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@@ -40,7 +40,7 @@ Rating Industries,http://www.ratingshistory.info/,,Data,,,,,,,,,,
Advanced ML II,https://github.com/hudson-and-thames/research,More implementations of Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,,,,,,,hudson-and-thames/research,,,
Advanced ML,https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises,Exercises too Financial Machine Learning (De Prado).,Data Processing Techniques and Transformations,4/3/21 6:12,964,435,4,4/25/18 17:22,1/16/20 17:25,BlackArbsCEO/Adv_Fin_ML_Exercises,active,,
crypto-rl,https://github.com/sadighian/crypto-rl,Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process),Deep Learning,4/3/21 21:08,345,112,1,6/21/18 1:06,11/5/20 11:08,sadighian/crypto-rl,active,3,3/31/21 8:00
DeepLearningInFinance,https://github.com/sonaam1234/DeepLearningInFinance,NEW,Deep Learning,3/8/21 13:09,266,145,1,8/21/17 16:00,8/21/17 17:23,sonaam1234/DeepLearningInFinance,inactive,3,3/31/21 8:00
DeepLearningInFinance,https://github.com/sonaam1234/DeepLearningInFinance,Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) 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. ,Deep Learning,3/8/21 13:09,266,145,1,8/21/17 16:00,8/21/17 17:23,sonaam1234/DeepLearningInFinance,inactive,3,3/31/21 8:00
LTSM GRU,https://github.com/RajatHanda/Finance-Forecasting,Stock Market Forecasting using LSTM\GRU.,Deep Learning,3/29/21 23:59,11,6,1,5/13/18 2:39,2/25/19 0:26,RajatHanda/Finance-Forecasting,inactive,3,
Deep Learning,https://github.com/keon/deepstock,Technical experimentations to beat the stock market using deep learning.,Deep Learning,3/24/21 14:45,427,154,2,12/12/16 2:15,3/4/17 8:37,keon/deepstock,inactive,4,
Deep Learning II,https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks,Tensorflow Regression.,Deep Learning,3/21/21 6:53,174,67,1,7/12/16 12:56,2/16/18 2:43,LiamConnell/deep-algotrading,inactive,3,
@@ -49,15 +49,15 @@ Deep Learning IV,https://github.com/achillesrasquinha/bulbea,Bulbea: Deep Learni
AI Trading,https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md,AI to predict stock market movements.,Deep Learning,4/3/21 21:14,2857,1378,1,1/9/19 8:02,2/11/19 16:32,borisbanushev/stockpredictionai,inactive,5,
ARIMA-LTSM Hybrid,https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid,Hybrid model to predict future price correlation coefficients of two assets.,Deep Learning,4/2/21 15:32,219,83,1,8/5/18 2:13,10/1/18 11:25,imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict,inactive,3,
LTSM Recurrent,https://github.com/VivekPa/AIAlpha,OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network.,Deep Learning,4/3/21 10:48,1199,371,2,10/7/18 3:58,8/3/19 9:00,VivekPa/AIAlpha,active,4,
Deep-Reinforcement-Learning-in-Trading,https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading,NEW,Deep Learning,3/31/21 10:40,137,66,1,5/11/18 0:52,10/26/19 14:22,saeed349/Deep-Reinforcement-Learning-in-Trading,active,3,3/31/21 8:00
Deep-Reinforcement-Learning-in-Trading,https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading,Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) 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](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman),Deep Learning,3/31/21 10:40,137,66,1,5/11/18 0:52,10/26/19 14:22,saeed349/Deep-Reinforcement-Learning-in-Trading,active,3,3/31/21 8:00
