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Portfolio Optimization-Based Stock Prediction Using Long-Short Term Memory Network in Quantitative Trading
12 references·10 citing·44 second hop
Portfolio Optimization-Based Stock Prediction Using Long-Short Term Memory Network in Quantitative Trading (2020)Portfolio Optimization-Based Stock Predic…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…Deep Learning for Finance: Deep Portfolios (2016)Deep Learning for Finance: De…Sentiment analysis on social media for stock movement prediction (2015)Sentiment analysis on social …Forecasting exchange rate using deep belief networks and conjugate gradient method (2015)Forecasting exchange rate usi…Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Comparison of ARIMA and Artif…60 Years of portfolio optimization: Practical challenges and current trends (2013)60 Years of portfolio optimiz…Neural network techniques for financial performance prediction: integrating fundamental and technical analysis (2003)Neural network techniques for…Common risk factors in the returns on stocks and bonds (1993)Common risk factors in the re…An Empirical Investigation of the Arbitrage Pricing Theory (1980)An Empirical Investigation of…PORTFOLIO SELECTION* (1952)PORTFOLIO SELECTION*Deep learning for financial forecasting: A review of recent trends (2025)Deep learning for financial f…Enhancing portfolio management using artificial intelligence: literature review (2024)Enhancing portfolio managemen…Deep reinforcement learning for portfolio selection (2024)Deep reinforcement learning f…Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization (2023)Harnessing a Hybrid CNN-LSTM …Forecasting Stock Market Indices Using the Recurrent Neural Network Based Hybrid Models: CNN-LSTM, GRU-CNN, and Ensemble Models (2023)Forecasting Stock Market Indi…Connectedness and portfolio hedging between NFTs segments, American stocks and cryptocurrencies Nexus (2023)Connectedness and portfolio h…StockGAN: robust stock price prediction using GAN algorithm (2022)StockGAN: robust stock price …Stock price prediction based on LSTM and LightGBM hybrid model (2022)Stock price prediction based …Markowitz Mean-Variance Portfolio Optimization with Predictive Stock Selection Using Machine Learning (2022)Markowitz Mean-Variance Portf…A Prediction Model of CNN-TLSTM for USD/CNY Exchange Rate Prediction (2021)A Prediction Model of CNN-TLS…The Adjustment of Stock Prices to New Information (1969)Efficient Capital Markets: II (1991)Twitter mood predicts the stock market (2011)Natural language based financial forecasting: a survey (2017)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020)Forecasting with artificial neural networks: (1998)An artificial neural network (p,d,q) model for timeseries forecasting (2009)Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)A systematic review of fundamental and technical analysis of stock market predictions (2019)A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction (2021)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Risk, Return, and Equilibrium: Empirical Tests (1973)The Cross-Section of Expected Stock Returns (1992)Illiquidity and stock returns: cross-section and time-series effects (2002)A five-factor asset pricing model (2014)Coherent Measures of Risk (1999)Optimization of conditional value-at-risk (2000)Building Diversified Portfolios that Outperform Out of Sample (2016)Decision-making for financial trading: A fusion approach of machine learning and portfolio selection (2018)Portfolio optimization with return prediction using deep learning and machine learning (2020)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Efficient Capital Markets: II (1991)Fundamentals and Stock Returns in Japan (1991)Alternative factor specifications, security characteristics, and the cross-section of expected stock returns1We are especially grateful to Eugene Fama (a referee), an anonymous referee and Bill Schwert (the editor) for insightful and constructive suggestions. We also thank Wayne Ferson, Ken French, Will Goetzmann, Craig Holden, Ravi Jagannathan, Bob Jennings, Bruce Lehmann, Josef Lakonishok, Richard Roll, participants at the 1997 Meetings of the Western Finance Association, the 1997 UCLA/USC/UC Irvine conference, the November 1997 Asset Pricing Meeting of the National Bureau of Economic Research, the Atlanta Forum, and seminars at Columbia, Indiana, Florida, New York, Tulane, and Yale Universities; Eugene Fama and Ken French for providing part of the data used in this study; and Christoph Schenzler for excellent programming assistance. The second author acknowledges support from the Dean's Fund for Research and the Financial Markets Research Center at Vanderbilt University. We are responsible for remaining errors. This paper was formerly titled `A Re-Examination of Security Return Anomalies'.1 (1998)A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)NSE Stock Market Prediction Using Deep-Learning Models (2018)Deep learning for financial applications : A survey (2020)Stock Market Prediction Using LSTM Recurrent Neural Network (2020)Does the Stock Market Overreact? (1985)Hierarchical structure in financial markets (1999)Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? (2007)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)On Persistence in Mutual Fund Performance (1997)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Forecasting stock market movement direction with support vector machine (2004)Temporal Relational Ranking for Stock Prediction (2019)Conditional value-at-risk for general loss distributions (2002)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)The relationship between corporate social responsibility and shareholder value: an empirical test of the risk management hypothesis (2008)
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References

  • 1993Common risk factors in the returns on stocks and bonds26,615 cited
  • 1952PORTFOLIO SELECTION*13,480 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 1980An Empirical Investigation of the Arbitrage Pricing Theory1,249 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies833 cited
  • 2016Deep Learning for Finance: Deep Portfolios765 cited
  • 201360 Years of portfolio optimization: Practical challenges and current trends633 cited
  • 2015Sentiment analysis on social media for stock movement prediction626 cited
  • 2014Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction579 cited
  • 2003Neural network techniques for financial performance prediction: integrating fundamental and technical analysis380 cited
  • 2015Forecasting exchange rate using deep belief networks and conjugate gradient method234 cited

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