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Deep learning in the Chinese stock market: The role of technical indicators
16 references·2 citing·49 second hop
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References

  • 2006Investor Sentiment and the Cross‐Section of Stock Returns6,042 cited
  • 2007Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?2,916 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2014Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media1,249 cited
  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 2014Forecasting the Equity Risk Premium: The Role of Technical Indicators1,001 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
  • 2015Deep learning for event-driven stock prediction675 cited
  • 2017Can Twitter Help Predict Firm-Level Earnings and Stock Returns?606 cited
  • 2021Machine learning in the Chinese stock market593 cited
  • 2014Investor Attention and Stock Market Volatility569 cited
  • 2018ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module373 cited
  • 2020Stock price prediction using deep learning and frequency decomposition373 cited
  • 2020Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong

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370 cited
  • 2022Corporate social responsibility (CSR) performance and green innovation: Evidence from China290 cited
  • 2017The importance of fear: investor sentiment and stock market returns207 cited
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    • 2022Stock index futures price prediction using feature selection and deep learning30 cited
    • 2023A Novel Approach of Stock Price Direction and Price Prediction Based on Investor’s Sentiments27 cited