Mean-variance model for portfolio optimization with background risk based on uncertainty theory. Issue 3 (3rd April 2018)

• Record Type: Journal Article
• Authors: Zhai, Jia; Bai, Manying
• Is Part Of: International journal of general systems. Volume 47:Issue 3(2018)
• Page Start: 294
• Page End: 312
• Publication Date: 2018-04-03
• Subjects: Uncertainty theory -- portfolio optimization -- mean-variance model -- background risk -- liquidity -- portfolio frontier; System theory -- Periodicals; 003
• DOI: 10.1080/03081079.2017.1414210
• Languages: English
• ISSNs: 0308-1079

Abstract

Abstract: The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.