Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15494
Title: A smoothing method for solving portfolio optimization with CVaR and applications in allocation of generation asset
Authors: Tong, X
Qi, L 
Wu, F
Zhou, H
Keywords: Allocation of generation asset
Conditional value-at-risk (CVaR)
Portfolio optimization
Smoothing method
Issue Date: 2010
Publisher: Elsevier
Source: Applied mathematics and computation, 2010, v. 216, no. 6, p. 1723-1740 How to cite?
Journal: Applied mathematics and computation 
Abstract: This paper focuses on the computation issue of portfolio optimization with scenario-based CVaR. According to the semismoothness of the studied models, a smoothing technology is considered, and a smoothing SQP algorithm then is presented. The global convergence of the algorithm is established. Numerical examples arising from the allocation of generation assets in power markets are done. The computation efficiency between the proposed method and the linear programming (LP) method is compared. Numerical results show that the performance of the new approach is very good. The remarkable characteristic of the new method is threefold. First, the dimension of smoothing models for portfolio optimization with scenario-based CVaR is low and is independent of the number of samples. Second, the smoothing models retain the convexity of original portfolio optimization problems. Third, the complicated smoothing model that maximizes the profit under the CVaR constraint can be reduced to an ordinary optimization model equivalently. All of these show the advantage of the new method to improve the computation efficiency for solving portfolio optimization problems with CVaR measure.
URI: http://hdl.handle.net/10397/15494
ISSN: 0096-3003
EISSN: 1873-5649
DOI: 10.1016/j.amc.2009.12.031
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