = 'REPLACE_WITH_KEY', persist = True) > News API is a simple, easy-to-use REST API that returns JSON search results for current and historic news articles published by over 80,000 worldwide sources.
-
Instructions
+Instructions
Go to: https://newsapi.org @@ -591,7 +590,7 @@ openbb.keys.news(key = 'REPLACE_WITH_KEY', persist = True) > OANDA's Currency Converter allows you to check the latest foreign exchange average bid/ask rates and convert all major world currencies.
-
Instructions
+Instructions
Go to: https://developer.oanda.com @@ -619,7 +618,7 @@ openbb.keys.oanda( > Live & historical data for US stocks for all 19 exchanges. Instant access to real-time and historical stock market data.
-
Instructions
+Instructions
Go to: https://polygon.io @@ -646,7 +645,7 @@ openbb.keys.polygon(key = 'REPLACE_WITH_KEY', persist = True) > The premier source for financial, economic, and alternative datasets, serving investment professionals. Quandl’s platform is used by over 400,000 people, including analysts from the world’s top hedge funds, asset managers and investment banks.
-
Instructions
+Instructions
 @@ -671,7 +670,7 @@ openbb.keys.quandl(key = 'REPLACE_WITH_KEY', persist = True) > Reddit is a network of communities where people can dive into their interests, hobbies and passions.
-
Instructions
+Instructions
Sign in to Reddit, and then go to: https://old.reddit.com/prefs/apps/ @@ -709,7 +708,7 @@ openbb.keys.reddit( > Robinhood has commission-free investing, and tools to help shape your financial future.
-
Instructions
+Instructions
Go to: https://robinhood.com/us/en @@ -733,7 +732,7 @@ The first login will request 2FA authorization from the device connected to the > We provide tools to help you analyze crypto markets and find data-driven opportunities to optimize your investing.
-
Instructions
+Instructions
Go to: https://app.santiment.net @@ -760,7 +759,7 @@ openbb.keys.santiment(key = 'REPLACE_WITH_KEY', persist = True) > Empowering investors to take advantage of alternative data. We track trending tickers on social media and provide alternative data for easy due-diligence & analysis.
-
Instructions
+Instructions
Go to: https://stocksera.pythonanywhere.com @@ -787,7 +786,7 @@ openbb.keys.stocksera(key = 'REPLACE_WITH_KEY', persist = True) > Token Terminal is a platform that aggregates financial data on the leading blockchains and decentralized applications.
-
Instructions
+Instructions
Go to: https://tokenterminal.com @@ -814,7 +813,7 @@ openbb.keys.tokenterminal(key = 'REPLACE_WITH_KEY', persist = True) > Tradier, the home of active traders. Our open collaboration platform allows investors to truly customize their trading experience like never before.
-
Instructions
+Instructions
Go to: https://documentation.tradier.com @@ -833,7 +832,7 @@ openbb.keys.tradier(key = 'REPLACE_WITH_KEY', persist = True) > From breaking news and entertainment to sports and politics, get the full story with all the live commentary.
-
Upcoming changes to the Twitter API will deprecate the current functionality, it is uncertain if the features will continue to work.
+Upcoming changes to the Twitter API will deprecate the current functionality, it is uncertain if the features will continue to work.
 @@ -844,7 +843,7 @@ openbb.keys.tradier(key = 'REPLACE_WITH_KEY', persist = True) > Whale Alert continuously collects and analyzes billions of blockchain transactions and related-off chain data from hundreds of reliable sources and converts it into an easy to use standardized format. Our world-class analytics and custom high speed database solutions process transactions the moment they are made, resulting in the largest and most up-to-date blockchain dataset in the world.
-
Instructions
+Instructions
Go to: https://docs.whale-alert.io  diff --git a/website/content/terminal/faqs/bugs_support_feedback.md b/website/content/terminal/faqs/bugs_support_feedback.md index 856cb1c589b6..8929444a78e2 100644 --- a/website/content/terminal/faqs/bugs_support_feedback.md +++ b/website/content/terminal/faqs/bugs_support_feedback.md @@ -1,19 +1,20 @@ --- title: Bugs, Support, and Feedback sidebar_position: 5 -description: Familiarize yourself with common issues and bug reports within our OpenBB +description: + Familiarize yourself with common issues and bug reports within our OpenBB Terminal, explore our patch release process and learn how to report issues or get support for OpenBB Terminal. You'll also learn how to provide feedback and request specific features within the platform. keywords: -- GitHub -- bugs -- patches -- issue reporting -- support -- Discord -- feature requests -- machine learning + - GitHub + - bugs + - patches + - issue reporting + - support + - Discord + - feature requests + - machine learning --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -22,7 +23,8 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; When an error is encountered, it is always a good idea to check the open issues on [GitHub](https://github.com/OpenBB-finance/OpenBBTerminal/issues). There may be a workaround solution for the specific problem until a patch is released. -How often are patches for bugs released?
+
+
-How often are patches for bugs released?
The installer versions are packaged approximately every two-weeks. Those working with a cloned GitHub version can checkout the Develop branch to get the latest fixes and releases before they are pushed to the main branch. @@ -32,19 +34,22 @@ git checkout developHow do I report a bug?
+
+
-How do I report a bug?
First, search the open issues for another report. If one already exists, attach any relevant information and screenshots as a comment. If one does not exist, start one with this [link](https://github.com/OpenBB-finance/OpenBBTerminal/issues/new?assignees=&labels=type%3Abug&template=bug_report.md&title=%5BBug%5D)How can I get help with OpenBB Terminal?
+
+
-How can I get help with OpenBB Terminal?
You can get help with OpenBB Terminal by joining our [Discord server](https://openbb.co/discord) or contact us in our support form [here](https://openbb.co/support).How can I give feedback about the OpenBB Terminal, or request specific functionality?
+
+
How can I give feedback about the OpenBB Terminal, or request specific functionality?
Being an open source platform that wishes to tailor to the needs of any type of investor, we highly encourage anyone to share with us their experience and/or how we can further improve the OpenBB Terminal. This can be anything from a very small bug, a new feature, or the implementation of a highly advanced Machine Learning model. diff --git a/website/content/terminal/faqs/data_sources.md b/website/content/terminal/faqs/data_sources.md index 945c74c56e5d..3ad3a5144f1d 100644 --- a/website/content/terminal/faqs/data_sources.md +++ b/website/content/terminal/faqs/data_sources.md @@ -1,17 +1,18 @@ --- title: Data and Sources sidebar_position: 4 -description: The page discusses the data sources and functionalities of OpenBB, an +description: + The page discusses the data sources and functionalities of OpenBB, an aggregator of data from various sources. It guides on troubleshooting, locating data, and requesting features. keywords: -- data aggregator -- troubleshooting guide -- data sources -- ticker symbols -- load function -- feature request -- data providers + - data aggregator + - troubleshooting guide + - data sources + - ticker symbols + - load function + - feature request + - data providers --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -22,13 +23,15 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; Please note that OpenBB does not provide any data, it is an aggregator which provides users access to data from a variety of sources. OpenBB does not maintain or have any control over the raw data supplied. If there is a specific problem with the output from a data provider, please consider contacting them first. -Is there a list of all data providers?
+
+
-Is there a list of all data providers?
The complete list is found [here](/terminal/usage/data/api-keys)How do I find and load a ticker symbol from India, or any other country?
+
+
-How do I find and load a ticker symbol from India, or any other country?
Use the [`/stocks/search`](/terminal/menus/stocks/introduction#search) command. @@ -46,7 +49,8 @@ The precise naming convention will differ by source, reference each source's ownData from today is missing.
+
+
-Data from today is missing.
By default, the load function requests end-of-day daily data and is not included until the EOD summary has been published. The current day's data is considered intraday and is loaded when the `interval` argument is present. @@ -56,13 +60,15 @@ load SPY -i 60Can I stream live prices and news feeds?
+
+
-Can I stream live prices and news feeds?
The OpenBB Terminal is not currently capable of streaming live feeds through websocket connections."Pair BTC/USDT not found in binance"
+
+
-"Pair BTC/USDT not found in binance"
US-based users are currently unable to access the Binance API. Please try loading the pair from a different source, for example: @@ -70,7 +76,8 @@ US-based users are currently unable to access the Binance API. Please try loadinHow can I request functionality for a specific data source?
+
+
How can I request functionality for a specific data source?
Please [request a feature](https://openbb.co/request-a-feature) by submitting a new request. diff --git a/website/content/terminal/faqs/developer_issues.md b/website/content/terminal/faqs/developer_issues.md index d3a9d8cf79c5..5372837ca471 100644 --- a/website/content/terminal/faqs/developer_issues.md +++ b/website/content/terminal/faqs/developer_issues.md @@ -1,43 +1,46 @@ --- title: Developer Issues sidebar_position: 6 -description: This page helps with frequently asked questions regarding debugging, +description: + This page helps with frequently asked questions regarding debugging, GitHub pull requests, and common error resolutions. The guide includes steps on how to launch in debug mode, switching branches, handling missing dependencies like wheel, dealing with .whl files, understanding JSONDecodeError, correcting line break errors, and using VS Code terminal. keywords: -- debug mode -- GitHub pull requests -- error resolutions -- missing dependencies -- wheel -- .whl file errors -- JSONDecodeError -- line break errors -- VS Code terminal -- poetry -- conda -- pip + - debug mode + - GitHub pull requests + - error resolutions + - missing dependencies + - wheel + - .whl file errors + - JSONDecodeError + - line break errors + - VS Code terminal + - poetry + - conda + - pip --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';How do I launch in debug mode?
+
+
-How do I launch in debug mode?
-When installed from source, the OpenBB Terminal can be launched in debug mode. Launch the Terminal using the syntax below. +When installed from source, the OpenBB Terminal can be launched in debug mode. Launch the Terminal using the syntax below. ```python python terminal.py --debug ``` -Operate the Terminal normally, and errors will trigger an interrupt which prints the traceback with the error. Charts and tables will also include a developer tools button, located at the top-left of the window, for identifying issues specific to the PyWry interactive window. +Operate the Terminal normally, and errors will trigger an interrupt which prints the traceback with the error. Charts and tables will also include a developer tools button, located at the top-left of the window, for identifying issues specific to the PyWry interactive window.What branch on GitHub should pull requests be submitted to?
+
+
-What branch on GitHub should pull requests be submitted to?
Pull requests submitted to the Main branch will not be merged, please create branches from the `develop` branch. @@ -56,7 +59,8 @@ Branches must also follow the naming convention:Error: "git pull" fails because of a hot fix: cannot lock ref
+
+
-Error: "git pull" fails because of a hot fix: cannot lock ref
If the error message looks something like: @@ -73,7 +77,8 @@ git pullWhat does it mean if it says wheel is missing?
+
+
-What does it mean if it says wheel is missing?
If you receive any notifications regarding `wheel` missing, this could be due to this dependency missing. @@ -81,7 +86,8 @@ If you receive any notifications regarding `wheel` missing, this could be due toWhy do these .whl files not exist?
