trading_simulator3_full_market.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"trading_simulator3_full_market.ipynb","provenance":[],"authorship_tag":"ABX9TyO3KoRu5Kg1CMA1CbtTwt5Z"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"6_Xz4h8wkWYa","executionInfo":{"status":"ok","timestamp":1617728478202,"user_tz":420,"elapsed":3102,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"bdccb9cf-0a63-4a26-eaf4-2402c5acf7f0"},"source":["!pip install yfinance"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.59)\n","Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.19.5)\n","Requirement already satisfied: pandas>=0.24 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.1.5)\n","Requirement already satisfied: lxml>=4.5.1 in /usr/local/lib/python3.7/dist-packages (from yfinance) (4.6.3)\n","Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.9)\n","Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.7/dist-packages (from yfinance) (2.23.0)\n","Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2018.9)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2.8.1)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (1.24.3)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (3.0.4)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2.10)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2020.12.5)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24->yfinance) (1.15.0)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"EXiwOEpdkgdy","executionInfo":{"status":"ok","timestamp":1617728478757,"user_tz":420,"elapsed":3627,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}}},"source":["import warnings\n","warnings.filterwarnings('ignore')\n","\n","import yfinance as yf\n","import pandas as pd\n","import numpy as np\n","import altair as alt\n","import datetime\n","import project_functions2 as pf\n","\n","from matplotlib import pyplot as plt\n","from sklearn.linear_model import LinearRegression"],"execution_count":2,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ES1dNJsNlJoJ","executionInfo":{"status":"ok","timestamp":1617728478776,"user_tz":420,"elapsed":3619,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"b7f6085b-fbee-4872-b83d-37498d03fe66"},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":3,"outputs":[{"output_type":"stream","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"kl549776kjzN","executionInfo":{"status":"ok","timestamp":1617728478780,"user_tz":420,"elapsed":3608,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}}},"source":["stock_list = ['AMZN', 'AAPL', 'FB','GOOG', 'MSFT', 'TSLA']"],"execution_count":4,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":649},"id":"xEUaiLqGZHs7","executionInfo":{"status":"ok","timestamp":1617728478783,"user_tz":420,"elapsed":3580,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"7891e61e-ee04-4e7b-bc6f-da44ab2d1bd3"},"source":["stock_list_df = pd.read_csv('/content/drive/MyDrive/SENG474_Project/data/nasdaq_list.csv')\n","stock_list_df = stock_list_df[stock_list_df['Market Cap'] > 0]\n","stock_list_df = stock_list_df[stock_list_df['IPO Year'] < 2018]\n","#stock_list_df = stock_list_df[stock_list_df['Volume'] > 10000]\n","stock_list_df['Last Sale'] = stock_list_df['Last Sale'].str.slice(start=1)\n","stock_list_df['Last Sale'] = stock_list_df['Last Sale'].astype(float)\n","stock_list_df = stock_list_df[stock_list_df['Volume']*stock_list_df['Last Sale']> 10000000]\n","#stock_list_df = stock_list_df[stock_list_df['Sector'] == 'Technology']\n","stock_list = list(stock_list_df['Symbol'])\n","stock_list_df"],"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Symbol</th>\n","      <th>Name</th>\n","      <th>Last Sale</th>\n","      <th>Net Change</th>\n","      <th>% Change</th>\n","      <th>Market Cap</th>\n","      <th>Country</th>\n","      <th>IPO Year</th>\n","      <th>Volume</th>\n","      <th>Sector</th>\n","      <th>Industry</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>8</th>\n","      <td>AAPL</td>\n","      <td>Apple Inc. Common Stock</td>\n","      <td>121.21</td>\n","      <td>0.620</td>\n","      <td>0.514%</td>\n","      <td>2.101459e+12</td>\n","      <td>United States</td>\n","      <td>1980.0</td>\n","      <td>93940602</td>\n","      <td>Technology</td>\n","      <td>Computer Manufacturing</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>ABCB</td>\n","      <td>Ameris Bancorp Common Stock</td>\n","      <td>54.94</td>\n","      <td>2.260</td>\n","      <td>4.29%</td>\n","      <td>3.824866e+09</td>\n","      <td>United States</td>\n","      <td>1994.0</td>\n","      <td>612835</td>\n","      <td>Finance</td>\n","      <td>Major Banks</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>ACAD</td>\n","      <td>ACADIA Pharmaceuticals Inc. Common Stock</td>\n","      <td>25.86</td>\n","      <td>-0.160</td>\n","      <td>-0.615%</td>\n","      <td>4.138828e+09</td>\n","      <td>United States</td>\n","      <td>1985.0</td>\n","      <td>1388296</td>\n","      <td>Health Care</td>\n","      <td>Major Pharmaceuticals</td>\n","    </tr>\n","    <tr>\n","      <th>43</th>\n","      <td>ACLS</td>\n","      <td>Axcelis Technologies Inc. Common Stock</td>\n","      <td>39.19</td>\n","      <td>2.130</td>\n","      <td>5.747%</td>\n","      <td>1.321961e+09</td>\n","      <td>United States</td>\n","      <td>2000.0</td>\n","      <td>371793</td>\n","      <td>Technology</td>\n","      <td>Industrial Machinery/Components</td>\n","    </tr>\n","    <tr>\n","      <th>44</th>\n","      <td>ACMR</td>\n","      <td>ACM Research Inc. Class A Common Stock</td>\n","      <td>83.36</td>\n","      <td>-0.640</td>\n","      <td>-0.762%</td>\n","      <td>1.562419e+09</td>\n","      <td>United States</td>\n","      <td>2017.0</td>\n","      <td>230639</td>\n","      <td>Technology</td>\n","      <td>Industrial Machinery/Components</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>3955</th>\n","      <td>ZG</td>\n","      <td>Zillow Group Inc. Class A Common Stock</td>\n","      <td>132.08</td>\n","      <td>0.730</td>\n","      <td>0.556%</td>\n","      <td>3.178632e+10</td>\n","      <td>United States</td>\n","      <td>2011.0</td>\n","      <td>1137494</td>\n","      <td>Miscellaneous</td>\n","      <td>Business Services</td>\n","    </tr>\n","    <tr>\n","      <th>3956</th>\n","      <td>ZGNX</td>\n","      <td>Zogenix Inc. Common Stock</td>\n","      <td>18.76</td>\n","      <td>-0.055</td>\n","      <td>-0.292%</td>\n","      <td>1.045599e+09</td>\n","      <td>United States</td>\n","      <td>2010.0</td>\n","      <td>1071416</td>\n","      <td>Health Care</td>\n","      <td>Major Pharmaceuticals</td>\n","    </tr>\n","    <tr>\n","      <th>3969</th>\n","      <td>ZKIN</td>\n","      <td>ZK International Group Co. Ltd Ordinary Share</td>\n","      <td>9.80</td>\n","      <td>-0.550</td>\n","      <td>-5.314%</td>\n","      <td>1.622688e+08</td>\n","      <td>China</td>\n","      <td>2017.0</td>\n","      <td>3000539</td>\n","      <td>Capital Goods</td>\n","      <td>Metal Fabrications</td>\n","    </tr>\n","    <tr>\n","      <th>3970</th>\n","      <td>ZLAB</td>\n","      <td>Zai Lab Limited American Depositary Shares</td>\n","      <td>128.42</td>\n","      <td>-1.660</td>\n","      <td>-1.276%</td>\n","      <td>9.679723e+09</td>\n","      <td>China</td>\n","      <td>2017.0</td>\n","      <td>349013</td>\n","      <td>Health Care</td>\n","      <td>Major Pharmaceuticals</td>\n","    </tr>\n","    <tr>\n","      <th>3972</th>\n","      <td>ZNGA</td>\n","      <td>Zynga Inc. Class A Common Stock</td>\n","      <td>10.06</td>\n","      <td>0.240</td>\n","      <td>2.444%</td>\n","      <td>1.089495e+10</td>\n","      <td>United States</td>\n","      <td>2011.0</td>\n","      <td>14650981</td>\n","      <td>Technology</td>\n","      <td>EDP Services</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>474 rows × 11 columns</p>\n","</div>"],"text/plain":["     Symbol  ...                         