Deep Learning III,https://github.com/Rachnog/Deep-Trading,Algorithmic trading with deep learning experiments.,Deep Learning,4/3/21 5:26,1264,675,1,6/18/16 18:23,8/7/18 15:24,Rachnog/Deep-Trading,inactive,5,
Stock-Prediction-Models,https://github.com/huseinzol05/Stock-Prediction-Models,NEW,Deep Learning,4/3/21 20:09,3599,1521,2,12/18/17 10:49,1/5/21 10:31,huseinzol05/Stock-Prediction-Models,active,5,3/31/21 8:00
RLTrader,https://github.com/notadamking/RLTrader,NEW,Deep Learning,4/3/21 20:09,1304,449,15,4/27/19 18:35,10/17/19 16:25,notadamking/RLTrader,active,5,3/31/21 8:00
trading-rl,https://github.com/Kostis-S-Z/trading-rl,NEW,Deep Learning,3/31/21 16:01,179,38,2,4/22/19 10:03,9/28/20 9:07,Kostis-S-Z/trading-rl,active,3,3/31/21 8:00
Stock-Prediction-Models,https://github.com/huseinzol05/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](https://github.com/google-research/bert)),Deep Learning,4/3/21 20:09,3599,1521,2,12/18/17 10:49,1/5/21 10:31,huseinzol05/Stock-Prediction-Models,active,5,3/31/21 8:00
RLTrader,https://github.com/notadamking/RLTrader,predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc.,Deep Learning,4/3/21 20:09,1304,449,15,4/27/19 18:35,10/17/19 16:25,notadamking/RLTrader,active,5,3/31/21 8:00
trading-rl,https://github.com/Kostis-S-Z/trading-rl,Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained,Deep Learning,3/31/21 16:01,179,38,2,4/22/19 10:03,9/28/20 9:07,Kostis-S-Z/trading-rl,active,3,3/31/21 8:00
awesome-deep-trading,https://github.com/cbailes/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,Deep Learning,4/3/21 19:52,541,137,1,11/26/18 3:23,1/1/21 9:41,cbailes/awesome-deep-trading,active,4,3/31/21 8:00
trading-bot,https://github.com/pskrunner14/trading-bot,Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python ,Deep Learning,4/2/21 18:45,286,139,1,8/13/18 10:44,1/23/20 4:41,pskrunner14/trading-bot,active,3,3/31/21 8:00
Advanced-Deep-Trading,https://github.com/Rachnog/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](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/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. ",Deep Learning,3/30/21 7:29,319,158,2,2/16/19 21:18,11/29/20 20:12,Rachnog/Advanced-Deep-Trading,active,3,3/31/21 8:00
FinRL-Library,https://github.com/AI4Finance-LLC/FinRL-Library,NEW,Deep Learning,4/4/21 1:53,1807,433,22,7/26/20 13:18,4/3/21 23:21,AI4Finance-LLC/FinRL-Library,active,5,3/31/21 8:00
FinRL-Library,https://github.com/AI4Finance-LLC/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](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading,Deep Learning,4/4/21 1:53,1807,433,22,7/26/20 13:18,4/3/21 23:21,AI4Finance-LLC/FinRL-Library,active,5,3/31/21 8:00
Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,NEW,Deep Learning,4/3/21 10:08,547,240,6,7/26/20 13:12,1/21/21 18:11,AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020,active,4,3/31/21 8:00
deep-RL-trading,https://github.com/golsun/deep-RL-trading,NEW,Deep Learning,4/1/21 12:51,233,109,1,2/25/18 17:41,12/1/20 22:06,golsun/deep-RL-trading,active,3,3/31/21 8:00
AutomatedStockTrading-DeepQ-Learning,https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning,NEW,Deep Learning,3/24/21 1:11,134,51,2,2/23/19 12:01,2/25/20 18:16,sachink2010/AutomatedStockTrading-DeepQ-Learning,active,3,3/31/21 8:00
1 name url comment category last_update star_count fork_count contributors_count created_at last_commit repo_path repo_status rating finml_added_date
