Computation of mean-semivariance efficient sets by the Critical Line Algorithm
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The general mean-semivariance portfolio optimization problem seeks to determine the efficient frontier by solving a parametric non-quadratic programming problem. In this paper it is shown how to transform this problem into a general mean-variance optimization problem, hence the Critical Line Algorithm is applicable. This paper also discusses how to implement the critical line algorithm to save storage and reduce execution time.
KeywordsMean-variance efficient frontier mean-semivariance efficient frontier historical returns Critical Line Algorithm
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- A.J. King and D.L. Jensen, Linear-quadratic efficient frontiers for portfolio optimization, RC 16524, IBM Research Report (1991).Google Scholar
- H.M. Markowitz, The optimization of the quadratic function subject to linear constraints, Naval Res. Log. Quarterly 3 (1956) 111–133.Google Scholar
- H.M. Markowitz,Portfolio Selection, Efficiency Diversification of Investments, Cowles Foundation Monograph 16 (Yale University Press, 1959 2nd ed.: Basil Blackwell, Cambridge, 1991).Google Scholar
- H.M. Markowitz,Mean-Variance Analysis in Portfolio Choice and Capital Markets (Basil Blackwell, Cambridge, 1987).Google Scholar
- H.M. Markowitz, P. Todd, G.L. Xu and Y. Yamane, Fast computation of mean-variance efficient sets using historical covariance, J. Fin. Eng. (1991), to appear.Google Scholar