Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm

@article{Hsieh2011ForecastingSM,
  title={Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm},
  author={T. Hsieh and Hsiao-Fen Hsiao and W. Yeh},
  journal={Appl. Soft Comput.},
  year={2011},
  volume={11},
  pages={2510-2525}
}
  • T. Hsieh, Hsiao-Fen Hsiao, W. Yeh
  • Published 2011
  • Computer Science
  • Appl. Soft Comput.
  • This study presents an integrated system where wavelet transforms and recurrent neural network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are combined for stock price forecasting. The system comprises three stages. First, the wavelet transform using the Haar wavelet is applied to decompose the stock price time series and thus eliminate noise. Second, the RNN, which has a simple architecture and uses numerous fundamental and technical indicators, is applied to… CONTINUE READING
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