Minimax portfolio optimization: empirical numerical study

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.