Interval random dependent-chance programming and its application to portfolio selection

Authors:
Wei Chen;Shaohua Tan
Affiliations:
Department of Machine Intelligence, School of EECS, Peking University, Beijing, China;Department of Machine Intelligence, School of EECS, Peking University, Beijing, China
Venue:
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Year:
2009

Citing 3
Cited 1

Interval analysis and fuzzy set theory

Fuzzy Sets and Systems - Special issue: Interfaces between fuzzy set theory and interval analysis
Fuzzy random dependent-chance programming

IEEE Transactions on Fuzzy Systems
A class of linear interval programming problems and its application to portfolio selection

IEEE Transactions on Fuzzy Systems

Worst-case VaR and robust portfolio optimization with interval random uncertainty set

Expert Systems with Applications: An International Journal

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Abstract

When employing fuzzy random variable in some real programming problems, it is not easy to specify the fuzzy values of random variables. But it is relatively easy to obtain the boundaries of the values of random variables. Hence, it is a good idea for people to determine the values of random variables as intervals. In this paper, we introduce the framework of interval random variable and interval random dependent-chance programming model. To pay attentions to both randomness and incompleteness of financial environment, we build the portfolio selection model by quantifying the stock return as interval random variable under this framework. Some computational results are discussed that demonstrate the potentially significant economic benefits of investing in portfolios computed using classical models and the model introduced here. The benefits are achieved at relatively high performance and low cost.