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A curated list of practical financial machine learning (FinML) tools and applications in Python.
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README.md Update README.md Jul 26, 2019

README.md

Financial Machine Learning and Data Science

A curated list of practical financial machine learning (FinML) tools and applications. This collection is primarily in Python.

If you want to contribute to this list (please do), send me a pull request or contact me @dereknow or on linkedin. Also, 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

  • Deep Learning - Technical experimentations to beat the stock market using deep learning.
  • Deep Learning II - Tensorflow Regression.
  • Deep Learning III - Algorithmic trading with deep learning experiments.
  • Deep Learning IV - Bulbea: Deep Learning based Python Library.
  • LTSM GRU - Stock Market Forecasting using LSTM\GRU.
    • Multilayer neural network architecture for stock return prediction.
  • LTSM Recurrent - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.
  • ARIMA-LTSM Hybrid - Hybrid model to predict future price correlation coefficients of two assets.
  • Neural Network - Neural networks to predict stock prices.
  • AI Trading - AI to predict stock market movements.

Reinforcement Learning

  • 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

Data Processing Techniques and Transformations

  • 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

Factor and Risk Analysis:

Techniques

Unsupervised:

Textual:

Other Assets

Derivatives and Hedging:

Fixed Income

  • 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

Extended Research:

Courses

Data

Personal Papers

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