{"id":13409388,"url":"https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading","last_synced_at":"2025-03-14T14:31:12.431Z","repository":{"id":39897849,"uuid":"156283359","full_name":"grananqvist/Awesome-Quant-Machine-Learning-Trading","owner":"grananqvist","description":"Quant/Algorithm trading resources with an emphasis on Machine Learning","archived":false,"fork":false,"pushed_at":"2023-08-15T08:20:33.000Z","size":31,"stargazers_count":2851,"open_issues_count":2,"forks_count":572,"subscribers_count":141,"default_branch":"master","last_synced_at":"2025-03-02T08:39:55.691Z","etag":null,"topics":["awesome","awesome-list","deep-learning","financial-machine-learning","machine-learning","machine-learning-trading","stock-trading","trading-strategies"],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/grananqvist.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-11-05T21:09:06.000Z","updated_at":"2025-03-02T07:56:15.000Z","dependencies_parsed_at":"2024-01-07T11:04:59.295Z","dependency_job_id":null,"html_url":"https://github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FAwesome-Quant-Machine-Learning-Trading","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FAwesome-Quant-Machine-Learning-Trading/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FAwesome-Quant-Machine-Learning-Trading/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/grananqvist%2FAwesome-Quant-Machine-Learning-Trading/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/grananqvist","download_url":"https://codeload.github.com/grananqvist/Awesome-Quant-Machine-Learning-Trading/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243593356,"owners_count":20316172,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["awesome","awesome-list","deep-learning","financial-machine-learning","machine-learning","machine-learning-trading","stock-trading","trading-strategies"],"created_at":"2024-07-30T20:01:00.381Z","updated_at":"2025-03-14T14:31:12.392Z","avatar_url":"https://github.com/grananqvist.png","language":null,"funding_links":[],"categories":["Others","Domain Applications","Machine Learning","Other Awesome List","Other Projects","Outdated","Other Lists","📚 Project Purpose"],"sub_categories":["GYM Environment","Science, Medicine, and Quant","JavaScript","Datasets","Explainability, Interpretability and Fairness","TeX Lists","Machine Learning (Interview-Level"],"readme":"# Awesome-Quant-Machine-Learning-Trading\nQuant/Algorithm trading resources with an emphasis on Machine Learning. \n\nI have excluded any kind of resources that I consider to be of low quality.  \n\n:star: - My favourites\n\n# Financial Machine Learning\n## Books\n\n* :star: Marcos López de Prado - Advances in Financial Machine Learning [[Link]](https://www.amazon.com/Advances-Financial-Machine-Learning-Marcos-ebook/dp/B079KLDW21/ref=sr_1_1?s=books\u0026ie=UTF8\u0026qid=1541717436\u0026sr=1-1).\n* :star: Dr Howard B Bandy - Quantitative Technical Analysis: An integrated approach to trading system development and trading management [[Link]](https://www.amazon.com/Quantitative-Technical-Analysis-integrated-development/dp/0979183855/ref=sr_1_1?s=books\u0026ie=UTF8\u0026qid=1541718134\u0026sr=1-1)\n* Tony Guida - Big Data and Machine Learning in Quantitative Investment [[Link]](https://www.amazon.com/Machine-Learning-Quantitative-Investment-Finance/dp/1119522196/ref=sr_1_1?s=books\u0026ie=UTF8\u0026qid=1541717791\u0026sr=1-1)\n* :star: Michael Halls-Moore - Advanced Algorithmic Trading [[Link]](https://www.quantstart.com/advanced-algorithmic-trading-ebook)\n* Jannes Klaas - Machine Learning for Finance: Data algorithms for the markets and deep learning from the ground up for financial