Article ID: | iaor20119907 |
Volume: | 8 |
Issue: | 4 |
Start Page Number: | 323 |
End Page Number: | 353 |
Publication Date: | Nov 2011 |
Journal: | Computational Management Science |
Authors: | Takeda Akiko, Gotoh Jun-ya |
Keywords: | programming: mathematical |
Several optimization approaches for portfolio selection have been proposed in order to alleviate the estimation error in the optimal portfolio. Among them are the norm‐constrained variance minimization and the robust portfolio models. In this paper, we examine the role of the norm constraint in portfolio optimization from several directions. First, it is shown that the norm constraint can be regarded as a robust constraint associated with the return vector. Second, the reformulations of the robust counterparts of the value‐at‐risk (VaR) and conditional value‐at‐risk (CVaR) minimizations contain norm terms and are shown to be highly related to the