+
+
-Why do these .whl files not exist?
If you get errors about .whl files not existing (usually on Windows) you have to reinitialize the following folder. Just removing the 'artifacts' folder could also be enough: @@ -112,12 +118,14 @@ If you run into trouble with Poetry, and the advice above did not help, your bes - `conda env remove -n obb` - `conda clean -a` - Make a new environment and install dependencies again. + - Reboot your computer and try again - Submit a ticket on GitHubWhat does the JSONDecodeError mean during poetry install?
+
+
-What does the JSONDecodeError mean during poetry install?
Sometimes poetry can throw a `JSONDecodeError` on random packages while running `poetry install`. This can be observed on macOS 10.14+ running python 3.8+. This is because of the use of an experimental installer that can be switched off to avoid the mentioned error. Run the code below as advised [here](https://github.com/python-poetry/poetry/issues/4210) and it should fix the installation process. @@ -133,7 +141,8 @@ _Commands that may help you in case of an error:_How do I deal with errors regarding CRLF?
+
+
-How do I deal with errors regarding CRLF?
When trying to commit code changes, pylint will prevent you from doing so if your line break settings are set to CRLF (default for Windows). @@ -156,7 +165,8 @@ git reset --hardWhy can't I run OpenBB via the VS Code integrated terminal?
+
+
Why can't I run OpenBB via the VS Code integrated terminal?
This occurs when VS Code terminal python version/path is different from the terminal version. diff --git a/website/content/terminal/faqs/general_operation.md b/website/content/terminal/faqs/general_operation.md index 0e2441b37dc6..5c7f2b38fa6c 100644 --- a/website/content/terminal/faqs/general_operation.md +++ b/website/content/terminal/faqs/general_operation.md @@ -1,21 +1,22 @@ --- title: General Operation sidebar_position: 3 -description: Learn how to overcome system-related issues by enabling the 'developer +description: + Learn how to overcome system-related issues by enabling the 'developer mode' on Windows and MacOS. Get answers for queries and potential issues. Here, you'll also get to know how to run applications that do not meet the system's security policy, allow apps through firewall and get tips on portfolio management. keywords: -- developer mode -- overcome system-related issues -- Windows -- MacOS -- run applications -- system's security policy -- allow apps through firewall -- Portfolio management -- Settings -- FAQ + - developer mode + - overcome system-related issues + - Windows + - MacOS + - run applications + - system's security policy + - allow apps through firewall + - Portfolio management + - Settings + - FAQ --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -35,7 +36,8 @@ From the Windows Security menu, click on the Firewall & Network Protection tab, - VcXsrv - Windows Terminal -Why does a specific menu or command not exist?
+
+
-Why does a specific menu or command not exist?
It could be that you are running an outdated version in which the menu or command is not yet available. Please check the [installation guide](/terminal/installation) to download the most recent release. @@ -43,25 +45,29 @@ Do note that it is also possible that the menu or command has been deprecated. ICharts do not display on Linux/WSL or Docker installation.
+
+
-Charts do not display on Linux/WSL or Docker installation.
Check that X-11, or similar, is installed, open, and configured. Follow the instructions pertaining to the system here: [/terminal/installation/docker](/terminal/installation/docker)How do I retrieve more results than is returned by default?
+
+
-How do I retrieve more results than is returned by default?
Most functions will have either, `--start` and `--end` flags, or a `--limit` argument. Print the help dialogue for any command by attaching, `--help` or `-h`.Does the portfolio menu allow for dividends, interest, or other distributions?
+
+
-Does the portfolio menu allow for dividends, interest, or other distributions?
Currently, this is only possible by manually updating the portfolio file.Why does my Portfolio file fail to load?
+
+
-Why does my Portfolio file fail to load?
This can be the result of a formatting error, check the file in a simple text editor to observe any abnormalities in the formatting; or, it could be a bug - check the [GitHub issues page](https://github.com/OpenBB-finance/OpenBBTerminal/issues) for similar errors. @@ -81,19 +87,22 @@ See the guide [here](/sdk/data-available/portfolio/introduction) for more informHow do I change the chart styles?
+
+
-How do I change the chart styles?
-See the guide [here](/terminal/usage/overview/customizing-the-terminal). The theme can be toggled between light and dark mode, directly on the individual chart. See the [Terminal Basics page](/terminal/usage/basics#charts) for more information on working with the charts. +See the guide [here](/terminal/usage/overview/customizing-the-terminal). The theme can be toggled between light and dark mode, directly on the individual chart. See the [Terminal Basics page](/terminal/usage/basics#charts) for more information on working with the charts.Can I change the colors of the text in the Terminal?
+
+
-Can I change the colors of the text in the Terminal?
Yes, use the `colors` command under the `/settings` menu: [/terminal/usage/overview/customizing-the-terminal](/terminal/usage/overview/customizing-the-terminal)After setting the preset in the stocks screener, nothing happens.
+
+
-After setting the preset in the stocks screener, nothing happens.
Print the current screen again with by entering, `?`. Does the name of the selected preset display? With a preset loaded, run the screener by entering one of the commands below: @@ -106,7 +115,8 @@ Print the current screen again with by entering, `?`. Does the name of the selecForecast functions say to enter a valid data set
+
+
-Forecast functions say to enter a valid data set
Because an unlimited number of data sets can be loaded into the Forecast menu, each function requires defining the specific data set to be used. Add the `-d` or `--dataset` argument to the command, along with the name of the desired data set. @@ -116,9 +126,10 @@ rnn -d SPYHow do I find stocks from India, or another country?
+
+
How do I find stocks from India, or another country?
-Use the `search` command from the `/stocks` menu. Refer to the menu's introduction guide [here](/terminal/menus/stocks#search). +Use the `search` command from the `/stocks` menu. Refer to the menu's introduction guide [here](/terminal/menus/stocks#search). As an example, try this: diff --git a/website/content/terminal/faqs/installation_updates.md b/website/content/terminal/faqs/installation_updates.md index b063447cf159..fb6835234e17 100644 --- a/website/content/terminal/faqs/installation_updates.md +++ b/website/content/terminal/faqs/installation_updates.md @@ -1,20 +1,21 @@ --- title: Installation and Updates sidebar_position: 1 -description: This page provides comprehensive insights about installing and updating +description: + This page provides comprehensive insights about installing and updating the OpenBB Terminal. It discusses system requirements, installation process, common errors and their solutions. Information about updating the OpenBB Terminal through different methods is also covered. keywords: -- OpenBB Terminal installation -- Updating OpenBB Terminal -- System requirements for OpenBB Terminal -- Installation errors with OpenBB Terminal -- Python pip installation -- Microsoft Visual C++ -- Homebrew installation -- libomp -- Conda installation issue + - OpenBB Terminal installation + - Updating OpenBB Terminal + - System requirements for OpenBB Terminal + - Installation errors with OpenBB Terminal + - Python pip installation + - Microsoft Visual C++ + - Homebrew installation + - libomp + - Conda installation issue --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -23,13 +24,15 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; ## Installation and Updates -How much hard drive space is required?
+
+
-How much hard drive space is required?
An installation will use approximately 4-5 GB of space, with additional storage required for optional machine learning models.What is the minimum version of Windows or MacOS required to install the OpenBB Terminal?
+
+
-What is the minimum version of Windows or MacOS required to install the OpenBB Terminal?
The OpenBB Terminal installation packages are compatible with: @@ -40,7 +43,8 @@ The OpenBB Terminal installation packages are compatible with:How do I update my installation to the latest version?
+
+
How do I update my installation to the latest version?
The terminal is constantly being updated with new features and bug fixes. The process for updating will vary by the installation type: @@ -69,7 +73,8 @@ pip install openbb-terminal-nightly[all] **Note**: This version may not be stable and should not be used in a production setting. -"Microsoft Visual C++ 14.0 or greater is required"
+
+
-"Microsoft Visual C++ 14.0 or greater is required"
Download and install [C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/), restart the machine, then try again. @@ -79,7 +84,8 @@ Download and install [C++ Build Tools](https://visualstudio.microsoft.com/visualError: failed building wheel for bt
+
+
-Error: failed building wheel for bt
There may be an additional message that is printed from this error, stating: "Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools". @@ -100,13 +106,15 @@ brew install cmakeMiniconda3 will not install on ARM/Linux Raspberry Pi machines.
+
+
-Miniconda3 will not install on ARM/Linux Raspberry Pi machines.
Refer to this issue on the Conda [GitHub](https://github.com/conda/conda/issues/10723) page.Error: Library not loaded: '/usr/local/opt/libomp/lib/libomp.dylib'
+
+
Error: Library not loaded: '/usr/local/opt/libomp/lib/libomp.dylib'
This error is resolved by installing libomp from Homebrew: diff --git a/website/content/terminal/faqs/launching.md b/website/content/terminal/faqs/launching.md index 82970d5d8f2d..f9161cbb3e71 100644 --- a/website/content/terminal/faqs/launching.md +++ b/website/content/terminal/faqs/launching.md @@ -1,27 +1,29 @@ --- title: Launching sidebar_position: 2 -description: Comprehensive troubleshooting guide for various software and system compatibility +description: + Comprehensive troubleshooting guide for various software and system compatibility issues encountered while using the OpenBB Terminal. Covers topics such as Mac M1/M2 Rosetta installation, Terminal, and SDK launch issues, ModuleNotFoundError solutions, SSL certificates authorization failures, proxy connection issues, and Linux Ubuntu specific problems. keywords: -- Mac M1/M2 Rosetta installation -- Incompatible library version issue -- Terminal app launch failure -- ModuleNotFoundError OpenBB troubleshooting -- Fontconfig warning solution -- SSL certificates authorization failure -- Proxy connection issues -- Linux Ubuntu OpenBB launch issue + - Mac M1/M2 Rosetta installation + - Incompatible library version issue + - Terminal app launch failure + - ModuleNotFoundError OpenBB troubleshooting + - Fontconfig warning solution + - SSL certificates authorization failure + - Proxy connection issues + - Linux Ubuntu OpenBB launch issue --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';Mac: Invalid CPU Type - Terminal fails to launch.
+
+
-Mac: Invalid CPU Type - Terminal fails to launch.
This error is usually the result of a Mac M1/M2 machine which does not have Rosetta installed. Install from the system Terminal command line: @@ -31,7 +33,8 @@ softwareupdate --install-rosettaIncompatible library version: libtiff.6.dylib requires version 10.0.0 or later, but liblzma.5.dylib provides version 8.0.0
+
+
-Incompatible library version: libtiff.6.dylib requires version 10.0.0 or later, but liblzma.5.dylib provides version 8.0.0
This issue can be resolved by following the steps below. @@ -43,13 +46,15 @@ This issue can be resolved by following the steps below.Terminal app does not launch: Failed to execute script 'terminal' due to unhandled exception!
+
+
-Terminal app does not launch: Failed to execute script 'terminal' due to unhandled exception!