experts and economics [[Link]](https://www.amazon.com/Machine-Learning-Finance-algorithms-financial-ebook/dp/B07BDK6LF9/ref=sr_1_1?s=digital-text\u0026ie=UTF8\u0026qid=1541717605\u0026sr=1-1)\n* Stefan Jansen - Hands-On Machine Learning for Algorithmic Trading: Design and implement smart investment strategies to analyze market behavior using the Python ecosystem [[Link]](https://www.amazon.com/Hands-Machine-Learning-Algorithmic-Trading-ebook/dp/B07JLFH7C5/ref=sr_1_1?s=digital-text\u0026ie=UTF8\u0026qid=1541717705\u0026sr=1-1)\n* Ali N. Akansu et al. - Financial Signal Processing and Machine Learning [[Link]](https://www.amazon.com/Financial-Signal-Processing-Machine-Learning/dp/1118745671/ref=sr_1_1?s=books\u0026ie=UTF8\u0026qid=1541718070\u0026sr=1-1)\n* David Aronson - Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading [[Link]](https://www.amazon.com/Evidence-Based-Technical-Analysis-Scientific-Statistical/dp/0470008741/ref=sr_1_1?s=books\u0026ie=UTF8\u0026qid=1541974508\u0026sr=1-1\u0026keywords=david+aronson)\n* David Aronson - Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments [[Link]](https://www.amazon.com/Statistically-Learning-Algorithmic-Financial-Instruments/dp/148950771X/ref=sr_1_3?s=books\u0026ie=UTF8\u0026qid=1541718293\u0026sr=1-3)\n* Ernest P. Chan - Machine Trading: Deploying Computer Algorithms to Conquer the Markets [[Link]](https://www.amazon.co.uk/gp/product/1119219604/ref=as_li_qf_asin_il_tl?ie=UTF8\u0026tag=startupanalyt-21\u0026creative=24630\u0026linkCode=as2\u0026creativeASIN=1119219604\u0026linkId=ce2ca9a67128675e3fcdc9ec9696e2c7)\n\n## Online series and courses\nThe selection of online courses for ML for trading is very poor in my opinion.  \n\n* Udacity, Georgia Tech - Machine Learning for Trading [[Link]](https://eu.udacity.com/course/machine-learning-for-trading--ud501)\n* Udacity, WorldQuant - Artificial Intelligence for Trading [[Link]](https://eu.udacity.com/course/ai-for-trading--nd880)\n\n* Coursera, NYU - Machine Learning and Reinforcement Learning in Finance Specialization (Weakly related to trading)\n  * Coursera, NYU - Guided Tour of Machine Learning in Finance [[Link]](https://www.coursera.org/learn/guided-tour-machine-learning-finance)\n  * Coursera, NYU - Fundamentals of Machine Learning in Finance [[Link]](https://www.coursera.org/learn/fundamentals-machine-learning-in-finance)\n  * Coursera, NYU - Reinforcement Learning in Finance [[Link]](https://www.coursera.org/learn/reinforcement-learning-in-finance)\n  * Coursera, NYU - Overview of Advanced Methods for Reinforcement Learning in Finance [[Link]](https://www.coursera.org/learn/advanced-methods-reinforcement-learning-finance)\n\n## Youtube videos\n* :star: Siraj Raval - Videos about stock market prediction using Deep Learning [[Link]](https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A/search?query=trading)\n* QuantInsti Youtube - webinars about Machine Learning for trading [[Link]](https://www.youtube.com/user/quantinsti/search?query=machine+learning)\n* :star: Quantopian - Webinars about Machine Learning for trading [[Link]](https://www.youtube.com/channel/UC606MUq45P3zFLa4VGKbxsg/search?query=machine+learning)\n* Sentdex - Machine Learning for Forex and Stock analysis and algorithmic trading [[Link]](https://www.youtube.com/watch?v=v_L9jR8P-54\u0026list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO)\n* Sentdex - Python programming for Finance (a few videos including Machine Learning) [[Link]](https://www.youtube.com/watch?v=Z-5wNWgRJpk\u0026index=9\u0026list=PLQVvvaa0QuDcOdF96TBtRtuQksErCEBYZ)\n* QuantNews - Machine Learning for Algorithmic Trading 3 part series [[Link]](https://www.youtube.com/playlist?list=PLHJACfjILJ-91qkw5YC83S6COKGscctzz)\n* :star: Howard Bandy - Machine Learning Trading System Development Webinar [[Link]](https://www.youtube.com/watch?v=v729evhMpYk\u0026t=1s)\n* Ernie Chan - Machine Learning for Quantitative Trading Webinar [[Link]](https://www.youtube.com/watch?v=72aEDjwGMr8\u0026t=1023s)\n* Hitoshi Harada, CTO at Alpaca - Deep Learning in Finance Talk [[Link]](https://www.youtube.com/watch?v=FoQKCeDuPiY)\n* Prediction Machines - Deep Learning with Python in Finance Talk [[Link]](https://www.youtube.com/watch?v=xvm-M-R2fZY)\n* Master Thesis presentation, Uni of Essex - Analyzing the Limit Order Book, A Deep Learning Approach [[Link]](https://www.youtube.com/watch?v=qxSh2VFmRGw)\n* Tucker Balch - Applying Deep Reinforcement Learning to Trading [[Link]](https://www.youtube.com/watch?v=Pka0DC_P17k)\n* Krish Naik - Machine learning tutorials and their Application in Stock Prediction [[Link]](https://www.youtube.com/watch?v=H6du_pfuznE)\n## Blogs and content websites\n* :star: Quantstart - Machine Learning for Trading articles [[Link]](https://www.quantstart.com/articles)\n* :star: Quantopian - Lecture notebooks on ML-related statistics [[Link]](https://www.quantopian.com/lectures)\n* :star: Quantopian - Tutorials and notebooks tagged with Machine Learning [[Link]](https://www.quantopian.com/posts/tag/machine-learning/newest?attachment=notebooks)\n* AAA Quants, Tom Starke Blog [[Link]](http://aaaquants.com/category/blog/)\n* RobotWealth, Kris Longmore Blog [[Link]](https://robotwealth.com/blog/)\n* Quantsportal, Jacques Joubert's Blog [[Link]](http://www.quantsportal.com/blog-page/)\n* Blackarbs blog [[Link]](http://www.blackarbs.com/blog/)\n* Hardikp, Hardik Patel blog [[Link]](https://www.hardikp.com/)\n\n## Interviews\n* :star: Chat with Traders EP042 - Machine learning for algorithmic trading with Bert Mouler [[Link]](https://www.youtube.com/watch?v=i8FNO8r7PaE)\n* :star: Chat with Traders EP142 - Algo trader using automation to bypass human flaws with Bert Mouler [[Link]](https://www.youtube.com/watch?v=ofL66mh6Tw0)\n* Chat with Traders EP147 - Detective work leading to viable trading strategies with Tom Starke [[Link]](https://www.youtube.com/watch?v=JjXw9Mda7eY)\n* :star: Chat with Traders Quantopian 5 - Good Uses of Machine Learning in Finance with Max Margenot [[Link]](https://www.youtube.com/watch?v=Zj5sXWv9SDM)\n* Chat With Traders EP131 - Trading strategies, powered by machine learning with Morgan Slade [[Link]](https://www.youtube.com/watch?v=EbWbeYu8zwg)\n* Better System Trader EP023 - Portfolio manager Michael Himmel talks AI and machine learning in trading [[Link]](https://www.youtube.com/watch?v=9tZjeyhfG0g)\n* :star: Better System Trader EP028 - David Aronson shares research into indicators that identify Bull and Bear markets. [[Link]](https://www.youtube.com/watch?v=Q4rV0Y9NokI)\n* Better System Trader EP082 - Machine Learning With Kris Longmore [[Link]](https://www.youtube.com/watch?v=0syNgsd635M)\n* :star: Better System Trader EP064 - Cryptocurrencies and Machine Learning with Bert Mouler [[Link]](https://www.youtube.com/watch?v=YgRTd4nLJoU)\n* Better System Trader EP090 - This quants’ approach to designing algo strategies with Michael Halls-Moore [[Link]](https://chatwithtraders.com/ep-090-michael-halls-moore/)\n\n## Papers\n* :star: James Cumming - An Investigation into the Use of Reinforcement Learning Techniques within the Algorithmic Trading Domain [[Link]](http://www.doc.ic.ac.uk/teaching/distinguished-projects/2015/j.cumming.pdf)\n* :star: Marcos López de Prado - The 10 reasons most Machine Learning Funds fails [[Link]](http://www.smallake.kr/wp-content/uploads/2018/07/SSRN-id3104816.pdf)\n* Zhuoran Xiong et