Industry\n","8      AAPL  ...           Computer Manufacturing\n","10     ABCB  ...                      Major Banks\n","24     ACAD  ...            Major Pharmaceuticals\n","43     ACLS  ...  Industrial Machinery/Components\n","44     ACMR  ...  Industrial Machinery/Components\n","...     ...  ...                              ...\n","3955     ZG  ...                Business Services\n","3956   ZGNX  ...            Major Pharmaceuticals\n","3969   ZKIN  ...               Metal Fabrications\n","3970   ZLAB  ...            Major Pharmaceuticals\n","3972   ZNGA  ...                     EDP Services\n","\n","[474 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"BFVCQ0Z5kk-x","executionInfo":{"status":"ok","timestamp":1617728481810,"user_tz":420,"elapsed":6580,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}}},"source":["stock_objects = {}\n","for stock in stock_list:\n","    stock_objects[stock] = yf.Ticker(stock)"],"execution_count":6,"outputs":[]},{"cell_type":"code","metadata":{"id":"xhGG4Mt6kmkR","executionInfo":{"status":"ok","timestamp":1617728481821,"user_tz":420,"elapsed":6573,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}}},"source":["def trading_sim_LRM(stock_objects, split_time, time_shift):\n","    columns = ['Date', 'Fund Value', 'Cash']\n","    stock_names = []\n","    proj_buy = 0\n","    curr_cash = 10000\n","    curr_shares = {}\n","    drop_list = [ 'Volume', 'Dividends', 'Stock Splits',\n","                 '5 Day Open Mean', '5 Day High Mean', '5 Day Low Mean',\n","                 '5 Day Close Mean', '5 Day Volume Mean', '5 Day Open Var',\n","                 '5 Day High Var', '5 Day Low Var', '5 Day Close Var',\n","                 '5 Day Volume Var','10 Day Open Mean', '10 Day High Mean', \n","                 '10 Day Low Mean','10 Day Close Mean', '10 Day Volume Mean', \n","                 '10 Day High Var', '10 Day Low Var', '10 Day Close Var',\n","                 '10 Day Volume Var', '10 Day High', '10 Day Low', \n","                 '20 Day Open Mean', '20 Day High Mean', '20 Day Low Mean',\n","                 '20 Day Close Mean', '20 Day Volume Mean', '20 Day Open Var',\n","                 '20 Day High Var', '20 Day Low Var', '20 Day Close Var',\n","                 '20 Day Volume Var', '10 Day Open Var']\n","    \n","    stock_dfs = {}\n","    for key in stock_objects:\n","        stock_dfs[key] = stock_objects[key].history(start='1990-01-01', end='2021-03-31')\n","        \n","    #stock_investing = {}\n","    #for key in stock_objects:\n","    #    stock_investing[key] = pd.read_csv('/content/drive/MyDrive/SENG474_Project/data/sentiment/investing_'+key+'_sentiment.csv')\n","    #    stock_investing[key].set_index('date', inplace=True)\n","    #stock_stocks = {}\n","    #for key in stock_objects:\n","    #    stock_stocks[key] = pd.read_csv('/content/drive/MyDrive/SENG474_Project/data/sentiment/stocks_'+key+'_sentiment.csv')\n","    #    stock_stocks[key].set_index('date', inplace=True)\n","    \n","    for key in stock_dfs:\n","        stock_dfs[key] = pf.rolling_aves(stock_dfs[key])\n","        stock_dfs[key].drop(drop_list, axis=1, inplace=True)\n","        #stock_dfs[key] = stock_dfs[key].merge(stock_investing[key], how='left', left_index=True, right_index=True)\n","        #stock_dfs[key] = stock_dfs[key].merge(stock_stocks[key], how='left', left_index=True, right_index=True)\n","        stock_dfs[key].replace([np.inf, -np.inf], np.nan, inplace=True)\n","        stock_dfs[key].fillna(0, inplace=True)\n","        stock_dfs[key] = pf.future_low_setup(stock_dfs[key], 1)\n","        stock_dfs[key] = pf.future_close_setup(stock_dfs[key], time_shift)\n","\n","    combine_df = pf.combiner(stock_dfs)\n","        \n","    test_dfs = stock_dfs\n","    \n","    for key in test_dfs:\n","        test_dfs[key] = test_dfs[key].tail(split_time)\n","        curr_shares[key] = 0\n","        stock_names.append(key)\n","    \n","    columns = columns + stock_names\n","    cash_df = pd.DataFrame(columns=columns)\n","    curr_line = [combine_df.index[int(len(combine_df) - (split_time * len(stock_dfs)))], curr_cash, curr_cash] + len(stock_names)*[0]\n","    cash_df.loc[len(cash_df)] = curr_line\n","    \n","    while split_time > time_shift:\n","        #print('Days left: ' +str(split_time))\n","        max_stock = ''\n","        max_stock_gain = 0\n","        split_mark = int(len(combine_df) - (split_time * len(stock_dfs)))\n","        \n","        X_train, y_train, X_test, y_test = pf.multi_stock_train_test_split(combine_df, split_time, stock_dfs)\n","        low_train = X_train.iloc[:,-1]\n","        low_test = X_test.iloc[:,-1]\n","        X_train.drop(['Low in 1 Days'], axis=1, inplace=True)\n","        X_test.drop(['Low in 1 Days'], axis=1, inplace=True)\n","        stock_model = LinearRegression().fit(X_train, y_train)\n","        low_model = LinearRegression().fit(X_train, low_train)\n","        \n","        for key in test_dfs:\n","            X = test_dfs[key].iloc[:,:-2]\n","            stock_pred = stock_model.predict(X.head(1))\n","            stock_pred = (float(stock_pred) - X['Close'][0]) / X['Close'][0]\n","            low_pred = low_model.predict(X.head(1))\n","            if stock_pred > max_stock_gain and low_pred > 0:\n","                max_stock = key\n","                max_stock_gain = stock_pred\n","                max_stock_low_pred = low_pred\n","        \n","        for key in test_dfs:\n","            test_dfs[key] = test_dfs[key].iloc[1:]\n","        \n","        \n","        if max_stock_gain > 0:\n","            if test_dfs[max_stock]['Open'][0] < max_stock_low_pred:\n","                proj_buy = test_dfs[max_stock]['Open'][0]\n","            else:    \n","                proj_buy = float((test_dfs[max_stock]['Open'][0] - max_stock_low_pred)*0.5 + test_dfs[max_stock]['Low'][0])\n","            #print(test_dfs[max_stock].index[0])\n","            #if max_stock_low_pred >= test_dfs[max_stock]['Open'][0]:\n","            #   print('Buy at open')\n","            #print(float(proj_buy - test_dfs[max_stock]['Low'][0]))\n","            if curr_shares[max_stock] == 0:\n","                for key in curr_shares:\n","                    if curr_shares[key] > 0:\n","                        curr_cash -= 6.95\n","                    curr_cash += curr_shares[key]*test_dfs[key]['Open'][0]\n","                    curr_shares[key] = 0\n","\n","                if proj_buy >= test_dfs[max_stock]['Low'][0]:\n","                    curr_cash -= 6.95\n","                    curr_shares[max_stock] = curr_cash // proj_buy\n","                    curr_cash -= curr_shares[max_stock]*proj_buy\n","            elif proj_buy >= test_dfs[max_stock]['Low'][0]:\n","                if curr_cash > 70:\n","                    curr_cash -= 6.95\n","                    curr_shares[max_stock] += curr_cash // proj_buy\n","                    curr_cash -= (curr_cash // proj_buy) * proj_buy\n","\n","            '''if proj_buy*0.9 > test_dfs[max_stock]['Low'][0]:\n","                if curr_shares[max_stock] > 0:\n","                    curr_cash -= 6.95\n","                curr_cash += curr_shares[max_stock]*proj_buy*0.9\n","                curr_shares[max_stock] = 0'''\n","\n","        else:\n","            for key in curr_shares:\n","                if curr_shares[key] > 0:\n","                    curr_cash -= 6.95\n","                curr_cash += curr_shares[key]*test_dfs[key]['Open'][0]\n","                curr_shares[key] = 0\n","        \n","        curr_line = [X_test.index[len(stock_names)], curr_cash ,curr_cash] + len(stock_names)*[0]\n","        cash_df.loc[len(cash_df)] = curr_line\n","        for key in curr_shares:\n","            cash_df.iloc[-1, cash_df.columns.get_loc(key)] = curr_shares[key]\n","            cash_df.iloc[-1, cash_df.columns.get_loc('Fund Value')] += curr_shares[key]*test_dfs[key]['Open'][0]\n","        