When an installer-packaged version of the OpenBB Terminal fails to launch, because of this message, the machine may have an obsolete CPU-type or operating system. Please try installing via the source code, and if problems persist, reach out to us on [Discord](https://discord.gg/xPHTuHCmuV) or fill out a support request form on our [website](https://openbb.co/support).ModuleNotFoundError: No module named '______'
+
+
-ModuleNotFoundError: No module named '______'
Before troubleshooting please verify that the recommended installation instructions were followed. These errors often can occur when the virtual environment has not been activated, or the `poetry install` command was skipped. Activate the OpenBB virtual environment created during the installation process prior to launching or importing the SDK. @@ -84,19 +89,21 @@ poetry install -E allFontconfig warning: ignoring UTF-8: not a valid region tag
+
+
-Fontconfig warning: ignoring UTF-8: not a valid region tag
In the OS default terminal shell profile, check for a variable similar to, “set locale environment variables at startup”, then also, set text encoding to UTF-8.SSL certificates fail to authorize
+
+
-SSL certificates fail to authorize
```console SSL: CERTIFICATE_VERIFY_FAILED ``` -An error message, similar to above, is usually encountered while attempting to use the OpenBB Platform from behind a firewall. A workplace environment is typically the most common occurrence. Try connecting to the internet directly through a home network to test the connection. If using a work computer and/or network, we recommend speaking with the company's IT department prior to installing or running any software. +An error message, similar to above, is usually encountered while attempting to use the OpenBB Platform from behind a firewall. A workplace environment is typically the most common occurrence. Try connecting to the internet directly through a home network to test the connection. If using a work computer and/or network, we recommend speaking with the company's IT department prior to installing or running any software. A potential solution is to try: @@ -106,7 +113,8 @@ pip install pip-system-certsCannot connect due to proxy connection.
+
+
-Cannot connect due to proxy connection.
Find the `.env` file (located at the root of the user account folder: (`~/.openbb_terminal/.env`), and add a line at the bottom of the file with: @@ -116,7 +124,8 @@ HTTP_PROXY="" or HTTPS_PROXY="”Linux Ubuntu installation was successful but now hangs on launch.
+
+
Linux Ubuntu installation was successful but now hangs on launch.
Check that VcXsvr - or an equivalent X-host - is running and configured prior to launch. diff --git a/website/content/terminal/installation/macos.md b/website/content/terminal/installation/macos.md index 699debd8f71a..b44f615b533f 100644 --- a/website/content/terminal/installation/macos.md +++ b/website/content/terminal/installation/macos.md @@ -1,22 +1,23 @@ --- title: MacOS sidebar_position: 2 -description: Step-by-step instructions for installing the OpenBB Terminal on MacOS. +description: + Step-by-step instructions for installing the OpenBB Terminal on MacOS. This guide covers installation for both Intel-based computers and Apple Silicon (M1) devices, and includes instructions for preliminaries like installing Rosetta for M1 users. keywords: -- OpenBB Terminal Installation -- MacOS installation guide -- OpenBB on Mac Intel -- OpenBB on Mac M1 -- Rosetta installation -- PKG installer -- OpenBB Terminal application -- MacOS Big Sur installation -- MacOS Monterey installation -- Apple Silicon installation -- Unverified developer warning + - OpenBB Terminal Installation + - MacOS installation guide + - OpenBB on Mac Intel + - OpenBB on Mac M1 + - Rosetta installation + - PKG installer + - OpenBB Terminal application + - MacOS Big Sur installation + - MacOS Monterey installation + - Apple Silicon installation + - Unverified developer warning --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -33,7 +34,8 @@ Install the OpenBB Terminal on MacOS (Big Sur or later). There are two versionsMinimum Requirements
+
+
Minimum Requirements
- MacOS Monterey or newer - Modern CPU (Intel processor made in the last 5 years or Apple Silicon chip) @@ -46,14 +48,15 @@ Install the OpenBB Terminal on MacOS (Big Sur or later). There are two versions :::info Apple Silicon users will need to install Rosetta prior to installation To understand whether you are using an Apple Sillicon (M1) device or an Intel-based device click on the Apple Icon at the top left of your MacBook and select "About This Mac". Then under "Chip" if it says something like "Apple M1 Pro" or "Apple M1 Max", you know you have an Apple Silicon MacBook. If it says for example "2,3 GHz Quad-Core Intel Core i7" you know that you have an Intel-based MacBook and you can continue by clicking on the "Mac Intel Installer" button. -Rosetta Installation Instructions (Apple Sillicon users only)
+
+
+
3. Follow the Installer prompt. You will be asked to enter your system password.
-
+
4. This process installs the application into the `/Application/OpenBB Terminal` folder.
-
+
5. Launch the application by double-clicking on the `OpenBB Terminal` application. If everything was successful you should see a screen like the one below:
diff --git a/website/content/terminal/installation/source.md b/website/content/terminal/installation/source.md
index dbf563d32a5d..df487282ebb0 100644
--- a/website/content/terminal/installation/source.md
+++ b/website/content/terminal/installation/source.md
@@ -1,30 +1,31 @@
---
title: Source
sidebar_position: 3
-description: Comprehensive guide to install the OpenBB Terminal and SDK from source.
+description:
+ Comprehensive guide to install the OpenBB Terminal and SDK from source.
The guide covers the installation process for Windows, macOS, and Linux systems
and covers various software installations including Miniconda, Git, Microsoft C++
Build Tools, Rosetta2, LibOMP, VcXsrv, and GTK toolchains. Instructions for environment
setup and package management through Conda and Poetry are also included, along with
troubleshooting tips and community support.
keywords:
-- Installation
-- Miniconda
-- Git
-- Microsoft C++ Build Tools
-- Rosetta2
-- LibOMP
-- VcXsrv
-- GTK toolchains
-- Conda
-- Poetry
-- Environment setup
-- Python package management
-- Troubleshooting
-- Community support
-- Linux
-- MacOS
-- Windows
+ - Installation
+ - Miniconda
+ - Git
+ - Microsoft C++ Build Tools
+ - Rosetta2
+ - LibOMP
+ - VcXsrv
+ - GTK toolchains
+ - Conda
+ - Poetry
+ - Environment setup
+ - Python package management
+ - Troubleshooting
+ - Community support
+ - Linux
+ - MacOS
+ - Windows
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -34,12 +35,13 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
:::warning
-The instructons on this page are for installing the OpenBB Terminal from the source code, which uses a legacy version of the Python SDK. If you do not wish to install the OpenBB Terminal application, please refer to the installation instructions [here](/platform/installation)
+The instructons on this page are for installing the OpenBB Terminal from the source code, which uses a legacy version of the Python SDK. If you do not wish to install the OpenBB Terminal application, please refer to the installation instructions [here](/platform/installation)
:::
This section provides steps to install the OpenBB Terminal and SDK from source. This installation type supports Windows, macOS and Linux systems. **Before starting the installation process, make sure the following pieces of software are installed.**
-
Rosetta Installation Instructions (Apple Sillicon users only)
1. Press ⌘ (Command) + SPACE to open spotlight search, and type "Terminal" and hit Return (⏎). 2. Copy and paste the following code in the Terminal and hit ENTER (⏎): - ```console - softwareupdate --install-rosetta - ``` +```console +softwareupdate --install-rosetta +``` 3. This will start up the Rosetta installation process and you will receive a message regarding the Licence Agreement. Type `A` and hit Return (⏎). 4. After the installation process has finished, you can proceed by clicking on the "Mac M1 Installer" button. @@ -66,13 +69,13 @@ Step by step instructions: 1. Download the PKG file from the links above. 2. Launch the PKG installer by double-clicking on it. -
+
3. Follow the Installer prompt. You will be asked to enter your system password.
-
+
4. This process installs the application into the `/Application/OpenBB Terminal` folder.
-
+
5. Launch the application by double-clicking on the `OpenBB Terminal` application. If everything was successful you should see a screen like the one below:
diff --git a/website/content/terminal/installation/source.md b/website/content/terminal/installation/source.md
index dbf563d32a5d..df487282ebb0 100644
--- a/website/content/terminal/installation/source.md
+++ b/website/content/terminal/installation/source.md
@@ -1,30 +1,31 @@
---
title: Source
sidebar_position: 3
-description: Comprehensive guide to install the OpenBB Terminal and SDK from source.
+description:
+ Comprehensive guide to install the OpenBB Terminal and SDK from source.
The guide covers the installation process for Windows, macOS, and Linux systems
and covers various software installations including Miniconda, Git, Microsoft C++
Build Tools, Rosetta2, LibOMP, VcXsrv, and GTK toolchains. Instructions for environment
setup and package management through Conda and Poetry are also included, along with
troubleshooting tips and community support.
keywords:
-- Installation
-- Miniconda
-- Git
-- Microsoft C++ Build Tools
-- Rosetta2
-- LibOMP
-- VcXsrv
-- GTK toolchains
-- Conda
-- Poetry
-- Environment setup
-- Python package management
-- Troubleshooting
-- Community support
-- Linux
-- MacOS
-- Windows
+ - Installation
+ - Miniconda
+ - Git
+ - Microsoft C++ Build Tools
+ - Rosetta2
+ - LibOMP
+ - VcXsrv
+ - GTK toolchains
+ - Conda
+ - Poetry
+ - Environment setup
+ - Python package management
+ - Troubleshooting
+ - Community support
+ - Linux
+ - MacOS
+ - Windows
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
@@ -34,12 +35,13 @@ import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
:::warning
-The instructons on this page are for installing the OpenBB Terminal from the source code, which uses a legacy version of the Python SDK. If you do not wish to install the OpenBB Terminal application, please refer to the installation instructions [here](/platform/installation)
+The instructons on this page are for installing the OpenBB Terminal from the source code, which uses a legacy version of the Python SDK. If you do not wish to install the OpenBB Terminal application, please refer to the installation instructions [here](/platform/installation)
:::
This section provides steps to install the OpenBB Terminal and SDK from source. This installation type supports Windows, macOS and Linux systems. **Before starting the installation process, make sure the following pieces of software are installed.**
-Miniconda
+
+
-Miniconda
Miniconda is a Python environment and package manager. It is required for installing certain dependencies. Go [here](https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links) to find the download for your operating system or use the links below: @@ -70,7 +72,8 @@ conda update -n base -c conda-forge condaGit
+
+
-Git
Check to verify if Git is installed by running the following command: @@ -94,7 +97,8 @@ Or follow the instructions [here](https://git-scm.com/book/en/v2/Getting-StartedMicrosoft C++ Build Tools (Windows only)
+
+
-Microsoft C++ Build Tools (Windows only)
Use the instructions [here](https://visualstudio.microsoft.com/visual-cpp-build-tools/) to install or update Microsoft C++ Build Tools. @@ -102,19 +106,21 @@ Use the instructions [here](https://visualstudio.microsoft.com/visual-cpp-build-  -Rosetta2 (Apple Silicon only)
+
+
-Rosetta2 (Apple Silicon only)
Install Rosetta from the terminal with: + ```shell softwareupdate --install-rosetta ```LibOMP (Apple Silicon only)
+
+
-LibOMP (Apple Silicon only)
Apple Silicon does not ship `libomp` by default. It will need to be installed manually for some features of the ML toolkit to work. The `libomp` library can be installed from [homebrew](https://brew.sh/). @@ -140,7 +146,8 @@ brew install libompVcXsrv (Windows Subsystem for Linux only)
+
+
-VcXsrv (Windows Subsystem for Linux only)
Since a WSL installation is headless by default (i.e., there is only access to a terminal running a Linux distribution) there are additional steps required to display visualizations. A more detailed tutorial is found, [here](https://medium.com/@shaoyenyu/make-matplotlib-works-correctly-with-x-server-in-wsl2-9d9928b4e36a). @@ -166,12 +173,13 @@ Alternatives to `VcXsrv` include:GTK toolchains (Linux only)
+
+
GTK toolchains (Linux only)
GTK is a window extension that is used to display interactive charts and tables. The library responsible for interactive charts and tables (`pywry`) requires certain dependencies, based on the Linux distribution, to be installed first.
