A stacked generalization system for automated FOREX portfolio trading

作者：

Highlights：

• We attack automated FOREX portfolio management.

• We present a machine learning-driven, stacked generalization system.

• Different machine learning algorithms are best at different cases.

• We infer subtle correlations between diverse machine learning algorithms.

• We optimally combine them to perform automated FOREX portfolio management.

摘要

•We attack automated FOREX portfolio management.•We present a machine learning-driven, stacked generalization system.•Different machine learning algorithms are best at different cases.•We infer subtle correlations between diverse machine learning algorithms.•We optimally combine them to perform automated FOREX portfolio management.

论文关键词：Forex forecasting,Algorithmic trading,Portfolio management,Machine learning,Stacked generalization

论文评审过程：Received 19 May 2017, Revised 16 July 2017, Accepted 4 August 2017, Available online 18 August 2017, Version of Record 23 August 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.08.011