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Financial Machine Learning and Data Science

This repo is officially under revamp as of 3/29/2021!!

***TODOs and roadmap is under the github project here If you would like to contribute to this repo, please send us a pull request or contact @dereknow or @bin-yang-algotune
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A curated list of practical financial machine learning (FinML) tools and applications. This collection is primarily in Python.

A listed repository should be deprecated if:

  • Repository's owner explicitly say that "this library is not maintained".
  • Not committed for long time (2~3 years).

Trading

Deep Learning (Details Wiki)

Reinforcement Learning (Details Wiki)

  • RL Trading - A collection of 25+ Reinforcement Learning Trading Strategies - Google Colab.
  • RL - OpenGym with Deep Q-learning and Policy Gradient.
  • RL II - reinforcement learning on stock market and agent tries to learn trading.
  • RL III - Github - Deep Reinforcement Learning based Trading Agent for Bitcoin.
  • RL IV - Reinforcement Learning for finance.
  • RL V - Building an Agent to Trade with Reinforcement Learning.
  • Pair Trading RL - Using deep actor-critic model to learn best strategies in pair trading.

Other Models Details Wiki

Data Processing Techniques and Transformations Details Wiki

  • Advanced ML - Exercises too Financial Machine Learning (De Prado).
  • Advanced ML II - More implementations of Financial Machine Learning (De Prado).

Portfolio Management

Portfolio Selection and Optimisation Details Wiki

Factor and Risk Analysis Details Wiki

Techniques

Unsupervised Details Wiki

Textual Details Wiki

Other Assets

Derivatives and Hedging Details Wiki

Fixed Income Details Wiki

  • Vasicek - Bootstrapping and interpolation.
  • Binomial Tree - Utility functions in fixed income securities.
  • Corporate Bonds - Predicting the buying and selling volume of the corporate bonds.

Alternative Finance Details Wiki

Extended Research Details Wiki

Courses Details Wiki

Data Details Wiki

Colleges, Centers and Departments Details Wiki

Languages
Python 100%