A stochastic programming approach to multicriteria portfolio optimization

Date

2013-10-01

Author

Sakar, Ceren Tuncer
Köksalan, Mustafa Murat

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We study a stochastic programming approach to multicriteria multi-period portfolio optimization problem. We use a Single Index Model to estimate the returns of stocks from a market-representative index and a random walk model to generate scenarios on the possible values of the index return. We consider expected return, Conditional Value at Risk and liquidity as our criteria. With stocks from Istanbul Stock Exchange, we make computational studies for the two and three-criteria cases. We demonstrate the tradeoffs between criteria and show that treating these criteria simultaneously yields meaningful efficient solutions. We provide insights based on our experiments.

Subject Keywords

Portfolio optimization, Stochastic programming, Market efficiency, Multicriteria, Liquidity, Conditional value at risk

URI

https://hdl.handle.net/11511/51522

Journal

JOURNAL OF GLOBAL OPTIMIZATION

DOI

https://doi.org/10.1007/s10898-012-0005-2

Collections

Department of Industrial Engineering, Article

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Citation Formats

C. T. Sakar and M. M. Köksalan, “A stochastic programming approach to multicriteria portfolio optimization,” JOURNAL OF GLOBAL OPTIMIZATION, pp. 299–314, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51522.