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deep_learning_and_reinforcement_learning
firmai edited this page Oct 4, 2024
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| repo | comment | created_at | last_commit | star_count | repo_status | rating |
|---|---|---|---|---|---|---|
| FinRL-Library | started by Columbia university engineering students and designed as an end to end deep reinforcement learning library for automated trading platform. Implementation of DQN DDQN DDPG etc using PyTorch and gym use pyfolio for showing backtesting stats. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading | 2020-07-26 13:18:16 | 2024-09-28 02:56:03 | 9697.0 | ✔️ | ⭐x5 |
| Stock-Prediction-Models | very good curated list of notebooks showing deep learning + reinforcement learning models. Also contain topics on outlier detections/overbought oversold study/monte carlo simulartions/sentiment analysis from text (text storage/parsing is not detailed but it mentioned using BERT) | 2017-12-18 10:49:59 | 2021-01-05 10:31:50 | 7924.0 | ✖️ | ⭐x5 |
| AI Trading | AI to predict stock market movements. | 2019-01-09 08:02:47 | 2019-02-11 16:32:47 | 4094.0 | ✖️ | ⭐x5 |
| Deep Learning IV | Bulbea: Deep Learning based Python Library. | 2017-03-09 06:11:06 | 2017-03-19 07:42:49 | 2032.0 | ✖️ | ⭐x5 |
| RLTrader | predecessor to tensortrade uses open api gym and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using Optuna etc. | 2019-04-27 18:35:15 | 2019-10-17 16:25:49 | 1731.0 | ✖️ | ⭐x5 |
| Deep Learning III | Algorithmic trading with deep learning experiments. | 2016-06-18 18:23:06 | 2018-08-07 15:24:45 | 1429.0 | ✖️ | ⭐x5 |
| Personae | implementation of deep reinforcement learning and supervised learnings covering areas: deep deterministic policy gradient (DDPG) and DDQN etc. Data are being pulled from rqalpha which is a python backtest engine and have a nice docker image to run training/testing | 2018-03-10 11:22:00 | 2018-09-02 17:21:38 | 1340.0 | ✖️ | ⭐x5 |
| RL Trading | A collection of 25+ Reinforcement Learning Trading Strategies -Google Colab. | nan | nan | nan | ✔️ | ⭐x4 |
| Neural Network | Neural networks to predict stock prices. | 2018-09-10 06:34:53 | 2018-11-21 07:39:31 | 734.0 | ✖️ | ⭐x4 |
| Deep Learning | Technical experimentations to beat the stock market using deep learning. | 2016-12-12 02:15:12 | 2017-03-04 08:37:29 | 470.0 | ✖️ | ⭐x4 |
| Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 | Part of FinRL and provided code for paper deep reinformacement learning for automated stock trading focuses on ensemble. | 2020-07-26 13:12:53 | 2024-07-01 08:09:06 | 2019.0 | ✔️ | ⭐x4 |
| LTSM Recurrent | OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network. | 2018-10-07 03:58:26 | 2019-08-03 09:00:44 | 1711.0 | ✖️ | ⭐x4 |
| awesome-deep-trading | curated list of papers/repos on topics like CNN/LSTM/GAN/Reinforcement Learning etc. Categorized as deep learning for now but there are other topics here. Manually maintained by cbailes | 2018-11-26 03:23:04 | 2021-01-01 09:41:21 | 1482.0 | ✖️ | ⭐x4 |
| trading-bot | Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based here and uses tensorflow/keras. Interesting helper python libraries used here are tqdm for console based progress bar and altair for declarative visualization in python | 2018-08-13 10:44:08 | 2020-01-23 04:41:20 | 952.0 | ✖️ | ⭐x3 |
