Awesome-Quant-Machine-Learning-Trading

Marcos López de Prado - Advances in Financial Machine Learning

Dr Howard B Bandy - Quantitative Technical Analysis: An integrated approach to trading system development and trading management

Tony Guida - Big Data and Machine Learning in Quantitative Investment

Michael Halls-Moore - Advanced Algorithmic Trading

Jannes Klaas - Machine Learning for Finance: Data algorithms for the markets and deep learning from the ground up for financial experts and economics

Stefan Jansen - Hands-On Machine Learning for Algorithmic Trading: Design and implement smart investment strategies to analyze market behavior using the Python ecosystem

Ali N. Akansu et al. - Financial Signal Processing and Machine Learning

David Aronson - Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading

David Aronson - Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments

Ernest P. Chan - Machine Trading: Deploying Computer Algorithms to Conquer the Markets

Coursera, NYU - Guided Tour of Machine Learning in Finance

Coursera, NYU - Fundamentals of Machine Learning in Finance

Coursera, NYU - Reinforcement Learning in Finance

Coursera, NYU - Overview of Advanced Methods for Reinforcement Learning in Finance

Siraj Raval - Videos about stock market prediction using Deep Learning

QuantInsti Youtube - webinars about Machine Learning for trading

Quantopian - Webinars about Machine Learning for trading

Sentdex - Machine Learning for Forex and Stock analysis and algorithmic trading

Sentdex - Python programming for Finance (a few videos including Machine Learning)

QuantNews - Machine Learning for Algorithmic Trading 3 part series

Howard Bandy - Machine Learning Trading System Development Webinar

Ernie Chan - Machine Learning for Quantitative Trading Webinar

Hitoshi Harada, CTO at Alpaca - Deep Learning in Finance Talk

Prediction Machines - Deep Learning with Python in Finance Talk

Master Thesis presentation, Uni of Essex - Analyzing the Limit Order Book, A Deep Learning Approach

Tucker Balch - Applying Deep Reinforcement Learning to Trading

Krish Naik - Machine learning tutorials and their Application in Stock Prediction

Quantstart - Machine Learning for Trading articles

Quantopian - Lecture notebooks on ML-related statistics

Quantopian - Tutorials and notebooks tagged with Machine Learning

AAA Quants, Tom Starke Blog

RobotWealth, Kris Longmore Blog

Quantsportal, Jacques Joubert's Blog

Blackarbs blog

Hardikp, Hardik Patel blog

Chat with Traders EP042 - Machine learning for algorithmic trading with Bert Mouler

Chat with Traders EP142 - Algo trader using automation to bypass human flaws with Bert Mouler

Chat with Traders EP147 - Detective work leading to viable trading strategies with Tom Starke

Chat with Traders Quantopian 5 - Good Uses of Machine Learning in Finance with Max Margenot

Chat With Traders EP131 - Trading strategies, powered by machine learning with Morgan Slade

Better System Trader EP023 - Portfolio manager Michael Himmel talks AI and machine learning in trading

Better System Trader EP028 - David Aronson shares research into indicators that identify Bull and Bear markets

Better System Trader EP082 - Machine Learning With Kris Longmore

Better System Trader EP064 - Cryptocurrencies and Machine Learning with Bert Mouler

Better System Trader EP090 - This quants’ approach to designing algo strategies with Michael Halls-Moore

James Cumming - An Investigation into the Use of Reinforcement Learning Techniques within the Algorithmic Trading Domain

Marcos López de Prado - The 10 reasons most Machine Learning Funds fails

Zhuoran Xiong et al. - Practical Deep Reinforcement Learning Approach for Stock Trading

Gordon Ritter - Machine Learning for Trading

J.B. Heaton et al. - Deep Learning for Finance: Deep Portfolios

Justin Sirignano et al. - Universal Features of Price Formation in Financial Markets: Perspectives From Deep Learning

Marcial Messmer - Deep Learning and the Cross-Section of Expected Returns

Marcos Lopez de Prado - Ten Financial Applications of Machine Learning (Presentation Slides)

Marcos Lopez de Prado - The Myth and Reality of Financial Machine Learning (Presentation Slides)

Artur Sepp - Machine Learning for Volatility Trading (Presentation Slides)

Marcos Lopez de Prado - Market Microstructure in the Age of Machine Learning

Jonathan Brogaard - Machine Learning and the Stock Market

Xinyao Qian - Financial Series Prediction: Comparison Between Precision of Time Series Models and Machine Learning Methods

Milan Fičura - Forecasting Foreign Exchange Rate Movements with k-Nearest-Neighbour, Ridge Regression and Feed-Forward Neural Networks

