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Operations Research Transactions >

2017 , Vol. 21 >Issue 1: 1 - 12

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2017.01.001

CVaR robust mean-CVaR portfolio optimization  model and the solving methods

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  • 1. School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China; 2. Sun Yat-sen Business School, Sun Yat-sen University, Guangzhou 510275, China; 3. School of Mathematical Science, Huaqiao University, Quanzhou 362021, Fujian, China

Received date: 2016-09-14

  Online published: 2017-03-15

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Abstract

When calculating the optimal portfolios,  the traditional mean-risk (including variance, value-at-risk (VaR), conditional value at risk (CVaR)) optimization model often assumes that mean returns are known constant values. In actual asset allocation, however, estimation of mean return will have deviation, namely there exists risk of estimation. On the basis of estimating the risk measured by CVaR, this paper further studies CVaR robust mean-CVaR portfolio optimization model and presents two different optimization algorithms, namely, the dual method and the smoothing method. Moreover, we explore some properties and characteristics of the two methods. Finally, we give some numerical experiments to show the feasibility and effectiveness of these two methods.

Key words：  portfolio selection; CVaR robust; dual method; smoothing method; resampling

Cite this article

KANG Zhilin, LI Zhongfei . CVaR robust mean-CVaR portfolio optimization  model and the solving methods[J]. Operations Research Transactions, 2017 , 21(1) : 1 -12 . DOI: 10.15960/j.cnki.issn.1007-6093.2017.01.001

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