awesome-deep-trading
github.com/cbailes/awesome-deep-trading ↗List of awesome resources for machine learning-based algorithmic trading
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me sentiment analysis resources from awesome-deep-trading"
Installation instructions →What's inside
Reinforcement Learning
- AAMDRL: Augmented Asset Management with Deep Reinforcement Learning
Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay, Jamal Atif (2020)
- AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks
Jingyuan Wang, Yang Zhang, Ke Tang, Junjie Wu, Zhang Xiong
- An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features
Ding Fengqian, Luo Chao (2020)
- An Application of Deep Reinforcement Learning to Algorithmic Trading
Thibaut Théate, Damien Ernst (2020)
- Application of Deep Q-Network in Portfolio Management
Ziming Gao, Yuan Gao, Yi Hu, Zhengyong Jiang, Jionglong Su (2020)
- A reinforcement learning model based on reward correction for quantitative stock selection
Haibo Chen, Chenyu Zhang, Yunke Li (2020)
Convolutional Neural Networks (CNNs)
- A deep learning based stock trading model with 2-D CNN trend detection
Ugur Gudelek, S. Arda Boluk, Murat Ozbayoglu, Murat Ozbayoglu (2017)
- Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach
Omer Berat Sezar, Murat Ozbayoglu (2018)
- DeepLOB: Deep Convolutional Neural Networks for Limit Order Books
Zihao Zhang, Stefan Zohren, Stephen Roberts (2019)
Resources
- A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem
Zhengyao Jiang, Dixing Xu, Jinjun Liang (2017)
- Agent Inspired Trading Using Recurrent Reinforcement Learning and LSTM Neural Networks
David W. Lu (2017)
- Algorithmic Trading and Machine Learning Based on GPU
Mantas Vaitonis, Saulius Masteika, Konstantinas Korovkinas (2018)
- An Empirical Study of Machine Learning Algorithms for Stock Daily Trading Strategy
Dongdong Lv, Shuhan Yuan, Meizi Li, Yang Xiang (2019)
- A quantitative trading method using deep convolution neural network
HaiBo Chen, DaoLei Liang, LL Zhao (2019)
- @cbailes
Patreoncontact@craigbailes.com)
Vulnerabilities
- Adversarial Attacks on Deep Algorithmic Trading Policies
Yaser Faghan, Nancirose Piazza, Vahid Behzadan, Ali Fathi (2020)
High Frequency
- Algorithmic Trading Using Deep Neural Networks on High Frequency Data
Andrés Arévalo, Jaime Niño, German Hernandez, Javier Sandoval, Diego León, Arbey Aragón (2017)
- Application of Machine Learning in High Frequency Trading of Stocks
Obi Bertrand Obi (2019)
- Deep Neural Networks in High Frequency Trading
Prakhar Ganesh, Puneet Rakheja (2018)
- Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets
Xingyu Zhou, Zhisong Pan, Guyu Hu, Siqi Tang, Cheng Zhao (2018)
Datasets
- Alpha Vantage
Free APIs in JSON and CSV formats, realtime and historical stock data, FX and cryptocurrency feeds, 50+ technical indicators
- Deep Hedging: Learning to Simulate Equity Option MarketsSimulation
Magnus Wiese, Lianjun Bai, Ben Wood, Hans Buehler (2019)
- Generating Realistic Stock Market Order StreamsSimulation
Anonymous Authors (2018)
- kaggle/Huge Stock Market Dataset
Historical daily prices and volumes of all U.S. stocks and ETFs
- Quandl
Long Short-Term Memory (LSTMs)
- A novel Deep Learning Framework: Prediction and Analysis of Financial Time Series using CEEMD and LSTM
Yong'an Zhang, Binbin Yan, Memon Aasma (2020)
- Application of Deep Learning to Algorithmic Trading, Stanford CS229
Guanting Chen, Yatong Chen, Takahiro Fushimi (2017)
- Deep Learning for Stock Market Trading: A Superior Trading Strategy?
D. Fister, J. C. Mun, V. Jagrič, T. Jagrič, (2019)
- Deep Stock Predictions
Akash Doshi, Alexander Issa, Puneet Sachdeva, Sina Rafati, Somnath Rakshit (2020)
- Performance Evaluation of Recurrent Neural Networks for Short-Term Investment Decision in Stock Market
Alexandre P. da Silva, Silas S. L. Pereira, Mário W. L. Moreira, Joel J. P. C. Rodrigues, Ricardo A. L. Rabêlo, Kashif Saleem (2020)
- Prediction Of Stock Trend For Swing Trades Using Long Short-Term Memory Neural Network Model
Varun Totakura, V. Devasekhar, Madhu Sake (2020)
Meta Analyses & Systematic Reviews
- Application of machine learning in stock trading: a review
Kok Sheng Tan, Rajasvaran Logeswaran (2018)
- A systematic review of fundamental and technical analysis of stock market predictions
Isaac kofi Nti, Adebayo Adekoya, Benjamin Asubam Weyori (2019)
- Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey
Lukas Ryll, Sebastian Seidens (2019)
- Financial Time Series Forecasting with Deep Learning: A Systematic Literature Review: 2005-2019
Omer Berat Sezer, Mehmet Ugur Gudelek, Ahmet Murat Ozbayoglu (2019)
- Reinforcement Learning in Financial Markets
Terry Lingze Meng, Matloob Khushi (2019)
Showing a sample of 123 resources. View the full list on GitHub →