Samuel Edet - Recurrent Neural Networks in Forecasting S&P 500 Index Amin Hedayati et al. - Stock Market Index Prediction Using Artificial Neural Network

Jaydip Sen et al. - A Robust Predictive Model for Stock Price Forecasting

O.B. Sezer et al. - An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework

Ritika Singh et al. - Stock prediction using deep learning

Thomas Fischera et al. - Deep learning with long short-term memory networks for financial market predictions

R.C.Cavalcante et al. - Computational Intelligence and Financial Markets: A Survey and Future Directions

E. Chong et al. - Deep Learning Networks for Stock Market Analysis and Prediction: Methodology, Data Representations, and Case Studies

Chien Yi Huang - Financial Trading as a Game: A Deep Reinforcement Learning Approach

W. Bao et al. - A deep learning framework for financial time series using stacked autoencoders and longshort term memory

Xingyu Zhou et al. - Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets

Fuli Feng et al. - Improving Stock Movement Prediction with Adversarial Training

Z. Zhao et al. - Time-Weighted LSTM Model with Redefined Labeling for Stock Trend Prediction

Arthur le Calvez, Dave Cliff - Deep Learning can Replicate Adaptive Traders in a Limit-Order-Book Financial Market

Dang Lien Minh et al. - Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network

Yue Deng et al. - Deep Direct Reinforcement Learning for Financial Signal Representation and Trading

Xiao Zhong - A comprehensive cluster and classification mining procedure for daily stock market return forecasting

J. Zhang et al. - A novel data-driven stock price trend prediction system

Ehsan Hoseinzade et al. - CNNPred: CNN-based stock market prediction using several data sources

Hyejung Chung et al. - Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction

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

Rajashree Dash et al. - A hybrid stock trading framework integrating technical analysis with machine learning techniques

E.A. Gerlein et al. - Evaluating machine learning classification for financial trading: an empirical approach

Justin Sirignano - Deep Learning for Limit Order Books

Frank Z. Xing et al. - Natural language based financial forecasting: a survey

Ziniu Hu et al. - Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction

J.W. Leung, Master Thesis, MIT - Application of Machine Learning: Automated Trading Informed by Event Driven Data

Xiao Ding et al. - Deep Learning for Event-Driven Stock Prediction

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TradingGym

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Trading-Gym

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btym

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TradzQAI

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marketneutral - pairs trading with ML

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BlackArbsCEO - Advances in Financial Machine Learning Exercises

mlfinlab - Package for Advances in Financial Machine Learning

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MachineLearningStocks - Using python and scikit-learn to make stock predictions

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AlphaAI - Use unsupervised and supervised learning to predict stocks

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SGX-Full-OrderBook-Tick-Data-Trading-Strategy - Providing the solutions for high-frequency trading (HFT) strategies using ML

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NeuralNetworkStocks - Using Python and keras to make stock predictions

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Stock-Price-Prediction-LSTM - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

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SravB - Algorithmic trading using machine learning

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Flow - High frequency AI based algorithmic trading module

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timestocome - Test-stock-prediction-algorithms

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deepstock - Technical experimentations to beat the stock market using deep learning

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qtrader - Reinforcement Learning for Portfolio Management

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stockPredictor - Predict stock movement with Machine Learning and Deep Learning algorithms

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stock_market_reinforcement_learning - Stock market environment using OpenGym with Deep Q-learning and Policy Gradient

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deep-algotrading - deep learning techniques from regression to LSTM using financial data

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deep_trader - Use reinforcement learning on stock market and agent tries to learn trading

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Deep-Trading - Algorithmic trading with deep learning experiments

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Deep-Trading - Algorithmic Trading using RNN

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Multidimensional-LSTM-BitCoin-Time-Series - Using multidimensional LSTM neural networks to create a forecast for Bitcoin price

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QLearning_Trading - Learning to trade under the reinforcement learning framework

Day-Trading-Application - Use deep learning to make accurate future stock return predictions

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bulbea - Deep Learning based Python Library for Stock Market Prediction and Modelling

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PGPortfolio - source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"

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Thesis - Reinforcement Learning for Automated Trading

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DQN - Reinforcement Learning for finance

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Deep-Trading-Agent - Deep Reinforcement Learning based Trading Agent for Bitcoin

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deep_portfolio - Use Reinforcement Learning and Supervised learning to Optimize portfolio allocation

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Deep-Reinforcement-Learning-in-Stock-Trading - Using deep actor-critic model to learn best strategies in pair trading

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Stock-Price-Prediction-LSTM - OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network