Mean-variance adjusting model for portfolio selection problem with fuzzy random returns

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we consider portfolio adjusting problem in the environment with multiple uncertainties. We establish two kinds of mean-variance adjusting models. The first one is formulated by only taking into account the transaction costs, and the second one is established by simultaneously considering transaction costs and minimum transaction lots. In the situation that all the returns are symmetrical triangular fuzzy random variables, these two models are converted into equivalent deterministic forms which are mixed-integer nonlinear programming models. Finally, a numerical example is given to illustrate the modelling idea.

Original languageEnglish
Title of host publicationProceedings - 2014 7th International Joint Conference on Computational Sciences and Optimization, CSO 2014
EditorsLean Yu, Qing Zhu, Jian Chai, Jian Chai, Shouyang Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages83-87
Number of pages5
ISBN (Electronic)9781479953721
DOIs
StatePublished - 14 Oct 2014
Event7th International Joint Conference on Computational Sciences and Optimization, CSO 2014 - Beijing, China
Duration: 4 Jul 20146 Jul 2014

Publication series

NameProceedings - 2014 7th International Joint Conference on Computational Sciences and Optimization, CSO 2014

Conference

Conference7th International Joint Conference on Computational Sciences and Optimization, CSO 2014
Country/TerritoryChina
CityBeijing
Period4/07/146/07/14

Keywords

  • fuzzy random variable
  • mean-variance model
  • portfolio adjusting problem
  • portfolio optimization

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