40 Advanced ML II https://github.com/hudson-and-thames/research More implementations of Financial Machine Learning (De Prado). Data Processing Techniques and Transformations hudson-and-thames/research
41 Advanced ML https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises Exercises too Financial Machine Learning (De Prado). Data Processing Techniques and Transformations 4/3/21 6:12 964 435 4 4/25/18 17:22 1/16/20 17:25 BlackArbsCEO/Adv_Fin_ML_Exercises active
42 crypto-rl https://github.com/sadighian/crypto-rl Retrieve limit order book level data from coinbase pro and bitfinex -> record in [arctic](https://github.com/man-group/arctic) timeseries database then implemented trend following strategies (market orders) and market making (limit orders). Uses reinforcement learning (DQN) [keras-rl](https://github.com/keras-rl/keras-rl) to create agents and uses [openai gym](https://gym.openai.com/) to implement POMDP (partially observable markov decision process) Deep Learning 4/3/21 21:08 345 112 1 6/21/18 1:06 11/5/20 11:08 sadighian/crypto-rl active 3 3/31/21 8:00
43 DeepLearningInFinance https://github.com/sonaam1234/DeepLearningInFinance NEW Based on a [talk](https://towardsdatascience.com/deep-learning-in-finance-9e088cb17c03) 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. Deep Learning 3/8/21 13:09 266 145 1 8/21/17 16:00 8/21/17 17:23 sonaam1234/DeepLearningInFinance inactive 3 3/31/21 8:00
44 LTSM GRU https://github.com/RajatHanda/Finance-Forecasting Stock Market Forecasting using LSTM\GRU. Deep Learning 3/29/21 23:59 11 6 1 5/13/18 2:39 2/25/19 0:26 RajatHanda/Finance-Forecasting inactive 3
45 Deep Learning https://github.com/keon/deepstock Technical experimentations to beat the stock market using deep learning. Deep Learning 3/24/21 14:45 427 154 2 12/12/16 2:15 3/4/17 8:37 keon/deepstock inactive 4
46 Deep Learning II https://github.com/LiamConnell/deep-algotrading/tree/master/notebooks Tensorflow Regression. Deep Learning 3/21/21 6:53 174 67 1 7/12/16 12:56 2/16/18 2:43 LiamConnell/deep-algotrading inactive 3
49 AI Trading https://github.com/borisbanushev/stockpredictionai/blob/master/readme2.md AI to predict stock market movements. Deep Learning 4/3/21 21:14 2857 1378 1 1/9/19 8:02 2/11/19 16:32 borisbanushev/stockpredictionai inactive 5
50 ARIMA-LTSM Hybrid https://github.com/imhgchoi/Corr_Prediction_ARIMA_LSTM_Hybrid Hybrid model to predict future price correlation coefficients of two assets. Deep Learning 4/2/21 15:32 219 83 1 8/5/18 2:13 10/1/18 11:25 imhgchoi/ARIMA-LSTM-hybrid-corrcoef-predict inactive 3
51 LTSM Recurrent https://github.com/VivekPa/AIAlpha OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network. Deep Learning 4/3/21 10:48 1199 371 2 10/7/18 3:58 8/3/19 9:00 VivekPa/AIAlpha active 4
52 Deep-Reinforcement-Learning-in-Trading https://github.com/saeed349/Deep-Reinforcement-Learning-in-Trading NEW Deep reinforcement learning for trading leveraging [openai gym](https://gym.openai.com/) 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](https://www.linkedin.com/pulse/deep-reinforcement-learning-trading-saeed-rahman) Deep Learning 3/31/21 10:40 137 66 1 5/11/18 0:52 10/26/19 14:22 saeed349/Deep-Reinforcement-Learning-in-Trading active 3 3/31/21 8:00
53 Deep Learning III https://github.com/Rachnog/Deep-Trading Algorithmic trading with deep learning experiments. Deep Learning 4/3/21 5:26 1264 675 1 6/18/16 18:23 8/7/18 15:24 Rachnog/Deep-Trading inactive 5
