Application of Differential Evolution Algorithms to Portfolio Optimization Problems using Loan

• Kiyoharu Tagawa

  School of Science and Engineering, Kindai University

• Orito Yukiko

  Graduate School of Humanities and Social Sciences, Hiroshima University

Bibliographic Information

Other Title

• 融資を利用したポートフォリオ最適化問題に対する差分進化アルゴリズムの適用
• A Study of GP (Genotype-Phenotype) Mapping
• GP（Genotype-Phenotype）写像に関する一考察

Abstract

In this paper, portfolio optimization using loan is formulated as a chance constrained problem in which the money borrowed from a loan is invested in risk assets. Then the chance constrained problem is transformed into a deterministic optimization problem that has an equality constraint. In order to apply conventional Differential Evolution (DE) algorithms to the constrained optimization problem effectively, two types of Genotype-Phenotype (GP) mappings, namely a conventional GP mapping and a newly proposed GP mapping, are compared. As a result of numerical experiments including a two-way analysis of variance (two-way ANOVA), it is shown that the proposed GP mapping outperforms the conventional one because the former enhances the quality of solutions obtained by DE algorithms. By using historical data of assets, an advantage of the investment using loan is also confirmed.

Journal

• Transaction of the Japanese Society for Evolutionary Computation

  Transaction of the Japanese Society for Evolutionary Computation 12 (2), 26-35, 2021

  The Japanese Society for Evolutionary Computation

Details

• CRID: 1390009294937755776
• NII Article ID: 130008141292
• DOI: 10.11394/tjpnsec.12.26
• ISSN: 21857385
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed