On the Use of Optimization Models for Portfolio Selection: A Review and Some Computational Results
AbstractPortfolio theory deals with the question of how to allocate resources among several competing alternatives (stocks, bonds), many of which have an unknown outcome. In this paper we provide an overview of different portfolio models with emphasis on the corresponding optimization problems. For the classical Markowitz mean-variance model we present computational results, applying a dual algorithm for constrained optimization. Citation Copyright 1994 by Kluwer Academic Publishers.
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 7 (1994)
Issue (Month): 4 ()
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- X. Cui & X. Zheng & S. Zhu & X. Sun, 2013. "Convex relaxations and MIQCQP reformulations for a class of cardinality-constrained portfolio selection problems," Journal of Global Optimization, Springer, vol. 56(4), pages 1409-1423, August.
- Xi-li Zhang & Wei-Guo Zhang & Wei-jun Xu & Wei-Lin Xiao, 2010. "Possibilistic Approaches to Portfolio Selection Problem with General Transaction Costs and a CLPSO Algorithm," Computational Economics, Society for Computational Economics, vol. 36(3), pages 191-200, October.
- Ehrgott, Matthias & Klamroth, Kathrin & Schwehm, Christian, 2004. "An MCDM approach to portfolio optimization," European Journal of Operational Research, Elsevier, vol. 155(3), pages 752-770, June.
- Pankaj Gupta & Mukesh Mehlawat & Garima Mittal, 2012. "Asset portfolio optimization using support vector machines and real-coded genetic algorithm," Journal of Global Optimization, Springer, vol. 53(2), pages 297-315, June.
- Panagiotis Xidonas & George Mavrotas & John Psarras, 2010. "Equity portfolio construction and selection using multiobjective mathematical programming," Journal of Global Optimization, Springer, vol. 47(2), pages 185-209, June.
- Deng, Xiao-Tie & Li, Zhong-Fei & Wang, Shou-Yang, 2005. "A minimax portfolio selection strategy with equilibrium," European Journal of Operational Research, Elsevier, vol. 166(1), pages 278-292, October.
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