-
Debian-based / Ubuntu / Mint
+Debian-based / Ubuntu / Mint
```shell sudo apt install libwebkit2gtk-4.0-dev @@ -180,7 +188,7 @@ sudo apt install libwebkit2gtk-4.0-dev
-
Arch Linux / Manjaro
+Arch Linux / Manjaro
```shell sudo pacman -S webkit2gtk @@ -189,7 +197,7 @@ sudo pacman -S webkit2gtk
-
Fedora
+Fedora
```shell sudo dnf install gtk3-devel webkit2gtk3-devel @@ -224,7 +232,7 @@ conda env create -n obb --file build/conda/conda-3-9-env.yaml ``` :::note -Additional `YAML` files provide support for Python versions 3.8 and 3.10. Substitute the `9`, in the command above, with the desired version. +Additional `YAML` files provide support for Python versions 3.8 and 3.10. Substitute the `9`, in the command above, with the desired version. ::: After the obb environment is created, activate it by entering: @@ -259,8 +267,11 @@ Install the remaining dependencies and the terminal through Poetry, a package ma ```shell poetry install -E all ``` + :::info -Read about Conda, Poetry and Python package management
+ +
+
Read about Conda, Poetry and Python package management
For the best user experience we advise using `conda` and `poetry` for environment setup and dependency management. Conda ships binaries for packages like `numpy` so these dependencies are not built from source locally by `pip`. Poetry solves the dependency tree in a way that the dependencies of dependencies of dependencies use versions that are compatible with each other. diff --git a/website/content/terminal/installation/windows.md b/website/content/terminal/installation/windows.md index 0910c1748700..3d53f1a3671f 100644 --- a/website/content/terminal/installation/windows.md +++ b/website/content/terminal/installation/windows.md @@ -1,15 +1,16 @@ --- title: Windows sidebar_position: 1 -description: Learn how to install the OpenBB Terminal on Windows, understand its minimum +description: + Learn how to install the OpenBB Terminal on Windows, understand its minimum requirements, and follow the step-by-step instructions to ensure successful installation. keywords: -- OpenBB Terminal installation -- Windows installation guide -- Windows OpenBB Terminal -- Download OpenBB Terminal -- Install OpenBB Terminal -- OpenBB Terminal requirements + - OpenBB Terminal installation + - Windows installation guide + - Windows OpenBB Terminal + - Download OpenBB Terminal + - Install OpenBB Terminal + - OpenBB Terminal requirements --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -22,7 +23,8 @@ This section provides you with the installation file as well as the guide to insMinimum Requirements
+
+
Minimum Requirements
- Windows 10 or newer - Modern CPU (Intel or AMD processor made in the last 5 years) diff --git a/website/content/terminal/reference/alt/oss/rossidx.md b/website/content/terminal/reference/alt/oss/rossidx.md index 1847c8e61395..113cd2bafc77 100644 --- a/website/content/terminal/reference/alt/oss/rossidx.md +++ b/website/content/terminal/reference/alt/oss/rossidx.md @@ -1,30 +1,31 @@ --- title: rossidx -description: This page provides detailed instructions on how to use the rossidx command +description: + This page provides detailed instructions on how to use the rossidx command in Python to sort and display information about startups from the Ross Index. Users can sort by various criteria (e.g. GitHub Stars, Company, Country), display charts, and set the chart type to 'stars' or 'forks'. keywords: -- rossidx -- startups -- chart -- stars -- forks -- sorting -- growth chart -- GitHub -- company -- country -- city -- founded -- raised money + - rossidx + - startups + - chart + - stars + - forks + - sorting + - growth chart + - GitHub + - company + - country + - city + - founded + - raised money --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
-
Instructions
+Instructions
Go to: https://www.alphavantage.co/support/#api-key @@ -95,7 +94,7 @@ Fill out the form, pass Captcha, and click on, "GET FREE API KEY". The issued ke > Binance cryptocurrency exchange - We operate the worlds biggest bitcoin exchange and altcoin crypto exchange in the world by volume
-
Instructions
+Instructions
Go to: https://www.binance.com/en/support/faq/how-to-create-api-360002502072 @@ -114,9 +113,9 @@ These instructions should provide clear guidance for obtaining an API Key. Enter > Bitquery is an API-first product company dedicated to power and solve blockchain data problems using the ground truth of on-chain data.
-
Instructions
+Instructions
-Go to: https://bitquery.io/< +Go to: [https://bitquery.io/](https://bitquery.io/)  @@ -141,17 +140,17 @@ Enter this API key into the OpenBB Terminal by typing: > BizToc is the one-stop business and finance news hub, encapsulating the top 200 US news providers in real time.
-
Instructions
+Instructions
-The BizToc API is hosted on RapidAPI. To set up, go to: https://rapidapi.com/thma/api/biztoc. +The BizToc API is hosted on RapidAPI. To set up, go to: https://rapidapi.com/thma/api/biztoc.  -In the top right, select "Sign Up". After answering some questions, you will be prompted to select one of their plans. +In the top right, select "Sign Up". After answering some questions, you will be prompted to select one of their plans.  -After signing up, navigate back to https://rapidapi.com/thma/api/biztoc. If you are logged in, you will see a header called X-RapidAPI-Key. +After signing up, navigate back to https://rapidapi.com/thma/api/biztoc. If you are logged in, you will see a header called X-RapidAPI-Key.  @@ -168,7 +167,7 @@ Copy the key to the clipboard, and enter this key into the OpenBB Terminal with: > CoinMarketCap is the world's most-referenced price-tracking website for cryptoassets in the rapidly growing cryptocurrency space. Its mission is to make crypto discoverable and efficient globally by empowering retail users with unbiased, high quality and accurate information for drawing their own informed conclusions.
-
Instructions
+Instructions
Go to: https://coinmarketcap.com/api @@ -195,7 +194,7 @@ Enter the API key into the OpenBB Terminal by typing: > Coinbase is a secure online platform for buying, selling, transferring, and storing cryptocurrency.
-
Instructions
+Instructions
Go to: https://help.coinbase.com/en/exchange/managing-my-account/how-to-create-an-api-key @@ -214,7 +213,7 @@ Follow the instructions to obtain the credentials for the specific account. Ente > Coinglass is a cryptocurrency futures trading & information platform,where you can find the Bitcoin Liquidations ,Bitcoin open interest, Grayscale Bitcoin Trust，Bitcoin longs vs shorts ratio and actively compare funding rates for crypto futures.Above all the quantities are shown as per their respective contract value.
-
Instructions
+Instructions
Go to: https://www.coinglass.com/ @@ -237,7 +236,7 @@ With the account created, find the assigned API key within the account profile p > CryptoPanic is a news aggregator platform indicating impact on price and market for traders and cryptocurrency enthusiasts.
-
Instructions
+Instructions
Go to: https://cryptopanic.com/developers/api/ @@ -260,7 +259,7 @@ Enter that value in the OpenBB Terminal by typing: > Databento eliminates tens of thousands of dollars in upfront expenses per dataset without sacrificing data integrity. We give you the flexibility to pick up real-time full exchange feeds and terabytes of historical data, whenever you need it.
-
Instructions
+Instructions
Go to: https://docs.databento.com/getting-started @@ -283,7 +282,7 @@ Enter this into the terminal with: > DEGIRO is Europe's fastest growing online stock broker. DEGIRO distinguishes itself from its competitors by offering extremely low trading commissions.
-
Instructions
+Instructions
Go to: https://www.degiro.com/ @@ -304,7 +303,7 @@ Instructions for setting up 2FA authorization are [here](https://github.com/Chav > Historical End of Day, Intraday, and Live prices API, with Fundamental Financial data API for more than 120000 stocks, ETFs and funds all over the world.
-
Instructions
+Instructions
Go to: https://eodhistoricaldata.com/r/?ref=869U7F4J @@ -331,7 +330,7 @@ Enter this string into the OpenBB Terminal by typing: > With the sole mission of democratizing financial data, we are proud to offer a FREE realtime API for stocks, forex and cryptocurrency.
-
Instructions
+Instructions
Go to: https://finnhub.io/ @@ -358,7 +357,7 @@ Add this key to the OpenBB Terminal by entering: > Enhance your application with our data that goes up to 30 years back in history. Earnings calendar, financial statements, multiple exchanges and more!
-
Instructions
+Instructions
Go to: https://site.financialmodelingprep.com/developer/docs @@ -385,7 +384,7 @@ Enter the key into the OpenBB Terminal with: > FRED is the trusted source for economic data since 1991. Download, graph, and track 819,000 US and international time series from 110 sources.
-
Instructions
+Instructions
Go to: https://fred.stlouisfed.org @@ -416,7 +415,7 @@ Enter the API key into the OpenBB Terminal with: > GitHub is where over 100 million developers shape the future of software.
-
Instructions
+Instructions
Go to: https://github.com @@ -443,7 +442,7 @@ After creating the app, the key will be issued. Enter this token into the OpenBB > Glassnode makes blockchain data accessible for everyone. We source and carefully dissect on-chain data, to deliver contextualized and actionable insights.
-
Instructions
+Instructions
Go to: https://studio.glassnode.com @@ -470,7 +469,7 @@ Enter this key in the OpenBB terminal with: > Intrinio is more than a financial data API provider – we're a real time data partner. That means we're your guide to every step of the financial data.
-
Instructions
+Instructions
Go to: https://intrinio.com/starter-plan @@ -489,7 +488,7 @@ An API key will be issued with a subscription. Find the token value within the a > Gain an edge over the crypto market with professional grade data, tools, and research.
-
Instructions
+Instructions
Go to: https://messari.io @@ -516,7 +515,7 @@ Copy the API key and add it to the OpenBB Terminal by entering: > News API is a simple, easy-to-use REST API that returns JSON search results for current and historic news articles published by over 80,000 worldwide sources.