for key in test_dfs:\n","            test_dfs[key] = test_dfs[key].iloc[time_shift-1:]\n","        \n","        split_time -= time_shift\n","\n","    return cash_df"],"execution_count":7,"outputs":[]},{"cell_type":"code","metadata":{"id":"h7nZRHrYQsUs","colab":{"base_uri":"https://localhost:8080/","height":647},"executionInfo":{"status":"ok","timestamp":1617731419734,"user_tz":420,"elapsed":2944465,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"43fa800d-2b80-43c9-ee99-30fcd2cdb56b"},"source":["fund_df = trading_sim_LRM(stock_objects, 292, 1)\n","fund_df.set_index('Date', inplace=True) # on big 6\n","fund_df #57904.5 --> 1 day"],"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Fund Value</th>\n","      <th>Cash</th>\n","      <th>AAPL</th>\n","      <th>ABCB</th>\n","      <th>ACAD</th>\n","      <th>ACLS</th>\n","      <th>ACMR</th>\n","      <th>ACRS</th>\n","      <th>ADBE</th>\n","      <th>AEIS</th>\n","      <th>AERI</th>\n","      <th>AGEN</th>\n","      <th>AGIO</th>\n","      <th>AGNC</th>\n","      <th>AIMC</th>\n","      <th>AKAM</th>\n","      <th>AKBA</th>\n","      <th>ALGN</th>\n","      <th>ALGT</th>\n","      <th>ALKS</th>\n","      <th>ALNY</th>\n","      <th>ALRM</th>\n","      <th>ALTR</th>\n","      <th>ALXN</th>\n","      <th>AMAT</th>\n","      <th>AMBA</th>\n","      <th>AMGN</th>\n","      <th>AMKR</th>\n","      <th>AMRS</th>\n","      <th>AMZN</th>\n","      <th>ANSS</th>\n","      <th>APLS</th>\n","      <th>APOP</th>\n","      <th>APPF</th>\n","      <th>APPN</th>\n","      <th>ARCC</th>\n","      <th>ARCT</th>\n","      <th>ARGX</th>\n","      <th>ARNA</th>\n","      <th>ASML</th>\n","      <th>...</th>\n","      <th>UCTT</th>\n","      <th>UFPI</th>\n","      <th>ULTA</th>\n","      <th>UPLD</th>\n","      <th>URBN</th>\n","      <th>UTHR</th>\n","      <th>VCYT</th>\n","      <th>VERI</th>\n","      <th>VG</th>\n","      <th>VIRT</th>\n","      <th>VISL</th>\n","      <th>VIVO</th>\n","      <th>VNET</th>\n","      <th>VRNS</th>\n","      <th>VRNT</th>\n","      <th>VRSK</th>\n","      <th>VRSN</th>\n","      <th>VRTX</th>\n","      <th>VSAT</th>\n","      <th>WB</th>\n","      <th>WDFC</th>\n","      <th>WERN</th>\n","      <th>WING</th>\n","      <th>WIX</th>\n","      <th>WSC</th>\n","      <th>WYNN</th>\n","      <th>XLNX</th>\n","      <th>XLRN</th>\n","      <th>XNCR</th>\n","      <th>XOMA</th>\n","      <th>XONE</th>\n","      <th>XRAY</th>\n","      <th>YNDX</th>\n","      <th>YY</th>\n","      <th>ZBRA</th>\n","      <th>ZG</th>\n","      <th>ZGNX</th>\n","      <th>ZKIN</th>\n","      <th>ZLAB</th>\n","      <th>ZNGA</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    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<td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      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<td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-03-26</th>\n","      <td>52141.6</td>\n","      <td>3.45388</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-03-29</th>\n","      <td>51393.4</td>\n","      <td>1.10155</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-03-30</th>\n","      <td>58802.8</td>\n","      <td>1.08761</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>292 rows × 476 columns</p>\n","</div>"],"text/plain":["           Fund Value      Cash AAPL ABCB ACAD ACLS  ... ZBRA ZG ZGNX ZKIN ZLAB ZNGA\n","Date                                                 ...                            \n","2020-02-03      10000     10000    0    0    0    0  ...    0  0    0    0    0    0\n","2020-02-04    9993.05  0.190125    0    0    0    0  ...    0  0    0    0    0    0\n","2020-02-05      10782  0.190125    0    0    0    0  ...    0  0    0    0    0    0\n","2020-02-06      11031  0.229616    0    0    0    0  ...    0  0    0    0    0    0\n","2020-02-07    11568.7   1.78897    0    0    0    0  ...    0  0    0    0    0    0\n","...               ...       ...  ...  ...  ...  ...  ...  ... ..  ...  ...  ...  ...\n","2021-03-24    52909.8  0.481866    0    0    0    0  ...    0  0    0    0    0    0\n","2021-03-25    44984.3   1.09461    0    0    0    0  ...    0  0    0    0    0    0\n","2021-03-26    52141.6   3.45388    0    0    0    0  ...    0  0    0    0    0    0\n","2021-03-29    51393.4   1.10155    0    0    0    0  ...    0  0    0    0    0    0\n","2021-03-30    58802.8   1.08761    0    0    0    0  ...    0  0    0    0    0    0\n","\n","[292 rows x 476 columns]"]},"metadata":{"tags":[]},"execution_count":8}]},{"cell_type":"code","metadata":{"id":"MMPScjAI7CiM","colab":{"base_uri":"https://localhost:8080/","height":437},"executionInfo":{"status":"ok","timestamp":1617731419736,"user_tz":420,"elapsed":2944426,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"307e53e5-8968-456a-98a7-6910fd778e79"},"source":["index = yf.Ticker('^IXIC')\n","index_df = index.history(start='2019-01-01')\n","index_df"],"execution_count":10,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Open</th>\n","      <th>High</th>\n","      <th>Low</th>\n","      <th>Close</th>\n","      <th>Volume</th>\n","      <th>Dividends</th>\n","      <th>Stock Splits</th>\n","    </tr>\n","    <tr>\n","      <th>Date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2019-01-02</th>\n","      <td>6506.910156</td>\n","      <td>6693.709961</td>\n","      <td>6506.879883</td>\n","      <td>6665.939941</td>\n","      <td>2261800000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2019-01-03</th>\n","      <td>6584.770020</td>\n","      <td>6600.209961</td>\n","      <td>6457.129883</td>\n","      <td>6463.500000</td>\n","      <td>2607290000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2019-01-04</th>\n","      <td>6567.140137</td>\n","      <td>6760.689941</td>\n","      <td>6554.240234</td>\n","      <td>6738.859863</td>\n","      <td>2579550000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2019-01-07</th>\n","      <td>6757.529785</td>\n","      <td>6855.600098</td>\n","      <td>6741.399902</td>\n","      <td>6823.470215</td>\n","      <td>2507550000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2019-01-08</th>\n","      <td>6893.439941</td>\n","      <td>6909.580078</td>\n","      <td>6795.859863</td>\n","      <td>6897.000000</td>\n","      <td>2380290000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>2021-03-30</th>\n","      <td>13008.799805</td>\n","      <td>13075.750000</td>\n","      <td>12922.570312</td>\n","      <td>13045.389648</td>\n","      <td>4685320000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-03-31</th>\n","      <td>13122.570312</td>\n","      <td>13325.540039</td>\n","      <td>13118.379883</td>\n","      <td>13246.870117</td>\n","      <td>4980670000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-04-01</th>\n","      <td>13414.320312</td>\n","      <td>13487.080078</td>\n","      <td>13404.179688</td>\n","      <td>13480.110352</td>\n","      <td>4553470000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-04-05</th>\n","      <td>13594.900391</td>\n","      <td>13720.580078</td>\n","      <td>13582.759766</td>\n","      <td>13705.589844</td>\n","      <td>4439970000</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2021-04-06</th>\n","      <td>13681.700195</td>\n","      <td>13776.709961</td>\n","      <td>13674.279297</td>\n","      <td>13721.134766</td>\n","      <td>2396557563</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>569 rows × 7 columns</p>\n","</div>"],"text/plain":["                    Open          High  ...  Dividends  Stock Splits\n","Date                                    ...                         \n","2019-01-02   6506.910156   6693.709961  ...          0             0\n","2019-01-03   6584.770020   6600.209961  ...          0             0\n","2019-01-04   6567.140137   6760.689941  ...          0             0\n","2019-01-07   6757.529785   6855.600098  ...          