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Gathers deep learning models for Stock forecasting including trading bots and simulations

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Swetha-Gudivada/Stock-market-prediction-using-deep-learning

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Enhancing Stock Market Prediction Using Deep Learning

CONTENTS

Deep Learning models

1.LSTM

2.LSTM Bidirectional

3.LSTM 2-Path

4.GRU

5.GRU Bidirectional

6.GRU 2-Path

7.Vanilla

8.Vanilla Bidirectional

9.Vanilla 2-Path

10.LSTM Seq2seq

11.LSTM Bidirectional Seq2seq

12.LSTM Seq2seq VAE

13.GRU Seq2seq

14.GRU Bidirectional Seq2seq

15.GRU Seq2seq VAE

16.Attention-is-all-you-Need

17.CNN-Seq2seq

18.Dilated-CNN-Seq2seq

Stacking

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

Agents

1.Turtle-trading agent

2.Moving-average agent

3.Signal rolling agent

4.Policy-gradient agent

5.Q-learning agent

6.Evolution-strategy agent

7.Double Q-learning agent

8.Recurrent Q-learning agent

9.Double Recurrent Q-learning agent

10.Duel Q-learning agent

11.Double Duel Q-learning agent

12.Duel Recurrent Q-learning agent

13.Double Duel Recurrent Q-learning agent

14.Actor-critic agent

15.Actor-critic Duel agent

16.Actor-critic Recurrent agent

17.Actor-critic Duel Recurrent agent

18.Curiosity Q-learning agent

19.Recurrent Curiosity Q-learning agent

20.Duel Curiosity Q-learning agent

21.Neuro-evolution agent

22.Neuro-evolution with Novelty search agent

23.ABCD strategy agent

Data Exploration

1.Stock market study on TESLA stock, tesla-study.ipynb

2.Outliers study using K-means, SVM, and Gaussian on TESLA stock, outliers.ipynb

3.Overbought-Oversold study on TESLA stock, overbought-oversold.ipynb

4.Which stock you need to buy? which-stock.ipynb

RESULTS

Stock forecasting JS

LSTM Model for stock forecasting and buying simulation inside Tensorflow JS, so everyone can try!

How-to

  1. Clone this folder and just open index.html,

Or, go to stock-forecasting-js!

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  1. Check hyper parameters you want to tune,

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  1. You can upload any stock CSV, downloaded from Yahoo finance or any website. Any error, please open an issue.

  2. Train the model and wait it's fitting!

  3. After done training, it will predict where to buy and sell,

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Comparing histogram and loss graph,

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