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Deep Learning with Gated Recurrent Unit Networks for Financial Sequence Predictions
4 references·16 citing·45 second hop
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References

  • 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*15,723 cited
  • 1970Efficient Capital Markets: A Review of Theory and Empirical Work13,616 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
  • 2005The use of data mining and neural networks for forecasting stock market returns465 cited

Cited by

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  • 2019An improved Stacking framework for stock index prediction by leveraging tree-based ensemble models and deep learning algorithms155 cited
  • 2023Financial Time Series Forecasting with the Deep Learning Ensemble Model137 cited
  • 2020Financial time series forecasting with deep learning : A systematic literature review: 2005–2019112 cited
  • 2023Forecasting Stock Market Indices Using the Recurrent Neural Network Based Hybrid Models: CNN-LSTM, GRU-CNN, and Ensemble Models99 cited
  • 2025LSTM–Transformer-Based Robust Hybrid Deep Learning Model for Financial Time Series Forecasting95 cited
  • 2020Forex exchange rate forecasting using deep recurrent neural networks93 cited
  • 2019LSTM with Wavelet Transform Based Data Preprocessing for Stock Price Prediction86 cited
  • 2020

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Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation
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