CNNpred: CNN-based stock market prediction using a diverse set of variables

作者：

Highlights：

• 3D-CNNpred is the first 3-dimensional CNN model designed for stock market prediction.

• CNNpred successfully combines various sources of information for prediction.

• CNNs filters are designed to better handle financial data.

• Deep CNN-based framework significantly outperforms shallow ANNs.

• CNNpred is profitable in 4 out of 5 tested indices in presence of transaction costs.

摘要

•3D-CNNpred is the first 3-dimensional CNN model designed for stock market prediction.•CNNpred successfully combines various sources of information for prediction.•CNNs filters are designed to better handle financial data.•Deep CNN-based framework significantly outperforms shallow ANNs.•CNNpred is profitable in 4 out of 5 tested indices in presence of transaction costs.

论文关键词：Stock markets prediction,Deep learning,Convolutional neural networks,CNN,Feature extraction

论文评审过程：Received 6 September 2018, Revised 15 March 2019, Accepted 16 March 2019, Available online 20 March 2019, Version of Record 15 April 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.03.029