کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5076886 | 1374106 | 2013 | 9 صفحه PDF | دانلود رایگان |
The tail mean-variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean-variance framework. The tail mean-variance criterion does not satisfy these properties, however, and the precise optimal solution typically requires the use of numerical methods. We use a convex optimization method and a mean-variance characterization to find an explicit and easily implementable solution for the tail mean-variance model. When a risk-free asset is available, the optimal portfolio is altered in a way that differs from the classical mean-variance setting. A complete solution to the optimal portfolio in the presence of a risk-free asset is also provided.
⺠We focus on the risk of rare but large losses. ⺠Portfolio optimization under the tail mean-variance criterion is considered. ⺠We provide an explicit and easily implementable optimal portfolio. ⺠A complete solution is also given when a risk-free asset is present.
Journal: Insurance: Mathematics and Economics - Volume 52, Issue 2, March 2013, Pages 213-221