-
Instructions
+Instructions
Go to: https://newsapi.org @@ -543,7 +542,7 @@ Add this API key into the OpenBB Terminal by entering: > OANDA's Currency Converter allows you to check the latest foreign exchange average bid/ask rates and convert all major world currencies.
-
-
### OpenAI
> An API for accessing new AI models developed by OpenAI.
Instructions
+Instructions
Go to: https://developer.oanda.com @@ -561,13 +560,12 @@ Upon completion of the account setup, enter the credentials into the OpenBB Term
-
-
-
-
### Polygon
> Live & historical data for US stocks for all 19 exchanges. Instant access to real-time and historical stock market data.
Instructions
+Instructions
Go to: https://openai.com/blog/openai-api @@ -576,11 +574,9 @@ Go to: https://openai.com/blog/openai-api Click sign up and create an account. Once done, you will be logged into the home page:  - Click the top right "Personal" button to find the following drop down:  - Click `View API Keys`. This will take you to the api Keys menu. Then click `Create new secret key`:  @@ -592,15 +588,12 @@ Then enter the Secret key credentials into the OpenBB Terminal using the syntax:
-
Instructions
+Instructions
Go to: https://polygon.io @@ -627,7 +620,7 @@ Enter the key into the OpenBB Terminal by typing: > The premier source for financial, economic, and alternative datasets, serving investment professionals. Quandl’s platform is used by over 400,000 people, including analysts from the world’s top hedge funds, asset managers and investment banks.
-
Instructions
+Instructions
Go to: https://www.quandl.com @@ -654,7 +647,7 @@ Enter the key into the OpenBB Terminal with: > Reddit is a network of communities where people can dive into their interests, hobbies and passions.
-
Instructions
+Instructions
Sign in to Reddit, and then go to: https://old.reddit.com/prefs/apps/ @@ -685,7 +678,7 @@ After submitting the form, check for a confirmation email. The credentials will > Robinhood has commission-free investing, and tools to help shape your financial future.
-
Instructions
+Instructions
Go to: https://robinhood.com/us/en @@ -706,7 +699,7 @@ The first login will request 2FA authorization from the device connected to the > We provide tools to help you analyze crypto markets and find data-driven opportunities to optimize your investing.
-
Instructions
+Instructions
Go to: https://app.santiment.net @@ -731,7 +724,7 @@ Add it to the OpenBB Terminal by entering: > Empowering investors to take advantage of alternative data. We track trending tickers on social media and provide alternative data for easy due-diligence & analysis.
-
Instructions
+Instructions
Go to: https://stocksera.pythonanywhere.com @@ -758,7 +751,7 @@ Add the key to the OpenBB Terminal by entering: > Token Terminal is a platform that aggregates financial data on the leading blockchains and decentralized applications.
-
Instructions
+Instructions
Go to: https://tokenterminal.com @@ -785,7 +778,7 @@ Add the key to the OpenBB Terminal by typing: > Tradier, the home of active traders. Our open collaboration platform allows investors to truly customize their trading experience like never before.
-
Instructions
+Instructions
Go to: https://documentation.tradier.com @@ -804,7 +797,7 @@ Click on, "Open Account", to start the sign-up process. After the account has be > From breaking news and entertainment to sports and politics, get the full story with all the live commentary.
-
Upcoming changes to the Twitter API will deprecate the current functionality, it is uncertain if the current features will continue to work.
+Upcoming changes to the Twitter API will deprecate the current functionality, it is uncertain if the current features will continue to work.
 @@ -815,7 +808,7 @@ Click on, "Open Account", to start the sign-up process. After the account has be > Ultima Insights offers tools such as the SEC Filing Analyst, Company news monitoring, Industry event watch, and Earnings Call Roundup for comprehensive investment monitoring. It incorporates daily Wall Street-level Qualitative analysis into OpenBB to keep users updated. The News curation system, powered by GPT + LLMs technology, presents relevant news to investors, often before it appears on platforms like Bloomberg. Ultima aims to provide timely and significant information for its users.
-
Instructions
+Instructions
Go to: https://ultimainsights.ai/openbb @@ -834,7 +827,7 @@ Click on the "Get started" button for Ultima Pro or "Just Want the API Key" to g > Whale Alert continuously collects and analyzes billions of blockchain transactions and related-off chain data from hundreds of reliable sources and converts it into an easy to use standardized format. Our world-class analytics and custom high speed database solutions process transactions the moment they are made, resulting in the largest and most up-to-date blockchain dataset in the world.
-
Instructions
+Instructions
Go to: https://docs.whale-alert.io diff --git a/website/content/terminal/usage/outputs/interactive-charts.md b/website/content/terminal/usage/outputs/interactive-charts.md index 4cb34f49aef8..fd394741db3d 100644 --- a/website/content/terminal/usage/outputs/interactive-charts.md +++ b/website/content/terminal/usage/outputs/interactive-charts.md @@ -1,21 +1,22 @@ --- title: Interactive Charts sidebar_position: 2 -description: Explore how to effectively utilize OpenBB's interactive charts backed +description: + Explore how to effectively utilize OpenBB's interactive charts backed by open source PyWry technology. Understand various capabilities including annotation, color modification, drawing tools, data export, and supplementary data overlay. keywords: -- interactive charts -- PyWry technology -- chart annotation -- drawing tools -- data export -- data overlay -- editing chart title -- Toolbar -- Text Tools -- Draw Tools -- Export Tools + - interactive charts + - PyWry technology + - chart annotation + - drawing tools + - data export + - data overlay + - editing chart title + - Toolbar + - Text Tools + - Draw Tools + - Export Tools --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -32,7 +33,7 @@ import TutorialVideo from '@site/src/components/General/TutorialVideo.tsx'; A common type of output in OpenBB are interactive charts which open in a separated window (due to our [open source PyWry](https://github.com/OpenBB-finance/pywry) technology). The OpenBB charting library provides interactive and highly customizable charts.
-
Charting cheat sheet
+Charting cheat sheet
 @@ -63,7 +64,7 @@ Annotate a chart by clicking on the `Add Text` button, or with the keyboard, `ct  -Enter some text, make any adjustments to the options, then `submit`. Place the crosshairs over the desired data point and click to place the text. +Enter some text, make any adjustments to the options, then `submit`. Place the crosshairs over the desired data point and click to place the text.  @@ -98,7 +99,7 @@ The two buttons at the far-right of the toolbar are for saving the raw data or, ## Overlay -The button, `Overlay chart from CSV`, provides an easy import method for supplementing a chart with additional data. Clicking on the button opens a pop-up dialogue to select the file, column, and whether the overlay should be a bar, candlestick, or line chart. As a candlestick, the CSV file must contain OHLC data. The import window can also be opened with the keyboard, `ctrl-o`. +The button, `Overlay chart from CSV`, provides an easy import method for supplementing a chart with additional data. Clicking on the button opens a pop-up dialogue to select the file, column, and whether the overlay should be a bar, candlestick, or line chart. As a candlestick, the CSV file must contain OHLC data. The import window can also be opened with the keyboard, `ctrl-o`.  diff --git a/website/content/terminal/usage/outputs/interactive-tables.md b/website/content/terminal/usage/outputs/interactive-tables.md index f1258c87ab11..a6c007c556f2 100644 --- a/website/content/terminal/usage/outputs/interactive-tables.md +++ b/website/content/terminal/usage/outputs/interactive-tables.md @@ -1,22 +1,23 @@ --- title: Interactive Tables sidebar_position: 1 -description: Learn how to navigate and utilize OpenBB's interactive tables using our +description: + Learn how to navigate and utilize OpenBB's interactive tables using our open source PyWry technology. Understand how to sort and filter columns, hide or remove columns, select number of rows per page, freeze index and column headers, and export the data. keywords: -- interactive tables -- PyWry technology -- sorting columns -- filtering columns -- hiding columns -- rows per page -- freeze index -- freeze column headers -- exporting data -- data visualization -- customizing tables + - interactive tables + - PyWry technology + - sorting columns + - filtering columns + - hiding columns + - rows per page + - freeze index + - freeze column headers + - exporting data + - data visualization + - customizing tables --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; @@ -33,7 +34,7 @@ import TutorialVideo from '@site/src/components/General/TutorialVideo.tsx'; A common type of output in OpenBB are interactive tables which open in a separated window (utilizing our [open source PyWry](https://github.com/OpenBB-finance/pywry) technology). These provide methods for searching, sorting, filtering, exporting and even adapting settings directly on the table.
