論文

査読有り
2016年

Portfolio optimization in single-period under cumulative prospect theory using genetic algorithms and bootstrap method

2016 13TH INTERNATIONAL CONFERENCE ON SERVICE SYSTEMS AND SERVICE MANAGEMENT
  • Chao Gong
  • ,
  • Chunhui Xu
  • ,
  • Masakazu Ando

記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
出版者・発行元
IEEE

Cumulative prospect theory (CPT) has become one of the most popular approaches for evaluating the behavior of decision makers under conditions of uncertainty. Substantial experimental evidence suggests that human behavior may significantly deviate from the traditional expected utility maximization framework when faced with uncertainty. The problem of portfolio selection should be revised when the investor's preference is for CPT instead of expected utility theory (EUT). However, because of the complexity of the CPT function, little research has investigated the portfolio choice problem based on CPT. In this paper, we present an approach to solve the portfolio optimization in single-period under cumulative prospect theory, based upon the coupling of genetic algorithms with bootstrap method. The computational experiments show that the behavior characteristics of CPT investors when they faced the portfolio composed of risky assets by using the method we proposed. Finally, these phenomena are discussed in this paper.


リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000390104400104&DestApp=WOS_CPL
ID情報
  • ISSN : 2161-1890
  • Web of Science ID : WOS:000390104400104

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