0             0\n","2019-01-08   6893.439941   6909.580078  ...          0             0\n","...                  ...           ...  ...        ...           ...\n","2021-03-30  13008.799805  13075.750000  ...          0             0\n","2021-03-31  13122.570312  13325.540039  ...          0             0\n","2021-04-01  13414.320312  13487.080078  ...          0             0\n","2021-04-05  13594.900391  13720.580078  ...          0             0\n","2021-04-06  13681.700195  13776.709961  ...          0             0\n","\n","[569 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"code","metadata":{"id":"MYreeX9B8Io9","colab":{"base_uri":"https://localhost:8080/","height":639},"executionInfo":{"status":"ok","timestamp":1617731419737,"user_tz":420,"elapsed":2944400,"user":{"displayName":"cody therrien","photoUrl":"","userId":"06182759585838248180"}},"outputId":"58e2b261-4db8-4c17-c289-7c2071566d35"},"source":["results_df = fund_df.merge(index_df, how='left', left_index=True, right_index=True)\n","results_df.drop(results_df.columns.difference(['Fund Value','Close']), 1, inplace=True)\n","results_df.rename(columns={'Close': 'NASDAQ Composite'}, inplace=True)\n","nas_open = results_df['NASDAQ Composite'][0]\n","results_df['NASDAQ Composite'] = results_df['NASDAQ Composite']*10000 / nas_open\n","results_df.reset_index(inplace=True)\n","print(results_df)\n","results_df = results_df.melt('Date', var_name='Company', value_name='Price')\n","\n","# Plots Results\n","line_plot = alt.Chart(results_df).mark_line().encode(\n","    x = 'Date',\n","    y = 'Price',\n","    color = 'Company'\n",").properties(\n","    title='Full Market Linear Regression Simulation Feb 2020-April 2021'\n",")\n","line_plot"],"execution_count":11,"outputs":[{"output_type":"stream","text":["          Date Fund Value  NASDAQ Composite\n","0   2020-02-03      10000      10000.000000\n","1   2020-02-04    9993.05      10209.814445\n","2   2020-02-05      10782      10253.714158\n","3   2020-02-06      11031      10322.157987\n","4   2020-02-07    11568.7      10266.471159\n","..         ...        ...               ...\n","287 2021-03-24    52909.8      13977.493802\n","288 2021-03-25    44984.3      13994.521040\n","289 2021-03-26    52141.6      14168.190648\n","290 2021-03-29    51393.4      14082.914401\n","291 2021-03-30    58802.8      14067.536285\n","\n","[292 rows x 3 columns]\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["alt.Chart(...)"],"text/html":["\n","<div id=\"altair-viz-e6e828faf3854685946eaa3085951fdd\"></div>\n","<script type=\"text/javascript\">\n","  (function(spec, embedOpt){\n","    let outputDiv = document.currentScript.previousElementSibling;\n","    if (outputDiv.id !== \"altair-viz-e6e828faf3854685946eaa3085951fdd\") {\n","      outputDiv = document.getElementById(\"altair-viz-e6e828faf3854685946eaa3085951fdd\");\n","    }\n","    const paths = {\n","      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n","      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n","      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.8.1?noext\",\n","      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n","    };\n","\n","    function loadScript(lib) {\n","      return new Promise(function(resolve, reject) {\n","        var s = document.createElement('script');\n","        s.src = paths[lib];\n","        s.async = true;\n","        s.onload = () => resolve(paths[lib]);\n","        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n","        document.getElementsByTagName(\"head\")[0].appendChild(s);\n","      });\n","    }\n","\n","    function showError(err) {\n","      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n","      throw err;\n","    }\n","\n","    function displayChart(vegaEmbed) {\n","      vegaEmbed(outputDiv, spec, embedOpt)\n","        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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