Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7960
Title: Minimax portfolio optimization : empirical numerical study
Authors: Cai, X
Teo, KL
Yang, XQ 
Zhou, XY
Keywords: Numerical study
Portfolio selection
Risk aversion measures
Standard deviation
Variance
Issue Date: 2004
Publisher: Palgrave Macmillan
Source: Journal of the Operational Research Society, 2004, v. 55, no. 1, p. 65-72 How to cite?
Journal: Journal of the Operational Research Society 
Abstract: In this paper, we carry out the empirical numerical study of the l ∞ portfolio selection model where the objective is to minimize the maximum individual risk. We compare the numerical performance of this model with that of the Markowitz's quadratic programming model by using real data from the Stock Exchange of Hong Kong. Our computational results show that the l ∞, model has a similar performance to the Markowitz's model and that the l∞, model is not sensitive to the data. For the situation with only two assets, we establish that the expected return of the minimum variance model is less than that of the minimum l∞ model when both variance and the return rate of one asset is less than the corresponding values of another asset.
URI: http://hdl.handle.net/10397/7960
ISSN: 0160-5682
EISSN: 1476-9360
DOI: 10.1057/palgrave.jors.2601648
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