Minimax portfolio optimization: empirical numerical study

X Cai, K L Teo, X Q Yang () and X Y Zhou
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X Cai: The Chinese University of Hong Kong
K L Teo: The Hong Kong Polytechnic University
X Q Yang: The Hong Kong Polytechnic University
X Y Zhou: The Chinese University of Hong Kong

Journal of the Operational Research Society, 2004, vol. 55, issue 1, 65-72

Abstract: 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.

Keywords: variance; standard deviation; portfolio selection; risk aversion measures; numerical study (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (2)

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DOI: 10.1057/palgrave.jors.2601648

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