al. - Practical Deep Reinforcement Learning Approach for Stock Trading [[Link]](https://arxiv.org/abs/1811.07522)\n* Gordon Ritter - Machine Learning for Trading [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3015609)\n* J.B. Heaton et al. - Deep Learning for Finance: Deep Portfolios [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2838013)\n* Justin Sirignano et al. - Universal Features of Price Formation in Financial Markets: Perspectives From Deep Learning [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3141294)\n* Marcial Messmer - Deep Learning and the Cross-Section of Expected Returns [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3081555)\n* :star: Marcos Lopez de Prado - Ten Financial Applications of Machine Learning (Presentation Slides) [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3197726)\n* :star: Marcos Lopez de Prado - The Myth and Reality of Financial Machine Learning (Presentation Slides) [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3120557)\n* Artur Sepp - Machine Learning for Volatility Trading (Presentation Slides) [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3186401)\n* Marcos Lopez de Prado - Market Microstructure in the Age of Machine Learning [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3193702)\n* Jonathan Brogaard - Machine Learning and the Stock Market [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3233119)\n* Xinyao Qian - Financial Series Prediction: Comparison Between Precision of Time Series Models and Machine Learning Methods [[Link]](https://arxiv.org/pdf/1706.00948.pdf)\n* Milan Fičura - Forecasting Foreign Exchange Rate Movements with k-Nearest-Neighbour, Ridge Regression and Feed-Forward Neural Networks [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2903547)\n* Samuel Edet - Recurrent Neural Networks in Forecasting S\u0026P 500 Index [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3001046)\nAmin Hedayati et al. - Stock Market Index Prediction Using Artificial Neural Network [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3004032)\n* Jaydip Sen et al. - A Robust Predictive Model for Stock Price Forecasting [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3068204)\n*  O.B. Sezer et al. - An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework [[Link]](https://dl.acm.org/citation.cfm?id=3077294)\n* Ritika Singh et al. - Stock prediction using deep learning [[Link]](https://link.springer.com/article/10.1007/s11042-016-4159-7)\n* Thomas Fischera et al. - Deep learning with long short-term memory networks for financial market predictions [[Link]](https://www.econstor.eu/bitstream/10419/157808/1/886576210.pdf)\n* R.C.Cavalcante et al. - Computational Intelligence and Financial Markets: A Survey and Future Directions [[Link]](https://www.sciencedirect.com/science/article/pii/S095741741630029X)\n* E. Chong et al. - Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies [[Link]](http://dro.dur.ac.uk/21533/1/21533.pdf)\n* Chien Yi Huang - Financial Trading as a Game: A Deep Reinforcement Learning Approach [[Link]](https://arxiv.org/pdf/1807.02787.pdf)\n* W. Bao et al. - A deep learning framework for financial time series using stacked autoencoders and longshort term memory [[Link]](https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0180944\u0026type=printable)\n* Xingyu Zhou et al. - Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets [[Link]](http://downloads.hindawi.com/journals/mpe/2018/4907423.pdf)\n* Fuli Feng et al. - Improving Stock Movement Prediction with Adversarial Training [[Link]](https://arxiv.org/pdf/1810.09936.pdf)\n* Z. Zhao et al. - Time-Weighted LSTM Model with Redefined Labeling for Stock Trend