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A visualization of 156 published stock market anomalies
Python
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.gitignore Mvp (#1) May 29, 2019
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README.md
application.py
requirements.txt
screenshot.png correct number of anomalies May 29, 2019

README.md

Anomalies

A visualization of 156 published stock market anomalies based on data from Chen and Zimmermann (2019).

Getting Started

  1. Clone the repository
  2. Download the returns data from Andrew Chen's Website. Place it in data/signal_month_returns.csv so the app can find it.
  3. Install the required packages from requirements.txt, ideally in a virtual environment.
  4. Run python application.py in a terminal for local execution

Demo

You can find a live demo here.

Screenshot from anomalies.maximilianeber.com

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