54 Stock-Prediction-Models https://github.com/huseinzol05/Stock-Prediction-Models NEW 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](https://github.com/google-research/bert)) Deep Learning 4/3/21 20:09 3599 1521 2 12/18/17 10:49 1/5/21 10:31 huseinzol05/Stock-Prediction-Models active 5 3/31/21 8:00
55 RLTrader https://github.com/notadamking/RLTrader NEW predecessor to [tensortrade](https://github.com/tensortrade-org/tensortrade) uses open api [gym](https://gym.openai.com/) and neat way to render matplotlib plots in real time. Also explains LSTM/data stationarity/Bayesian optimization using [Optuna](https://github.com/optuna/optuna) etc. Deep Learning 4/3/21 20:09 1304 449 15 4/27/19 18:35 10/17/19 16:25 notadamking/RLTrader active 5 3/31/21 8:00
56 trading-rl https://github.com/Kostis-S-Z/trading-rl NEW Deep reinforcement learning for financial trading using [gym](https://gym.openai.com/) and [keras-rl](https://github.com/keras-rl/keras-rl) on FX dataset (EURUSD) not actively maintained Deep Learning 3/31/21 16:01 179 38 2 4/22/19 10:03 9/28/20 9:07 Kostis-S-Z/trading-rl active 3 3/31/21 8:00
57 awesome-deep-trading https://github.com/cbailes/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 Deep Learning 4/3/21 19:52 541 137 1 11/26/18 3:23 1/1/21 9:41 cbailes/awesome-deep-trading active 4 3/31/21 8:00
58 trading-bot https://github.com/pskrunner14/trading-bot Implementation of deep reinforcement learning using Deep Q Network (DQN). Only supports single security at the moment. Idea is roughly based [here](https://keon.github.io/deep-q-learning/) and uses tensorflow/keras. Interesting helper python libraries used here are [tqdm](https://tqdm.github.io/) for console based progress bar and [altair](https://altair-viz.github.io/) for declarative visualization in python Deep Learning 4/2/21 18:45 286 139 1 8/13/18 10:44 1/23/20 4:41 pskrunner14/trading-bot active 3 3/31/21 8:00
59 Advanced-Deep-Trading https://github.com/Rachnog/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](https://github.com/hudson-and-thames/mlfinlab) for calculating return stats and [shap](https://github.com/slundberg/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. Deep Learning 3/30/21 7:29 319 158 2 2/16/19 21:18 11/29/20 20:12 Rachnog/Advanced-Deep-Trading active 3 3/31/21 8:00
60 FinRL-Library https://github.com/AI4Finance-LLC/FinRL-Library NEW 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](https://gym.openai.com/) use [pyfolio](https://github.com/quantopian/pyfolio) for showing backtesting. Big contributions on Proximal Policy Optimization (PPO) advantage actor critic (A2C) and Deep Deterministic Policy Gradient (DDPG) agents for trading Deep Learning 4/4/21 1:53 1807 433 22 7/26/20 13:18 4/3/21 23:21 AI4Finance-LLC/FinRL-Library active 5 3/31/21 8:00
61 Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 https://github.com/AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 NEW Deep Learning 4/3/21 10:08 547 240 6 7/26/20 13:12 1/21/21 18:11 AI4Finance-LLC/Deep-Reinforcement-Learning-for-Automated-Stock-Trading-Ensemble-Strategy-ICAIF-2020 active 4 3/31/21 8:00
62 deep-RL-trading https://github.com/golsun/deep-RL-trading NEW Deep Learning 4/1/21 12:51 233 109 1 2/25/18 17:41 12/1/20 22:06 golsun/deep-RL-trading active 3 3/31/21 8:00
63 AutomatedStockTrading-DeepQ-Learning https://github.com/sachink2010/AutomatedStockTrading-DeepQ-Learning NEW Deep Learning 3/24/21 1:11 134 51 2 2/23/19 12:01 2/25/20 18:16 sachink2010/AutomatedStockTrading-DeepQ-Learning active 3 3/31/21 8:00