Prediction [[Link]](https://ieeexplore.ieee.org/abstract/document/8372087)\n* Arthur le Calvez, Dave Cliff - Deep Learning can Replicate Adaptive Traders in a Limit-Order-Book Financial Market [[Link]](https://arxiv.org/abs/1811.02880)\n* Dang Lien Minh et al. - Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network [[Link]](https://ieeexplore.ieee.org/abstract/document/8456512)\n* Yue Deng et al. - Deep Direct Reinforcement Learning for Financial Signal Representation and Trading [[Link]](http://cslt.riit.tsinghua.edu.cn/mediawiki/images/a/aa/07407387.pdf)\n* Xiao Zhong - A comprehensive cluster and classification mining procedure for daily stock market return forecasting [[Link]](https://www.sciencedirect.com/science/article/pii/S0925231217310652)\n* J. Zhang et al. - A novel data-driven stock price trend prediction system [[Link]](https://www.sciencedirect.com/science/article/pii/S0957417417308485)\n* Ehsan Hoseinzade et al. - CNNPred: CNN-based stock market prediction using several data sources [[Link]](https://arxiv.org/pdf/1810.08923.pdf)\n* Hyejung Chung et al. - Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction [[Link]](https://www.mdpi.com/2071-1050/10/10/3765/pdf)\n* Yujin Baek et al. - ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module [[Link]](https://www.sciencedirect.com/science/article/pii/S0957417418304342)\n* Rajashree Dash et al. - A hybrid stock trading framework integrating technical analysis with machine learning techniques [[Link]](https://www.sciencedirect.com/science/article/pii/S2405918815300179)\n* E.A. Gerlein et al. - Evaluating machine learning classification for financial trading: an empirical approach [[Link]](http://nrl.northumbria.ac.uk/34544/1/Evaluating%20machine%20learning.pdf)\n* Justin Sirignano - Deep Learning for Limit Order Books [[Link]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2710331)\n\n### Events \u0026 Sentiment trading\n* Frank Z. Xing et al. - Natural language based financial forecasting: a survey [[Link]](http://sentic.net/natural-language-based-financial-forecasting.pdf)\n* Ziniu Hu et al. - Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction [[Link]](https://arxiv.org/abs/1712.02136v1)\n* J.W. Leung, Master Thesis, MIT - Application of Machine Learning: Automated Trading Informed by Event Driven Data [[Link]](https://dspace.mit.edu/bitstream/handle/1721.1/105982/965785890-MIT.pdf?sequence=1)\n* Xiao Ding et al. - Deep Learning for Event-Driven Stock Prediction [[Link]](http://www.aaai.org/ocs/index.php/IJCAI/IJCAI15/paper/download/11031/10986)\n\n## Reinforcement Learning environments\n* :star: TradingGym [[Link]](https://github.com/Yvictor/TradingGym)\n* Trading-Gym [[Link]](https://github.com/thedimlebowski/Trading-Gym)\n* btym [[Link]](https://github.com/Kismuz/btgym)\n* TradzQAI [[Link]](https://github.com/kkuette/TradzQAI)\n\n## Code\n* marketneutral - pairs trading with ML [[Link]](https://github.com/marketneutral/pairs-trading-with-ML)\n* BlackArbsCEO - Advances in Financial Machine Learning Exercises [[Link]](https://github.com/BlackArbsCEO/Adv_Fin_ML_Exercises)\n* mlfinlab - Package for Advances in Financial Machine Learning [[Link]](https://github.com/hudson-and-thames)\n* MachineLearningStocks - Using python and scikit-learn to make stock predictions [[Link]](https://github.com/robertmartin8/MachineLearningStocks)\n* AlphaAI - Use unsupervised and supervised learning to predict stocks [[Link]](https://github.com/VivekPa/AlphaAI)\n* SGX-Full-OrderBook-Tick-Data-Trading-Strategy - Providing the solutions for high-frequency trading (HFT) strategies using ML [[Link]](https://github.com/rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy)\n* NeuralNetworkStocks - Using Python and keras to make stock predictions [[Link]](https://github.com/VivekPa/NeuralNetworkStocks)\n* Stock-Price-Prediction-LSTM - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network [[Link]](https://github.com/NourozR/Stock-Price-Prediction-LSTM)\n* SravB - Algorithmic trading using machine learning [[Link]](https://github.com/SravB/Algorithmic-Trading)\n* Flow - High frequency AI based algorithmic trading module [[Link]](https://github.com/yazanobeidi/flow)\n* timestocome - Test-stock-prediction-algorithms [[Link]](https://github.com/timestocome/Test-stock-prediction-algorithms)\n* deepstock - Technical experimentations to beat the stock market using deep learning [[Link]](https://github.com/keon/deepstock)\n* qtrader - Reinforcement Learning for Portfolio Management [[Link]](https://github.com/filangel/qtrader)\n* stockPredictor - Predict stock movement with Machine Learning and Deep Learning algorithms [[Link]](https://github.com/Nazanin1369/stockPredictor)\n* stock_market_reinforcement_learning - Stock market environment using OpenGym with Deep Q-learning and Policy Gradient [[Link]](https://github.com/kh-kim/stock_market_reinforcement_learning)\n* deep-algotrading - deep learning techniques from regression to LSTM using financial data [[Link]](https://github.com/LiamConnell/deep-algotrading)\n* deep_trader - Use reinforcement learning on stock market and agent tries to learn trading [[Link]](https://github.com/deependersingla/deep_trader)\n* Deep-Trading - Algorithmic trading with deep learning experiments [[Link]](https://github.com/Rachnog/Deep-Trading)\n* Deep-Trading - Algorithmic Trading using RNN [[Link]](https://github.com/ha2emnomer/Deep-Trading)\n* Multidimensional-LSTM-BitCoin-Time-Series - Using multidimensional LSTM neural networks to create a forecast for Bitcoin price [[Link]](https://github.com/jaungiers/Multidimensional-LSTM-BitCoin-Time-Series)\n* QLearning_Trading - Learning to trade under the reinforcement learning framework [[Link]](https://github.com/ucaiado/QLearning_Trading)\n* Day-Trading-Application - Use deep learning to make accurate future stock return predictions [[Link]](https://github.com/jbboltz123/Day-Trading-Application)\n* bulbea - Deep Learning based Python Library for Stock Market Prediction and Modelling [[Link]](https://github.com/achillesrasquinha/bulbea)\n* PGPortfolio - source code of \"A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem\" [[Link]](https://github.com/ZhengyaoJiang/PGPortfolio)\n* Thesis - Reinforcement Learning for Automated Trading [[Link]](https://github.com/pnecchi/Thesis)\n* DQN - Reinforcement Learning for finance [[Link]](https://github.com/jjakimoto/DQN)\n* Deep-Trading-Agent - Deep Reinforcement Learning based Trading Agent for Bitcoin [[Link]](https://github.com/samre12/deep-trading-agent)\n* deep_portfolio - Use Reinforcement Learning and Supervised learning to Optimize portfolio allocation [[Link]](https://github.com/deependersingla/deep_portfolio)\n* Deep-Reinforcement-Learning-in-Stock-Trading - Using deep actor-critic model to learn best strategies in pair trading [[Link]](https://github.com/shenyichen105/Deep-Reinforcement-Learning-in-Stock-Trading)\n* Stock-Price-Prediction-LSTM - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network [[Link]](https://github.com/NourozR/Stock-Price-Prediction-LSTM)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrananqvist%2FAwesome-Quant-Machine-Learning-Trading","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgrananqvist%2FAwesome-Quant-Machine-Learning-Trading","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgrananqvist%2FAwesome-Quant-Machine-Learning-Trading/lists"}