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High-performance stock index trading via neural networks and trees
16 references·1 citing·41 second hop
High-performance stock index trading via neural networks and trees (2020)High-performance stock index trading via …Combining Principal Component Analysis, Discrete Wavelet Transform and XGBoost to trade in the financial markets (2019)Combining Principal Component…Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Statistical and Machine Learn…ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module (2018)ModAugNet: A new forecasting …Empirical Asset Pricing via Machine Learning (2018)Empirical Asset Pricing via M…Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…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…Forecasting daily stock market return using dimensionality reduction (2016)Forecasting daily stock marke…Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Deep neural networks, gradien…Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Deep Direct Reinforcement Lea…Evaluating multiple classifiers for stock price direction prediction (2015)Evaluating multiple classifie…Customer churn prediction using improved balanced random forests (2008)Customer churn prediction usi…The Capital Asset Pricing Model: Theory and Evidence (2004)The Capital Asset Pricing Mod…Common risk factors in the returns on stocks and bonds (1993)Common risk factors in the re…Economic Forecast Evaluation: Profits versus the Conventional Error Measures (1991)Economic Forecast Evaluation:…Artificial Intelligence and Machine Learning in Financial Services to Improve the Business System (2023)Artificial Intelligence and M…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)On Persistence in Mutual Fund Performance (1997)Capital Account Liberalization: Theory, Evidence, and Speculation (2007)Political connections and the cost of equity capital (2012)Impact of ESG factors on firm risk in Europe (2016)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A five-factor asset pricing model (2014)Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series (2019)Literature review: Machine learning techniques applied to financial market prediction (2019)Deep learning for financial applications : A survey (2020)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)Applications of deep learning in stock market prediction: Recent progress (2021)Does the Stock Market Overreact? 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References

  • 1993Common risk factors in the returns on stocks and bonds26,615 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2004The Capital Asset Pricing Model: Theory and Evidence2,057 cited
  • 2018Statistical and Machine Learning forecasting methods: Concerns and ways forward1,515 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 Direct Reinforcement Learning for Financial Signal Representation and Trading821 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
  • 2015Evaluating multiple classifiers for stock price direction prediction597 cited
  • 1991Economic Forecast Evaluation: Profits versus the Conventional Error Measures453 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach433 cited
  • 2008Customer churn prediction using improved balanced random forests412 cited
  • 2016Forecasting daily stock market return using dimensionality reduction395 cited
  • 2018Empirical Asset Pricing via Machine Learning

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384 cited
  • 2018ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module373 cited
  • 2019Combining Principal Component Analysis, Discrete Wavelet Transform and XGBoost to trade in the financial markets290 cited
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    • 2023Artificial Intelligence and Machine Learning in Financial Services to Improve the Business System8 cited