-
Table cheat sheet
+Table cheat sheet
 @@ -41,7 +42,7 @@ A common type of output in OpenBB are interactive tables which open in a separat ## Sorting -Columns can be sorted ascending/descending/unsorted, by clicking the controls to the right of each header title. The status of the filtering is shown as a blue indicator. +Columns can be sorted ascending/descending/unsorted, by clicking the controls to the right of each header title. The status of the filtering is shown as a blue indicator.  @@ -57,7 +58,7 @@ The columns can be filtered with min/max values or by letters, depending on the ## Hiding columns -The table will scroll to the right as far as there are columns. Columns can be removed from the table by clicking the icon to the right of the settings button and unchecking it from the list. +The table will scroll to the right as far as there are columns. Columns can be removed from the table by clicking the icon to the right of the settings button and unchecking it from the list.  @@ -75,6 +76,6 @@ Right-click on the index name to enable/disable freezing when scrolling to the r ## Exporting Data -At the bottom-right corner of the table window, there is a button for exporting the data. To the left, the drop down selection for `Type` can be defined as a CSV, XLSX, or PNG file. Exporting the table as a PNG file will create a screenshot of the table at its current view, and data that is not visible will not be captured. +At the bottom-right corner of the table window, there is a button for exporting the data. To the left, the drop down selection for `Type` can be defined as a CSV, XLSX, or PNG file. Exporting the table as a PNG file will create a screenshot of the table at its current view, and data that is not visible will not be captured.  diff --git a/website/docusaurus.config.js b/website/docusaurus.config.js deleted file mode 100644 index 066d214099de..000000000000 --- a/website/docusaurus.config.js +++ /dev/null @@ -1,129 +0,0 @@ -// @ts-check -// Note: type annotations allow type checking and IDEs autocompletion - -const lightCodeTheme = require("prism-react-renderer/themes/vsLight"); -const darkCodeTheme = require("prism-react-renderer/themes/vsDark"); -const math = require("remark-math"); -const katex = require("rehype-katex"); - -/** @type {import('@docusaurus/types').Config} */ -const config = { - title: "OpenBB Docs", - tagline: "OpenBB Docs", - url: "https://docs.openbb.co", // Your website URL - baseUrl: "/", - projectName: "OpenBBTerminal", - organizationName: "OpenBB-finance", - trailingSlash: false, - onBrokenLinks: "warn", - onBrokenMarkdownLinks: "warn", - favicon: "img/favicon.ico", - - // GitHub pages deployment config. - // If you aren't using GitHub pages, you don't need these. - - // Even if you don't use internalization, you can use this field to set useful - // metadata like html lang. For example, if your site is Chinese, you may want - // to replace "en" with "zh-Hans". - i18n: { - defaultLocale: "en", - locales: ["en"], - }, - plugins: [ - [ - "@docusaurus/plugin-client-redirects", - { - redirects: [ - { - from: "/terminal/menus/forecasting", - to: "/terminal/menus/forecast", - }, - ], - }, - ], - async function twPlugin(context, options) { - return { - name: "docusaurus-tailwindcss", - configurePostCss(postcssOptions) { - // Appends TailwindCSS and AutoPrefixer. - postcssOptions.plugins.push(require("tailwindcss")); - postcssOptions.plugins.push(require("autoprefixer")); - return postcssOptions; - }, - }; - }, - /*[ - "@docusaurus/plugin-content-docs", - { - id: "sdk", - path: "content/sdk", - routeBasePath: "sdk", - editUrl: - "https://github.com/OpenBB-finance/OpenBBTerminal/edit/main/website/", - sidebarPath: require.resolve("./sidebars.js"), - }, - ], - [ - "@docusaurus/plugin-content-docs", - { - id: "bot", - path: "content/bot", - routeBasePath: "bot", - editUrl: - "https://github.com/OpenBB-finance/OpenBBTerminal/edit/main/website/", - sidebarPath: require.resolve("./sidebars.js"), - }, - ],*/ - ], - presets: [ - [ - "classic", - /** @type {import('@docusaurus/preset-classic').Options} */ - ({ - docs: { - sidebarPath: require.resolve("./sidebars.js"), - editUrl: "https://github.com/OpenBB-finance/OpenBBTerminal/edit/main/website/", - showLastUpdateTime: true, - showLastUpdateAuthor: true, - routeBasePath: "/", - path: "content", - remarkPlugins: [math], - rehypePlugins: [katex], - }, - theme: { - customCss: require.resolve("./src/css/custom.css"), - }, - }), - ], - ], - - themeConfig: - /** @type {import('@docusaurus/preset-classic').ThemeConfig} */ - ({ - image: "img/banner.png", - prism: { - theme: lightCodeTheme, - darkTheme: darkCodeTheme, - }, - // TODO - Jose can you make this so we get lighter color on main view - like bot docs - colorMode: { - defaultMode: "dark", - disableSwitch: false, - respectPrefersColorScheme: false, - }, - algolia: { - appId: "7D1HQ0IXAS", - apiKey: "a2e289977b4b663ed9cf3d4635a438fd", // pragma: allowlist secret - indexName: "openbbterminal", - contextualSearch: false, - }, - }), - stylesheets: [ - { - href: "/katex/katex.min.css", - type: "text/css", - }, - ], -}; - -module.exports = config; diff --git a/website/docusaurus.config.ts b/website/docusaurus.config.ts new file mode 100644 index 000000000000..710387b45188 --- /dev/null +++ b/website/docusaurus.config.ts @@ -0,0 +1,105 @@ +// @ts-check +// Note: type annotations allow type checking and IDEs autocompletion + +import { Options, ThemeConfig } from "@docusaurus/preset-classic"; +import { Config } from "@docusaurus/types"; +import autoprefixer from "autoprefixer"; +import { themes } from "prism-react-renderer"; +import katex from "rehype-katex"; +import math from "remark-math"; +import tailwind from "tailwindcss"; + +export default { + title: "OpenBB Docs", + tagline: "OpenBB Docs", + url: "https://docs.openbb.co", // Your website URL + baseUrl: "/", + projectName: "OpenBBTerminal", + organizationName: "OpenBB-finance", + trailingSlash: false, + onBrokenLinks: "warn", + onBrokenMarkdownLinks: "warn", + favicon: "img/favicon.ico", + + // GitHub pages deployment config. + // If you aren't using GitHub pages, you don't need these. + + // Even if you don't use internalization, you can use this field to set useful + // metadata like html lang. For example, if your site is Chinese, you may want + // to replace "en" with "zh-Hans". + i18n: { + defaultLocale: "en", + locales: ["en"], + }, + plugins: [ + [ + "@docusaurus/plugin-client-redirects", + { + redirects: [ + { + from: "/terminal/menus/forecasting", + to: "/terminal/menus/forecast", + }, + ], + }, + ], + async function twPlugin(context, options) { + return { + name: "docusaurus-tailwindcss", + configurePostCss(postcssOptions) { + // Appends TailwindCSS and AutoPrefixer. + postcssOptions.plugins.push(tailwind); + postcssOptions.plugins.push(autoprefixer); + return postcssOptions; + }, + }; + }, + ], + presets: [ + [ + "classic", + { + docs: { + sidebarPath: "./sidebars.js", + editUrl: + "https://github.com/OpenBB-finance/OpenBBTerminal/edit/main/website/", + showLastUpdateTime: true, + showLastUpdateAuthor: true, + routeBasePath: "/", + path: "content", + remarkPlugins: [math], + rehypePlugins: [katex], + }, + theme: { + customCss: "./src/css/custom.css", + }, + } satisfies Options, + ], + ], + + themeConfig: { + image: "img/banner.png", + prism: { + theme: themes.vsLight, + darkTheme: themes.vsDark, + }, + // TODO - Jose can you make this so we get lighter color on main view - like bot docs + colorMode: { + defaultMode: "dark", + disableSwitch: false, + respectPrefersColorScheme: false, + }, + algolia: { + appId: "7D1HQ0IXAS", + apiKey: "a2e289977b4b663ed9cf3d4635a438fd", // pragma: allowlist secret + indexName: "openbbterminal", + contextualSearch: false, + }, + } satisfies ThemeConfig, + stylesheets: [ + { + href: "/katex/katex.min.css", + type: "text/css", + }, + ], +} satisfies Config; diff --git a/website/package-lock.json b/website/package-lock.json index 4c4d95bec466..ddcb2300e626 100644 --- a/website/package-lock.json +++ b/website/package-lock.json @@ -8,39 +8,41 @@ "name": "docs", "version": "1.0.0", "dependencies": { - "@docusaurus/core": "^2.4.3", - "@docusaurus/plugin-client-redirects": "^2.4.3", - "@docusaurus/plugin-content-docs": "^2.4.3", - "@docusaurus/preset-classic": "^2.4.3", - "@mdx-js/react": "^1.6.22", - "@radix-ui/react-dialog": "^1.0.2", - "@radix-ui/react-popover": "^1.0.3", - "@radix-ui/react-tooltip": "^1.0.5", - "axios": "^1.6.2", - "clsx": "^1.2.1", + "@docusaurus/core": "^3.3.2", + "@docusaurus/plugin-client-redirects": "^3.3.2", + "@docusaurus/plugin-content-docs": "^3.3.2", + "@docusaurus/preset-classic": "^3.3.2", + "@radix-ui/react-dialog": "^1.0.5", + "@radix-ui/react-popover": "^1.0.7", + "@radix-ui/react-tooltip": "^1.0.7", + "axios": "^1.6.8", + "clsx": "^2.1.1", "fuse.js": "^6.6.2", - "hast-util-is-element": "^1.1.0", - "posthog-js": "^1.53.4", - "prism-react-renderer": "^1.3.5", - "react": "^17.0.2", - "react-dom": "^17.0.2", - "react-player": "^2.14.1", - "rehype-katex": "^5.0.0", - "remark-math": "^3.0.1", - "tailwindcss-radix": "^2.7.0", + "hast-util-is-element": "^3.0.0", + "posthog-js": "^1.131.3", + "prism-react-renderer": "^2.3.1", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-player": "^2.16.0", + "rehype-katex": "^7.0.0", + "remark-math": "^6.0.0", + "tailwindcss-radix": "^3.0.3", "typescript-toggle": "^1.1.0" }, "devDependencies": { - "@docusaurus/module-type-aliases": "^2.4.3", - "@tailwindcss/typography": "^0.5.8", - "@tsconfig/docusaurus": "^1.0.5", - "autoprefixer": "^10.4.13", - "postcss": "^8.4.18", - "tailwindcss": "^3.2.3", - "typescript": "^4.7.4" + "@docusaurus/module-type-aliases": "^3.3.2", + "@docusaurus/tsconfig": "^3.3.2", + "@mdx-js/loader": "^3.0.1", + "@mdx-js/react": "^3.0.1", + "@tailwindcss/typography": "^0.5.13", + "autoprefixer": "^10.4.19", + "postcss": "^8.4.38", + "remark-gfm": "^4.0.0", + "tailwindcss": "^3.4.3", + "typescript": "^5.4.5" }, "engines": { - "node": ">=16.14" + "node": ">=18.17" } }, "node_modules/@algolia/autocomplete-core": { @@ -85,74 +87,74 @@ } }, "node_modules/@algolia/cache-browser-local-storage": { - "version": "4.20.0", - "resolved": 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engines: {node: '>= 14'} - dev: true - - /yocto-queue@0.1.0: - resolution: {integrity: sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==} - engines: {node: '>=10'} - dev: false - - /zwitch@1.0.5: - resolution: {integrity: sha512-V50KMwwzqJV0NpZIZFwfOD5/lyny3WlSzRiXgA0G7VUnRlqttta1L6UQIHzd6EuBY/cHGfwTIck7w1yH6Q5zUw==} - dev: false diff --git a/website/sidebars.js b/website/sidebars.js index 363ca91127ee..17d5b5dccbc3 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -12,7 +12,7 @@ // @ts-check /** @type {import('@docusaurus/plugin-content-docs').SidebarsConfig} */ -const sidebars = { +export default { // By default, Docusaurus generates a sidebar from the docs folder structure tutorialSidebar: [ { @@ -34,8 +34,7 @@ const sidebars = { { type: "category", label: "OpenBB Platform", - items: [ - { type: "autogenerated", dirName: "platform" }], + items: [{ type: "autogenerated", dirName: "platform" }], }, { type: "category", @@ -87,5 +86,3 @@ const sidebars = { ], */ }; - -module.exports = sidebars; diff --git a/website/src/pages/index.tsx b/website/src/pages/index.tsx index 43a5f48836ba..00b77cfa9ff4 100644 --- a/website/src/pages/index.tsx +++ b/website/src/pages/index.tsx @@ -1,11 +1,9 @@ import Link from "@docusaurus/Link"; import Layout from "@theme/Layout"; import clsx from "clsx"; -import React from "react"; import ChevronRightIcon from "../components/Icons/ChevronRight"; import DarkBlueRadialGradient from "../components/Icons/RadialGradients/DarkBlue"; import RubyRedRadialGradient from "../components/Icons/RadialGradients/RubyRed"; -import CloseIcon from "../components/Icons/Close" export default function Home(): JSX.Element { return ( @@ -19,7 +17,8 @@ export default function Home(): JSX.Element { OpenBB Documentation- All the documentation for the tools you need for your investment research. + All the documentation for the tools you need for your investment + research.
