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An Efficient and Concise Algorithm for Convex Quadratic Programming and Its Application to Markowitz’s Portfolio Selection Model
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Technology and Investment·Volume 02 (2011)·Pages 229–239·Published 4 November 2011·DOI10.4236/ti.2011.24024
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Abstract
This paper presents a pivoting-based method for solving convex quadratic programming and then shows how to use it together with a parameter technique to solve mean-variance portfolio selection problems.
KeywordsConvex Quadratic ProgrammingMean-Variance Portfolio Selection ModelPivoting Algorithm
- R. Fletcher, “Practical Method of Optimization: Constrained Optimization,” John Wiley & Sons, New York, 1981.
- J. Nocedal and S. J. Wright, “Numerical Optimization,” Science Press of China, Beijing, 2006.
- P. Wolfe, “The Simplex Method for Quadratic Programming,” Econometrica, Vol. 27, No. 10, 1959, pp. 382-398. doi:10.2307/1909468
- H. Markowitz, “Portfolio Selection,” The Journal of Finance, Vol. 7, No. 1, 1952, pp. 77-91. doi:10.2307/2975974
- H. M. Markowitz and G. P. Todd, “Mean-Variance Analysis in Portfolio Choice and Capital Markets,” Frank J. Fabozzi Associates, Pennsylvania, 2000.
- Z. Z. Zhang, “Convex Programming: Pivoting Algorithms for Portfolio Selection and Network Optimization,” Wuhan University Press, Wuhan, 2004.
- Z. Z. Zhang, “Quadratic Programming: Algorithms for Nonlinear Programming and Portfolio Selection,” Wuhan University Press, Wuhan, 2006.
- Z. Z. Zhang, “An Efficient Method for Solving the Local Minimum of Indefinite Quadratic Programming,” 2007. http://www.numerical.rl.uk/qp/qp.html
- V. Chvatal, “Linear Programming,” W. H. Freeman Company, New York, 1983.