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Readme update (#111)
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* add demo link in readme. bump version.

* fix colab link

* try html for target blank support.

* nvm
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Joshwani authored Aug 6, 2024
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4 changes: 3 additions & 1 deletion README.md
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## Overview
The LPPLS model provides a flexible framework to detect bubbles and predict regime changes of a financial asset. A bubble is defined as a faster-than-exponential increase in asset price, that reflects positive feedback loop of higher return anticipations competing with negative feedback spirals of crash expectations. It models a bubble price as a power law with a finite-time singularity decorated by oscillations with a frequency increasing with time.

🆕 The LPPLS Confidence Indicator (LPPLS CI), an indicator derived from the LPPLS model, is applied to both G7 and BRICS nations and has been made available as a digital resource. To experience and interact with the data visualization, one can access the platform hosted by Boulder Investment Technologies at ✨[signals.boulderinvestment.tech](https://signals.boulderinvestment.tech)✨.
Try the demo:

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Qvbdj4DGNcC9Oop9mA6Vzdvsoec6k2I0?usp=sharing)

Here is the model:

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2 changes: 1 addition & 1 deletion setup.py
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long_description = fh.read()

setuptools.setup(name='lppls',
version='0.6.18',
version='0.6.19',
description='A Python module for fitting the LPPLS model to data.',
packages=['lppls'],
author='Josh Nielsen',
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