@@ -34,11 +33,12 @@ export default function Home(): JSX.Element {
OpenBB Terminal Pro
{imageUrl && (
- ![]()
{
- setImageUrl(null);
- }}
- src={imageUrl}
- alt="example"
- />
- )}
+ ![]()
{
+ setImageUrl(null);
+ }}
+ src={imageUrl}
+ alt="example"
+ />
+ )}
);
}
diff --git a/website/src/theme/ColorModeToggle/index.js b/website/src/theme/ColorModeToggle/index.js
index 139f91c589df..6011b4dea49d 100644
--- a/website/src/theme/ColorModeToggle/index.js
+++ b/website/src/theme/ColorModeToggle/index.js
@@ -1,15 +1,15 @@
-import React, { useEffect } from "react";
-import clsx from "clsx";
-import useIsBrowser from "@docusaurus/useIsBrowser";
+import Link from "@docusaurus/Link";
import { translate } from "@docusaurus/Translate";
-import * as PopoverPrimitive from "@radix-ui/react-popover";
-import SunIcon from "@site/src/components/Icons/Sun";
-import MoonIcon from "@site/src/components/Icons/Moon";
import { useLocation } from "@docusaurus/router";
+import useIsBrowser from "@docusaurus/useIsBrowser";
+import * as PopoverPrimitive from "@radix-ui/react-popover";
import DiscordIcon from "@site/src/components/Icons/Discord";
+import MoonIcon from "@site/src/components/Icons/Moon";
+import SunIcon from "@site/src/components/Icons/Sun";
import TelegramIcon from "@site/src/components/Icons/Telegram";
-import Link from "@docusaurus/Link";
-import { useIFrameContext } from "../Root";
+import clsx from "clsx";
+import React, { useEffect } from "react";
+import { useIFrameContext } from "../Root.tsx";
function ColorModeToggle({ className, value, onChange }) {
const { isIFrame } = useIFrameContext();
const { pathname } = useLocation();
@@ -115,7 +115,7 @@ function ColorModeToggle({ className, value, onChange }) {
})}
type="button"
onClick={() => {
- onChange("light")
+ onChange("light");
window.location.reload();
}}
disabled={!isBrowser}
@@ -132,7 +132,7 @@ function ColorModeToggle({ className, value, onChange }) {
})}
type="button"
onClick={() => {
- onChange("dark")
+ onChange("dark");
window.location.reload();
}}
disabled={!isBrowser}
diff --git a/website/src/theme/DocSidebarItem/Category/index.js b/website/src/theme/DocSidebarItem/Category/index.js
index 0d8c90879431..4ddec60bf68c 100644
--- a/website/src/theme/DocSidebarItem/Category/index.js
+++ b/website/src/theme/DocSidebarItem/Category/index.js
@@ -9,7 +9,7 @@ import {
useThemeConfig,
} from "@docusaurus/theme-common";
import {
- findFirstCategoryLink,
+ // findFirstCategoryLink,
isActiveSidebarItem,
isSamePath,
useDocSidebarItemsExpandedState,
@@ -18,7 +18,7 @@ import useIsBrowser from "@docusaurus/useIsBrowser";
import DocSidebarItems from "@theme/DocSidebarItems";
import clsx from "clsx";
import React, { useEffect, useMemo } from "react";
-import { useIFrameContext } from "../../Root";
+import { useIFrameContext } from "../../Root.tsx";
// If we navigate to a category and it becomes active, it should automatically
// expand itself
function useAutoExpandActiveCategory({ isActive, collapsed, updateCollapsed }) {
@@ -49,7 +49,7 @@ function useCategoryHrefWithSSRFallback(item, href) {
if (isBrowser || !item.collapsible) {
return undefined;
}
- return findFirstCategoryLink(item);
+ // return findFirstCategoryLink(item);
}, [item, isBrowser]);
}
function CollapseButton({ categoryLabel, onClick }) {
@@ -126,19 +126,19 @@ export default function DocSidebarItemCategory({
const dontShowLink =
isIFrame && ["OpenBB Terminal", "OpenBB SDK", "OpenBB Bot"].includes(label);
- const location = useLocation();
- const isProPage = location.pathname.startsWith("/pro");
- const isExcelPage = location.pathname.startsWith("/excel");
+ const location = useLocation();
+ const isProPage = location.pathname.startsWith("/pro");
+ const isExcelPage = location.pathname.startsWith("/excel");
- // Hide the OpenBB Terminal Pro section if we're not on a /pro or /excel page
- if (item.customProps?.hiddenByDefault && !(isProPage || isExcelPage)) {
- return null;
- }
+ // Hide the OpenBB Terminal Pro section if we're not on a /pro or /excel page
+ if (item.customProps?.hiddenByDefault && !(isProPage || isExcelPage)) {
+ return null;
+ }
- // Temporary, remove to show Excel tab
- if (item.customProps?.onlyDirectAccess && !isExcelPage) {
- return null;
- }
+ // Temporary, remove to show Excel tab
+ if (item.customProps?.onlyDirectAccess && !isExcelPage) {
+ return null;
+ }
return (
shouldHideItem(childItem, productPath)
@@ -48,7 +46,11 @@ export default function DocSidebarItem({ item, ...props }) {
if ((isPro || isExcel) && !checkIfAnyChildIsProExcel(item)) {
return null;
- } else if (!(isPro || isExcel) && item.href?.startsWith("/pro") && item.href?.startsWith("/excel")) {
+ } else if (
+ !(isPro || isExcel) &&
+ item.href?.startsWith("/pro") &&
+ item.href?.startsWith("/excel")
+ ) {
return null;
}
diff --git a/website/src/theme/Footer/index.js b/website/src/theme/Footer/index.js
index 1474108bdc0b..9d400f15b8a5 100644
--- a/website/src/theme/Footer/index.js
+++ b/website/src/theme/Footer/index.js
@@ -1,17 +1,17 @@
-import React, { useEffect, useState } from "react";
import Link from "@docusaurus/Link";
-import LetteringLogo from "@site/src/components/Icons/LetteringLogo";
-import StarIcon from "@site/src/components/Icons/Star";
+import ChevronRightIcon from "@site/src/components/Icons/ChevronRight";
+import DiscordIcon from "@site/src/components/Icons/Discord";
import GithubIcon from "@site/src/components/Icons/Github";
+import LetteringLogo from "@site/src/components/Icons/LetteringLogo";
import LinkedinIcon from "@site/src/components/Icons/Linkedin";
-import TwitterIcon from "@site/src/components/Icons/Twitter";
-import TiktokIcon from "@site/src/components/Icons/Tiktok";
import RedditIcon from "@site/src/components/Icons/Reddit";
-import DiscordIcon from "@site/src/components/Icons/Discord";
+import StarIcon from "@site/src/components/Icons/Star";
+import TiktokIcon from "@site/src/components/Icons/Tiktok";
+import TwitterIcon from "@site/src/components/Icons/Twitter";
import YoutubeIcon from "@site/src/components/Icons/Youtube";
-import ChevronRightIcon from "@site/src/components/Icons/ChevronRight";
import clsx from "clsx";
-import { useIFrameContext } from "../Root";
+import React, { useEffect, useState } from "react";
+import { useIFrameContext } from "../Root.tsx";
const nFormatter = (num, digits) => {
const si = [
{ value: 1, symbol: "" },
diff --git a/website/src/theme/Navbar/Content/index.js b/website/src/theme/Navbar/Content/index.js
index 85f85f7f9116..bf5763341a9b 100644
--- a/website/src/theme/Navbar/Content/index.js
+++ b/website/src/theme/Navbar/Content/index.js
@@ -1,20 +1,20 @@
-import React from "react";
import { useThemeConfig } from "@docusaurus/theme-common";
import {
splitNavbarItems,
useNavbarMobileSidebar,
} from "@docusaurus/theme-common/internal";
-import NavbarItem from "@theme/NavbarItem";
import NavbarColorModeToggle from "@theme/Navbar/ColorModeToggle";
-import SearchBar from "@theme/SearchBar";
-import NavbarMobileSidebarToggle from "@theme/Navbar/MobileSidebar/Toggle";
import NavbarLogo from "@theme/Navbar/Logo";
+import NavbarMobileSidebarToggle from "@theme/Navbar/MobileSidebar/Toggle";
import NavbarSearch from "@theme/Navbar/Search";
-import styles from "./styles.module.css";
+import NavbarItem from "@theme/NavbarItem";
+import SearchBar from "@theme/SearchBar";
+
function useNavbarItems() {
// TODO temporary casting until ThemeConfig type is improved
return useThemeConfig().navbar.items;
}
+
function NavbarItems({ items }) {
return (
<>
@@ -24,16 +24,18 @@ function NavbarItems({ items }) {
);
}
+
function NavbarContentLayout({ left, right }) {
return (
- {() => isOpen &&
+ {() =>
+ isOpen &&
DocSearchModal &&
searchContainer.current &&
createPortal(
@@ -187,11 +195,13 @@ function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
translations={translations.modal}
/>,
searchContainer.current
- )}
+ )
+ }
);
}
+
export default function SearchBar() {
const { siteConfig } = useDocusaurusContext();
const { isIFrame } = useIFrameContext();
diff --git a/website/tailwind.config.js b/website/tailwind.config.ts
similarity index 91%
rename from website/tailwind.config.js
rename to website/tailwind.config.ts
index 478fd44fe1fb..8852d95a0a7e 100644
--- a/website/tailwind.config.js
+++ b/website/tailwind.config.ts
@@ -1,3 +1,7 @@
+import typographyPlugin from "@tailwindcss/typography";
+import { Config } from "tailwindcss";
+import radixPlugin from "tailwindcss-radix";
+
const disabledCss = {
"code::before": false,
"code::after": false,
@@ -6,11 +10,9 @@ const disabledCss = {
pre: false,
code: false,
"pre code": false,
- "code::before": false,
- "code::after": false,
};
-module.exports = {
+export default {
darkMode: ["class", '[data-theme="dark"]'],
content: ["./src/**/*.{js,jsx,ts,tsx}", "./content/**/*.{mdx,md}"],
theme: {
@@ -68,5 +70,5 @@ module.exports = {
},
},
},
- plugins: [require("@tailwindcss/typography"), require("tailwindcss-radix")()],
-};
+ plugins: [typographyPlugin, radixPlugin],
+} satisfies Config;
diff --git a/website/tsconfig.json b/website/tsconfig.json
index 57bbce401d6a..d250afaeddd7 100644
--- a/website/tsconfig.json
+++ b/website/tsconfig.json
@@ -1,5 +1,5 @@
{
- "extends": "@tsconfig/docusaurus/tsconfig.json",
+ "extends": "@docusaurus/tsconfig",
"compilerOptions": {
"baseUrl": "."
