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Beating the Stock Market with a Deep Reinforcement Learning Day Trading System
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Beating the Stock Market with a Deep Reinforcement Learning Day Trading System (2020)Beating the Stock Market with a Deep Rein…Trading financial indices with reinforcement learning agents (2018)Trading financial indices wit…Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning (2018)Improving financial trading d…Adversarial Deep Reinforcement Learning in Portfolio Management (2018)Adversarial Deep Reinforcemen…Advances in Financial Machine Learning (2018)Advances in Financial Machine…An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown (2017)An adaptive portfolio trading…A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (2017)A Deep Reinforcement Learning…Deep Learning for Finance: Deep Portfolios (2016)Deep Learning for Finance: De…Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Deep Direct Reinforcement Lea…Forecasting S&P 500 index using artificial neural networks and design of experiments (2013)Forecasting S&P 500 index usi…Technical analysis: the complete resource for financial market technicians (2011)Technical analysis: the compl…Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Surveying stock market foreca…An automated FX trading system using adaptive reinforcement learning (2005)An automated FX trading syste…Adaptive stock trading with dynamic asset allocation using reinforcement learning (2005)Adaptive stock trading with d…Learning to trade via direct reinforcement (2001)Learning to trade via direct …Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation (2000)Foundations of Technical Anal…Performance functions and reinforcement learning for trading systems and portfolios (1998)Performance functions and rei…Exposition of a New Theory on the Measurement of Risk (1954)Portfolio Selection: Efficient Diversification of Investments (1959)Mutual Fund Performance (1966)PAMR: Passive aggressive mean reversion strategy for portfolio selection (2012)Online portfolio selection (2014)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Forecasting stock market movement direction with support vector machine (2004)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Using artificial neural network models in stock market index prediction (2011)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Optimum consumption and portfolio rules in a continuous-time model (1971)Option pricing: A simplified approach (1979)Cryptocurrency portfolio management with deep reinforcement learning (2017)DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2019)Mean Reversion in Stock Prices: Evidence and Implications (1987)Mean reversion in stock prices (1988)The Sharpe Ratio (1994)Deep learning-based feature engineering for stock price movement prediction (2018)Deep learning for financial applications : A survey (2020)Applications of deep learning in stock market prediction: Recent progress (2021)A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)NSE Stock Market Prediction Using Deep-Learning Models (2018)Stock Market Prediction Using LSTM Recurrent Neural Network (2020)PORTFOLIO SELECTION* (1952)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? 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  • 2016Deep Direct Reinforcement Learning for Financial Signal Representation and Trading821 cited
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  • 2018Adversarial Deep Reinforcement Learning in Portfolio Management

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122 cited
  • 2018Trading financial indices with reinforcement learning agents117 cited
  • 2005Adaptive stock trading with dynamic asset allocation using reinforcement learning81 cited
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