/Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting, included trading bots

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Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting, included trading bots

Models

Stacking models

  1. Deep Feed-forward Auto-Encoder Neural Network to reduce dimension + Deep Recurrent Neural Network + ARIMA + Extreme Boosting Gradient Regressor
  2. Adaboost + Bagging + Extra Trees + Gradient Boosting + Random Forest + XGB

Deep-learning models

  1. LSTM Recurrent Neural Network
  2. Encoder-Decoder Feed-forward + LSTM Recurrent Neural Network
  3. LSTM Bidirectional Neural Network
  4. 2-Path LSTM Recurrent Neural Network
  5. GRU Recurrent Neural Network
  6. Encoder-Decoder Feed-forward + GRU Recurrent Neural Network
  7. GRU Bidirectional Neural Network
  8. 2-Path GRU Recurrent Neural Network
  9. Vanilla Recurrent Neural Network
  10. Encoder-Decoder Feed-forward + Vanilla Recurrent Neural Network
  11. Vanilla Bidirectional Neural Network
  12. 2-Path Vanilla Recurrent Neural Network
  13. LSTM Sequence-to-Sequence Recurrent Neural Network
  14. LSTM with Attention Recurrent Neural Network
  15. LSTM Sequence-to-Sequence with Attention Recurrent Neural Network
  16. LSTM Sequence-to-Sequence Bidirectional Recurrent Neural Network
  17. LSTM Sequence-to-Sequence with Attention Bidirectional Recurrent Neural Network
  18. LSTM with Attention Scaled-Dot Recurrent Neural Network
  19. LSTM with Dilated Recurrent Neural Network
  20. Only Attention Neural Network
  21. Multihead Attention Neural Network
  22. LSTM with Bahdanau Attention
  23. LSTM with Luong Attention
  24. LSTM with Bahdanau + Luong Attention
  25. DNC Recurrent Neural Network
  26. Residual LSTM Recurrent Neural Network

Agents

  1. Simple signal rolling agent
  2. Q-learning deep learning agent
  3. Evolution-strategy agent
  4. Evolution-strategy-Bayesian agent

Miscellaneous

  1. stock market study on TESLA stock, tesla-study.ipynb
  2. fashion trending prediction with cross-validation, fashion-forecasting.ipynb

Results Agent

signal rolling agent, READ MORE

total gained 185.099850, total investment 1.850998 %

q-learning deep learning agent READ MORE

total gained -108.630036, total investment -1.086300 %

evolution strategy agent READ MORE

total gained 8240.610260, total investment 82.406103 %

evolution strategy with bayesian agent READ MORE

total gained 9221.279840, total investment 92.212798 %

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Results signal prediction

LSTM Recurrent Neural Network

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LSTM Bidirectional Neural Network

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2-Path LSTM Recurrent Neural Network

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Deep Feed-forward Auto-Encoder Neural Network to reduce dimension + Deep Recurrent Neural Network + ARIMA + Extreme Boosting Gradient Regressor

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LSTM Sequence-to-Sequence Recurrent Neural Network

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LSTM Sequence-to-Sequence with Attention Recurrent Neural Network

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LSTM Sequence-to-Sequence with Attention Bidirectional Recurrent Neural Network

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Encoder-Decoder Feed-forward + LSTM Recurrent Neural Network

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Adaboost + Bagging + Extra Trees + Gradient Boosting + Random Forest + XGB

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