| crypto-rl | Retrieve limit order book level data from coinbase pro and bitfinex -> record in arctic timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) keras-rl to create agents and uses openai gym to implement POMDP (partially observable markov decision process) | 2018-06-21 01:06:01 | 2021-11-30 13:52:18 | 849.0 | ✖️ | ⭐x3 |
| DQN-DDPG_Stock_Trading | merged into FinRL library and uses gym and implementation of DQN | 2018-09-19 03:17:06 | 2024-03-15 13:46:17 | 815.0 | ✔️ | ⭐x3 |
| RL III | Github -Deep Reinforcement Learning based Trading Agent for Bitcoin. | 2017-09-21 17:05:19 | 2018-04-13 16:33:21 | 750.0 | ✖️ | ⭐x3 |
| Deep-Reinforcement-Stock-Trading | inspired by Q-trader a deep reinforcement learning repo for trading. Only 3 actions allowed (buy/hold/sell) and no transaction cost is implemented yet. Uses empyrical for portfolio stats | 2019-05-19 22:20:05 | 2024-07-31 02:21:24 | 562.0 | ✔️ | ⭐x3 |
| Advanced-Deep-Trading | notebooks containing experiments based on Lopez de Prado book "Advances in financial machine learning". Mostly not deep learning related but rather sklearn regression models. Interesting libraries include mlfinlab for calculating return stats and shap for explaining models. Examlpe of shap can be which features are pushing the value up and and which features are pushing the value down. Also contain functions for calculating geometric brownian motion and jump diffusion functions. | 2019-02-16 21:18:00 | 2020-11-29 20:12:59 | 542.0 | ✖️ | ⭐x3 |
| ARIMA-LTSM Hybrid | Hybrid model to predict future price correlation coefficients of two assets. | 2018-08-05 02:13:21 | 2018-10-01 11:25:53 | 388.0 | ✖️ | ⭐x3 |
| deep-RL-trading | trading game comparing RNN vs CNN vs MLP based on paper | 2018-02-25 17:41:42 | 2020-12-01 22:06:39 | 355.0 | ✖️ | ⭐x3 |
| BitcoinForecast | RNN model to predict short term price movement (in this case BTC for the next 9 minutes) deepchart is used to visualize the model | 2017-03-10 10:52:02 | 2018-06-11 08:07:02 | 350.0 | ✖️ | ⭐x3 |
| Pair Trading RL | Using deep actor-critic model to learn best strategies in pair trading. | 2017-05-18 16:47:11 | 2017-05-18 16:56:38 | 308.0 | ✖️ | ⭐x3 |
| DeepLearningInFinance | Based on a talk Sonam Srivastava gave and there are two studies: 1. single timeseries return prediction using ARIMA/VAR/SVR/Deep Regression/CNN/LSTM 2. indexed portfolio construction using autoencoders i.e. replicate a index using handful of stocks. | 2017-08-21 16:00:42 | 2017-08-21 17:23:48 | 280.0 | ✖️ | ⭐x3 |
| AutomatedStockTrading-DeepQ-Learning | cornerstone project repo for Udacity nanodegree program Become a machine learning engineer and focus on trading using deep q learning. Good explanation on design choices in the report | 2019-02-23 12:01:21 | 2021-08-31 15:34:07 | 261.0 | ✖️ | ⭐x3 |
| LTSM GRU | Stock Market Forecasting using LSTM\GRU. | 2018-05-13 02:39:32 | 2019-02-25 00:26:42 | 24.0 | ✖️ | ⭐x3 |
| Deep Learning II | Tensorflow Regression. | 2016-07-12 12:56:10 | 2018-06-10 19:15:31 | 235.0 | ✖️ | ⭐x3 |
| trading-rl | Deep reinforcement learning for financial trading using gym and keras-rl on FX dataset (EURUSD) not actively maintained | 2019-04-22 10:03:21 | 2020-09-28 09:07:18 | 217.0 | ✖️ | ⭐x3 |
| Deep-Reinforcement-Learning-in-Trading | Deep reinforcement learning for trading leveraging openai gym framework. Keras implementation of DQN DDQN (double deep Q network) and DDDQN (dueling double dqn) trained/tested on s&p 500 daily data from 2013 to 2018. approach is described in an article here | 2018-05-11 00:52:14 | 2019-10-26 14:22:44 | 208.0 | ✖️ | ⭐x3 |
| RL II | reinforcement learning on stock market and agent tries to learn trading. | 2016-06-11 07:27:10 | 2018-01-22 14:35:50 | 1458.0 | ✖️ | ⭐x3 |
