A higher order portfolio optimization model incorporating information entropy

被引：2

作者：

Goncalves, Guilherme ^{[1
]}

Wanke, Peter ^{[1
]}

Tan, Yong ^{[2
]}

机构：

[1] Univ Fed Rio de Janeiro, COPPEAD Grad Business Sch, Rua Paschoal Lemme 355, BR-21949900 Rio De Janeiro, Brazil

[2] Univ Bradford, Sch Management, Bradford BD7 1DP, W Yorkshire, England

来源：

INTELLIGENT SYSTEMS WITH APPLICATIONS | 2022年 / 15卷

关键词：

Modern Portfolio Theory; Mean-variance; Markowitz; MVSK model; MVSKE portfolio; Information entropy; SELECTION; DIVERSIFICATION; DECISION; RISK; FLOW;

D O I：

10.1016/j.iswa.2022.200101

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper expands the model for higher-order moments (evolving into an MVSK model with skewness and kurtosis analysis) and compares it to the classic quadratic objective function of Markowitz. Along with the MVSK analysis, we add an information entropy variable to the model taking into account the asset's informational efficiency and diversity, and trying to encompass the high uncertainty intrinsic to the market's returns and increase the model's validity. We analyze the practical effectiveness and the complexity of creating such a multi- objective portfolio model to see if we can provide more information to the investor with the new framework.

引用

页数：15

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