Risk management in portfolio applications of non-convex stochastic programming

Li-Ping Pang, Shuang Chen and Jin-He Wang

Applied Mathematics and Computation, 2015, vol. 258, issue C, 565-575

Abstract: In this paper, we investigate a method to hedge nonconvex stochastic programming with CVaR constraints and apply the sample average approximation (SAA) method based on bundle method to solve it. Under some moderate conditions, the SAA solution converges to its true counterpart with probability approaching one. This technique is suitable for using by investment companies, brokerage firms, mutual funds, and any business that evaluates risks. It can be combined with analytical or scenario-based methods to optimize portfolios in which case the calculations often come down to non-convex programming. Finally, we illustrate our method by considering several portfolios in the Chinese stocks market.

Keywords: Non-convex stochastic programming; Risk management; Portfolio; Bundle methods (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:258:y:2015:i:c:p:565-575

DOI: 10.1016/j.amc.2015.02.031

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