| Deep-Learning-Machine-Learning-Stock | curated list of notebooks for machine learning models. Start with very simple linear models to more advanced reinforcement learning type of models. Problem with this repo is that the library version numbers may be changing over time and there's no specific way to track and upgrade | 2018-09-29 23:38:06 | 2024-03-01 00:12:23 | 1222.0 | ✔️ | ⭐x3 |
| RL | OpenGym with Deep Q-learning and Policy Gradient. | 2016-10-04 14:42:19 | 2016-12-23 07:34:08 | 790.0 | ✖️ | ⭐x2 |
| RL V | Building an Agent to Trade with Reinforcement Learning. | 2019-01-16 00:43:36 | 2020-03-19 20:28:08 | 40.0 | ✖️ | ⭐x2 |
| FinRL | NEW | 2020-07-26 13:18:16 | 2024-09-28 02:56:03 | 9697.0 | ✔️ | |
| maro | NEW | 2019-12-27 06:48:27 | 2023-10-30 10:34:18 | 844.0 | ✔️ | |
| gym-trading | NEW | 2016-12-09 20:46:19 | 2017-12-24 15:34:37 | 702.0 | ✖️ | |
| Pair-Trading-Reinforcement-Learning | NEW | 2019-06-09 22:50:37 | 2023-07-16 17:00:56 | 7.0 | ✔️ | |
| Trading-Gym | NEW | 2017-06-13 13:14:48 | 2017-07-10 08:09:30 | 548.0 | ✖️ | |
| QLearning_Trading | NEW | 2016-08-10 06:02:23 | 2016-10-15 02:36:09 | 495.0 | ✖️ | |
| stock-prediction-deep-neural-learning | NEW | 2020-07-01 17:31:42 | 2024-01-03 19:18:12 | 493.0 | ✔️ | |
| tensortrade | NEW | 2019-07-30 21:28:32 | 2024-06-09 21:29:43 | 4515.0 | ✔️ | |
| a3c_trading | NEW | 2018-06-04 15:30:16 | 2023-01-24 01:52:36 | 423.0 | ✔️ | |
| RL-Bitcoin-trading-bot | NEW | 2020-12-02 06:07:14 | 2023-11-24 10:30:07 | 380.0 | ✔️ | |
| RLQuant | NEW | 2018-04-05 05:42:44 | 2018-08-13 04:18:29 | 337.0 | ✖️ | |
| rl_trading | NEW | 2017-05-29 22:19:00 | 2017-08-29 14:54:50 | 272.0 | ✖️ | |
| pairstrade-fyp-2019 | NEW | 2018-09-07 07:51:06 | 2020-05-13 05:06:51 | 256.0 | ✖️ | |
| Machine-Learning-and-Reinforcement-Learning-in-Finance | NEW | 2018-06-26 04:30:08 | 2018-09-23 16:50:33 | 246.0 | ✖️ | |
| slow-momentum-fast-reversion | NEW | 2021-06-27 14:49:05 | 2022-11-24 10:59:47 | 229.0 | ✔️ | |
| freqtrade-gym | NEW | 2020-09-23 12:57:20 | 2021-10-11 07:36:32 | 221.0 | ✖️ | |
| TradingGym | NEW | 2017-11-06 00:50:01 | 2024-09-23 00:44:41 | 210.0 | ✔️ | |
| RL IV | Reinforcement Learning for finance. | 2016-10-21 02:47:17 | 2017-04-07 08:11:57 | 181.0 | ✖️ | |
| An-Application-of-Deep-Reinforcement-Learning-to-Algorithmic-Trading | NEW | 2020-10-05 09:09:24 | 2020-10-06 13:32:48 | 170.0 | ✖️ | |
| TradingGym | NEW | 2017-05-01 13:53:32 | 2023-08-12 05:37:32 | 1556.0 | ✔️ | |
| reinforcement_learning_financial_trading | NEW | 2020-02-04 13:06:40 | 2024-03-07 02:11:19 | 152.0 | ✔️ | |
| IPythonScripts | NEW | 2013-08-18 16:26:25 | 2018-11-18 10:43:05 | 146.0 | ✖️ | |
| DQN-Trading | NEW | 2021-08-27 21:07:21 | 2021-10-09 05:50:21 | 141.0 | ✖️ | |
| gym-continuousDoubleAuction | NEW | 2019-07-20 14:53:16 | 2020-07-22 04:22:36 | 138.0 | ✖️ | |
| TradeMaster | NEW | 2022-08-23 13:02:43 | 2024-02-28 04:13:16 | 1342.0 | ✔️ | |
| Reinforcement-Learning-for-Trading | NEW | 2021-03-15 09:13:21 | 2021-03-15 09:16:53 | 129.0 | ✖️ | |
| Quantitative-finance-papers-using-deep-learning | NEW | 2019-08-22 13:16:08 | 2023-05-21 11:04:12 | 127.0 | ✔️ | |
| Deep_Learning_Machine_Learning_Stock | NEW | 2018-09-29 23:38:06 | 2024-03-01 00:12:23 | 1222.0 | ✔️ | |
| trials | NEW | 2023-04-01 14:25:35 | 2023-08-31 16:16:25 | 109.0 | ✔️ | |
| rl | NEW | 2019-10-19 04:08:30 | 2023-08-25 18:34:01 | 105.0 | ✔️ | |
| StarTrader | NEW | 2019-03-04 04:38:15 | 2019-09-12 21:24:15 | 104.0 | ✖️ |