awesome-deep-trading

List of code, papers, and resources for AI/deep learning/machine learning/neural networks applied to algorithmic trading.

Open access: all rights granted for use and re-use of any kind, by anyone, at no cost, under your choice of either the free MIT License or Creative Commons CC-BY International Public License.

© 2021 Craig Bailes (@cbailes | Patreon | contact@craigbailes.com)

Contents

• Papers
  • Meta Analyses & Systematic Reviews
  • Convolutional Neural Networks (CNNs)
  • Long Short-Term Memory (LSTMs)
  • Generative Adversarial Networks (GANs)
  • High Frequency
  • Portfolio
  • Reinforcement Learning
  • Vulnerabilities
  • Cryptocurrency
  • Social Processing
    • Behavioral Analysis
    • Sentiment Analysis
• Repositories
  • Generative Adversarial Networks (GANs)
  • Guides
  • Cryptocurrency
  • Datasets
    • Simulation
• Resources
  • Presentations
  • Courses
  • Further Reading

Papers

• Classification-based Financial Markets Prediction using Deep Neural Networks - Matthew Dixon, Diego Klabjan, Jin Hoon Bang (2016)
• Deep Learning for Limit Order Books - Justin Sirignano (2016)
• High-Frequency Trading Strategy Based on Deep Neural Networks - Andrés Arévalo, Jaime Niño, German Hernández, Javier Sandoval (2016)
• 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)
• Deep Hedging - Hans Bühler, Lukas Gonon, Josef Teichmann, Ben Wood (2018)
• Stock Trading Bot Using Deep Reinforcement Learning - Akhil Raj Azhikodan, Anvitha G. K. Bhat, Mamatha V. Jadhav (2018)
• Financial Trading as a Game: A Deep Reinforcement Learning Approach - Chien Yi Huang (2018)
• Practical Deep Reinforcement Learning Approach for Stock Trading - Zhuoran Xiong, Xiao-Yang Liu, Shan Zhong, Hongyang Yang, Anwar Walid (2018)
• Algorithmic Trading and Machine Learning Based on GPU - Mantas Vaitonis, Saulius Masteika, Konstantinas Korovkinas (2018)
• A quantitative trading method using deep convolution neural network - HaiBo Chen, DaoLei Liang, LL Zhao (2019)
• Deep learning in exchange markets - Rui Gonçalves, Vitor Miguel Ribeiro, Fernando Lobo Pereira, Ana Paula Rocha (2019)
• Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks - Omer Berat Sezer, Ahmet Murat Ozbayoglu (2019)
• Deep Reinforcement Learning for Financial Trading Using Price Trailing - Konstantinos Saitas Zarkias, Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas (2019)
• Cooperative Multi-Agent Reinforcement Learning Framework for Scalping Trading - Uk Jo, Taehyun Jo, Wanjun Kim, Iljoo Yoon, Dongseok Lee, Seungho Lee (2019)
• Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning - Gyeeun Jeong, Ha Young Kim (2019)
• Deep Execution - Value and Policy Based Reinforcement Learning for Trading and Beating Market Benchmarks - Kevin Dabérius, Elvin Granat, Patrik Karlsson (2019)
• An Empirical Study of Machine Learning Algorithms for Stock Daily Trading Strategy - Dongdong Lv, Shuhan Yuan, Meizi Li, Yang Xiang (2019)
• Recipe for Quantitative Trading with Machine Learning - Daniel Alexandre Bloch (2019)
• Exploring Possible Improvements to Momentum Strategies with Deep Learning - Adam Takács, X. Xiao (2019)
• Enhancing Time Series Momentum Strategies Using Deep Neural Networks - Bryan Lim, Stefan Zohren, Stephen Roberts (2019)
• Multi-Agent Deep Reinforcement Learning for Liquidation Strategy Analysis - Wenhang Bao, Xiao-yang Liu (2019)
• Deep learning-based feature engineering for stock price movement prediction - Wen Long, Zhichen Lu, Lingxiao Cui (2019)
• Review on Stock Market Forecasting & Analysis - Anirban Bal, Debayan Ganguly, Kingshuk Chatterjee (2019)
• Neural Networks as a Forecasting Tool in the Context of the Russian Financial Market Digitalization - Valery Aleshin, Oleg Sviridov, Inna Nekrasova, Dmitry Shevchenko (2020)
• Deep Hierarchical Strategy Model for Multi-Source Driven Quantitative Investment - Chunming Tang, Wenyan Zhu, Xiang Yu (2019)
• Finding Efficient Stocks in BSE100: Implementation of Buffet Approach INTRODUCTION - Sherin Varghese, Sandeep Thakur, Medha Dhingra (2020)
• Deep Learning in Asset Pricing - Luyang Chen, Markus Pelger, Jason Zhu (2020)

Meta Analyses & Systematic Reviews

• Application of machine learning in stock trading: a review - Kok Sheng Tan, Rajasvaran Logeswaran (2018)
• Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey - Lukas Ryll, Sebastian Seidens (2019)
• Reinforcement Learning in Financial Markets - Terry Lingze Meng, Matloob Khushi (2019)
• Financial Time Series Forecasting with Deep Learning: A Systematic Literature Review: 2005-2019 - Omer Berat Sezer, Mehmet Ugur Gudelek, Ahmet Murat Ozbayoglu (2019)
• A systematic review of fundamental and technical analysis of stock market predictions - Isaac kofi Nti, Adebayo Adekoya, Benjamin Asubam Weyori (2019)

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)

Long Short-Term Memory (LSTMs)

• Application of Deep Learning to Algorithmic Trading, Stanford CS229 - Guanting Chen, Yatong Chen, Takahiro Fushimi (2017)
• Stock Prices Prediction using Deep Learning Models - Jialin Liu, Fei Chao, Yu-Chen Lin, Chih-Min Lin (2019)
• Deep Learning for Stock Market Trading: A Superior Trading Strategy? - D. Fister, J. C. Mun, V. Jagrič, T. Jagrič, (2019)
• 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)
• Research on financial assets transaction prediction model based on LSTM neural network - Xue Yan, Wang Weihan & Miao Chang (2020)
• [Prediction Of Stock Trend For Swing Trades Usi