Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies

作者：

Highlights：

• Deep learning networks are applied to stock market analysis and prediction.

• A comprehensive analysis with different data representation methods is offered.

• Five-minute intraday data from the Korean KOSPI stock market is used.

• The network applied to residuals of autoregressive model improves prediction.

• Covariance estimation for market structure analysis is improved with the network.

摘要

•Deep learning networks are applied to stock market analysis and prediction.•A comprehensive analysis with different data representation methods is offered.•Five-minute intraday data from the Korean KOSPI stock market is used.•The network applied to residuals of autoregressive model improves prediction.•Covariance estimation for market structure analysis is improved with the network.

论文关键词：Stock market prediction,Deep learning,Multilayer neural network,Covariance estimation

论文评审过程：Received 15 November 2016, Revised 15 April 2017, Accepted 16 April 2017, Available online 22 April 2017, Version of Record 28 April 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.04.030