Forecasting stock market crisis events using deep and statistical machine learning techniques

作者：

Highlights：

• Highlights

• We examine crash event propagation in international stock markets.

• We investigate transmission mechanisms across markets.

• We devise a forecasting mechanism for stock market crash events.

• We leverage bleeding-edge advances in Deep Learning.

• Our results provide strong evidence that stock market crises exhibit persistence.

摘要

Highlights•We examine crash event propagation in international stock markets.•We investigate transmission mechanisms across markets.•We devise a forecasting mechanism for stock market crash events.•We leverage bleeding-edge advances in Deep Learning.•Our results provide strong evidence that stock market crises exhibit persistence.

论文关键词：Stock market crashes,Forecasting,Random forests,Support vector machines,Deep learning,XGBoost

论文评审过程：Received 10 April 2018, Revised 13 June 2018, Accepted 14 June 2018, Available online 28 June 2018, Version of Record 27 July 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.032