}
diff --git a/website/yarn.lock b/website/yarn.lock
deleted file mode 100644
index 3f99c138cd0e..000000000000
--- a/website/yarn.lock
+++ /dev/null
@@ -1,8432 +0,0 @@
-# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
-# yarn lockfile v1
-
-
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- dependencies:
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- "@algolia/autocomplete-shared" "1.9.3"
-
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- resolved "https://registry.npmjs.org/@algolia/autocomplete-plugin-algolia-insights/-/autocomplete-plugin-algolia-insights-1.9.3.tgz"
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- dependencies:
- "@algolia/autocomplete-shared" "1.9.3"
-
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- resolved "https://registry.npmjs.org/@algolia/autocomplete-preset-algolia/-/autocomplete-preset-algolia-1.9.3.tgz"
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- "@algolia/autocomplete-shared" "1.9.3"
-
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-
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-
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- integrity sha512-r3vXyErRCYJ7wg28yvBY5VSoAF8ZvlcW9/BwUzEtUsjvX/DKs24dIkuwjtuprwJJHsbyUbLApepYTR1BN4uHrg==
-
-yocto-queue@^0.1.0:
- version "0.1.0"
- resolved "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz"
- integrity sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==
-
-zwitch@^1.0.0:
- version "1.0.5"
- resolved "https://registry.npmjs.org/zwitch/-/zwitch-1.0.5.tgz"
- integrity sha512-V50KMwwzqJV0NpZIZFwfOD5/lyny3WlSzRiXgA0G7VUnRlqttta1L6UQIHzd6EuBY/cHGfwTIck7w1yH6Q5zUw==
- The OpenBB Terminal Pro is the investment research platform for the 21st century. + The OpenBB Terminal Pro is the investment research platform for + the 21st century.
See more @@ -56,11 +56,12 @@ export default function Home(): JSX.Element { OpenBB Add-In for Excel
- The OpenBB Add-In for Excel allows access to the same data as the OpenBB Terminal Pro, but through Excel. + The OpenBB Add-In for Excel allows access to the same data as + the OpenBB Terminal Pro, but through Excel.
See more @@ -81,11 +82,12 @@ export default function Home(): JSX.Element { OpenBB Platform
- The OpenBB Platform provides a convenient way to access raw financial data from multiple data providers. + The OpenBB Platform provides a convenient way to access raw + financial data from multiple data providers.
See more diff --git a/website/src/theme/CodeBlock/Content/String.js b/website/src/theme/CodeBlock/Content/String.js index c143af0fdb38..d235e110b06c 100644 --- a/website/src/theme/CodeBlock/Content/String.js +++ b/website/src/theme/CodeBlock/Content/String.js @@ -1,20 +1,20 @@ -import React, { useState, useEffect, useRef } from "react"; -import clsx from "clsx"; -import { useThemeConfig, usePrismTheme } from "@docusaurus/theme-common"; +import { usePrismTheme, useThemeConfig } from "@docusaurus/theme-common"; import { + containsLineNumbers, parseCodeBlockTitle, parseLanguage, parseLines, - containsLineNumbers, useCodeWordWrap, } from "@docusaurus/theme-common/internal"; -import Highlight, { defaultProps } from "prism-react-renderer"; -import Line from "@theme/CodeBlock/Line"; +import Container from "@theme/CodeBlock/Container"; import CopyButton from "@theme/CodeBlock/CopyButton"; +import Line from "@theme/CodeBlock/Line"; import WordWrapButton from "@theme/CodeBlock/WordWrapButton"; -import Container from "@theme/CodeBlock/Container"; -import styles from "./styles.module.css"; +import clsx from "clsx"; +import { Highlight } from "prism-react-renderer"; +import { useEffect, useRef, useState } from "react"; import { useLocation } from "react-router-dom"; +import styles from "./styles.module.css"; function getImageUrl(pathname, text) { if (!pathname.startsWith("/bot/")) { @@ -29,7 +29,7 @@ function getImageUrl(pathname, text) { ) { imgname = text.split(" ")[0].toLowerCase().replace("/", ""); } else if (platform == "telegram") { - console.log(pathvalue) + console.log(pathvalue); if (pathvalue.toString() == "etf" || pathvalue.toString() == "screeners") { imgname = text.split(" ")[1].toLowerCase(); } else { @@ -118,7 +118,6 @@ export default function CodeBlockString({ {title &&
{title}
}
{left}
-
+
);
}
+
export default function NavbarContent() {
const mobileSidebar = useNavbarMobileSidebar();
const items = useNavbarItems();
diff --git a/website/src/theme/Navbar/Layout/index.js b/website/src/theme/Navbar/Layout/index.js
index 11006748e35d..8a767c3f6200 100644
--- a/website/src/theme/Navbar/Layout/index.js
+++ b/website/src/theme/Navbar/Layout/index.js
@@ -7,7 +7,7 @@ import {
import NavbarMobileSidebar from "@theme/Navbar/MobileSidebar";
import clsx from "clsx";
import React, { useEffect } from "react";
-import { useIFrameContext } from "../../Root";
+import { useIFrameContext } from "../../Root.tsx";
import styles from "./styles.module.css";
function NavbarBackdrop(props) {
return (
@@ -29,61 +29,55 @@ export default function NavbarLayout({ children }) {
const cleanedPath = pathname.replace(/\/v\d+/, "");
useEffect(() => {
- if (cleanedPath.startsWith("/terminal") ||
- cleanedPath.startsWith("/pro")
- ) {
- if (document.documentElement.getAttribute('data-theme') === 'dark') {
+ if (cleanedPath.startsWith("/terminal") || cleanedPath.startsWith("/pro")) {
+ if (document.documentElement.getAttribute("data-theme") === "dark") {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#669DCB",
+ "#669DCB"
);
} else {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#004A87",
+ "#004A87"
);
}
} else if (
cleanedPath.startsWith("/sdk") ||
cleanedPath.startsWith("/platform")
) {
- if (document.documentElement.getAttribute('data-theme') === 'dark') {
+ if (document.documentElement.getAttribute("data-theme") === "dark") {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#F5B166",
+ "#F5B166"
);
} else {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#511d11",
+ "#511d11"
);
}
- }
- else if (
- cleanedPath.startsWith("/excel")
- ) {
- if (document.documentElement.getAttribute('data-theme') === 'dark') {
+ } else if (cleanedPath.startsWith("/excel")) {
+ if (document.documentElement.getAttribute("data-theme") === "dark") {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#16A34A",
+ "#16A34A"
);
} else {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#14532D",
+ "#14532D"
);
}
- }
- else if (cleanedPath.startsWith("/bot")) {
- if (document.documentElement.getAttribute('data-theme') === 'dark') {
+ } else if (cleanedPath.startsWith("/bot")) {
+ if (document.documentElement.getAttribute("data-theme") === "dark") {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#b186bb",
+ "#b186bb"
);
} else {
document.documentElement.style.setProperty(
"--ifm-color-primary",
- "#3a204f",
+ "#3a204f"
);
}
} else {
@@ -123,7 +117,7 @@ export default function NavbarLayout({ children }) {
},
{
hidden: isIFrame,
- },
+ }
)}
>
{children}
diff --git a/website/src/theme/NotFound.js b/website/src/theme/NotFound.js
index 2e664fb89718..8c66f1b58b89 100644
--- a/website/src/theme/NotFound.js
+++ b/website/src/theme/NotFound.js
@@ -1,8 +1,8 @@
import React from "react";
import Layout from "@theme/Layout";
import Link from "@docusaurus/Link";
-import DarkBlueRadialGradient from "../components/Icons/RadialGradients/DarkBlue";
-import RubyRedRadialGradient from "../components/Icons/RadialGradients/RubyRed";
+import DarkBlueRadialGradient from "../components/Icons/RadialGradients/DarkBlue.tsx";
+import RubyRedRadialGradient from "../components/Icons/RadialGradients/RubyRed.tsx";
import { useIFrameContext } from "@site/src/theme/Root";
export default function NotFound() {
diff --git a/website/src/theme/SearchBar/index.js b/website/src/theme/SearchBar/index.js
index a6fca7218cb5..fef237d929b0 100644
--- a/website/src/theme/SearchBar/index.js
+++ b/website/src/theme/SearchBar/index.js
@@ -1,5 +1,8 @@
-import { DocSearchButton, useDocSearchKeyboardEvents } from "@docsearch/react";
-
+import "@docsearch/css";
+import {
+ DocSearchButton,
+ useDocSearchKeyboardEvents,
+} from "@docsearch/react";
import BrowserOnly from "@docusaurus/BrowserOnly";
import Head from "@docusaurus/Head";
import Link from "@docusaurus/Link";
@@ -12,13 +15,16 @@ import {
} from "@docusaurus/theme-search-algolia/client";
import useDocusaurusContext from "@docusaurus/useDocusaurusContext";
import translations from "@theme/SearchTranslations";
-import React, { useCallback, useMemo, useRef, useState } from "react";
+import { useCallback, useMemo, useRef, useState } from "react";
import { createPortal } from "react-dom";
-import { useIFrameContext } from "../Root";
+import { useIFrameContext } from "../Root.tsx";
+
let DocSearchModal = null;
+
function Hit({ hit, children }) {
return {children};
}
+
function ResultsFooter({ state, onClose }) {
return (
@@ -31,10 +37,12 @@ function ResultsFooter({ state, onClose }) {
);
}
+
function mergeFacetFilters(f1, f2) {
const normalize = (f) => (typeof f === "string" ? [f] : f);
return [...normalize(f1), ...normalize(f2)];
}
+
function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
const location = useLocation();
const { siteMetadata } = useDocusaurusContext();
@@ -43,9 +51,9 @@ function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
const configFacetFilters = props.searchParameters?.facetFilters ?? [];
const facetFilters = contextualSearch
? // Merge contextual search filters with config filters
- mergeFacetFilters(contextualSearchFacetFilters, configFacetFilters)
+ mergeFacetFilters(contextualSearchFacetFilters, configFacetFilters)
: // ... or use config facetFilters
- configFacetFilters;
+ configFacetFilters;
// We let user override default searchParameters if she wants to
const searchParameters = {
...props.searchParameters,
@@ -62,7 +70,7 @@ function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
}
return Promise.all([
import("@docsearch/react/modal"),
- import("@docsearch/react/style"),
+ // import("@docsearch/react/style"),
import("./styles.css"),
]).then(([{ DocSearchModal: Modal }]) => {
DocSearchModal = Modal;
@@ -105,19 +113,18 @@ function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
const transformItems = useRef((items) =>
(props.transformItems
? // Custom transformItems
- props.transformItems(items)
+ props.transformItems(items)
: // Default transformItems
- items.map((item) => ({
- ...item,
- url: processSearchResultUrl(item.url),
- }))).filter((item) => {
- const firstPathSegment = location.pathname.split("/")[1];
- return (
- !firstPathSegment ? true :
- item.url.startsWith(`/${firstPathSegment}/`)
- );
- }
- )
+ items.map((item) => ({
+ ...item,
+ url: processSearchResultUrl(item.url),
+ }))
+ ).filter((item) => {
+ const firstPathSegment = location.pathname.split("/")[1];
+ return !firstPathSegment
+ ? true
+ : item.url.startsWith(`/${firstPathSegment}/`);
+ })
).current;
const resultsFooterComponent = useMemo(
() =>
@@ -166,7 +173,8 @@ function DocSearch({ contextualSearch, externalUrlRegex, ...props }) {
/>
{right}