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Detecting Stock Market Crashes with Topological Data Analysis

What is it?

A demo on how to build a simple topological detector to analyse stock market crashes. To learn more, have a look at our blog post.

Getting started

Spin up a virtual environment and install the required libraries:

virtualenv -p python3.7 env
pip install -r requirements.txt

To make plotly play nice with JupyterLab one needs to also run

# Avoid "JavaScript heap out of memory" errors during extension installation
# (OS X/Linux)
export NODE_OPTIONS=--max-old-space-size=4096
# (Windows)
set NODE_OPTIONS=--max-old-space-size=4096

# Jupyter widgets extension
jupyter labextension install @jupyter-widgets/[email protected] --no-build

# FigureWidget support
jupyter labextension install [email protected] --no-build

# and jupyterlab renderer support
jupyter labextension install [email protected] --no-build

# JupyterLab chart editor support (optional)
jupyter labextension install [email protected] --no-build

# Build extensions (must be done to activate extensions since --no-build is used above)
jupyter lab build

# Unset NODE_OPTIONS environment variable
# (OS X/Linux)
unset NODE_OPTIONS
# (Windows)
set NODE_OPTIONS=

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How to detect stock market crashes with topology.

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