A polynomial goal programming model for portfolio optimization based on entropy and higher moments

作者：

Highlights：

• A mean variance skewness kurtosis entropy model is proposed for portfolio optimization.

• Two types of entropy measures are compared and examined in portfolio selection with higher moments.

• A new dimension is added and corrections are made on Polynomial Goal Programming Approach.

• Out-of-sample analysis is conducted with rolling window procedure for Polynomial Goal Programming.

• Data sets are taken from two different types of markets.

摘要

•A mean variance skewness kurtosis entropy model is proposed for portfolio optimization.•Two types of entropy measures are compared and examined in portfolio selection with higher moments.•A new dimension is added and corrections are made on Polynomial Goal Programming Approach.•Out-of-sample analysis is conducted with rolling window procedure for Polynomial Goal Programming.•Data sets are taken from two different types of markets.

论文关键词：Portfolio optimization,Higher moment,Diversity index,Entropy,Portfolio performance measure

论文评审过程：Received 10 May 2017, Revised 10 October 2017, Accepted 29 October 2017, Available online 31 October 2017, Version of Record 5 November 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.056