Tail risk measures and portfolio selection

Abstract

Since Markowitz[13] propose the mean-variance efficient portfolio selection method it has been one of the frequently used approach to the portfolio optimization problem. However, as we know, this approach has critical draw backs such as unstable assets weights and poor forecasting performance due to the estimation error. In this study, we propose an improved portfolio selection rules using various distortion functions. Our approach can make up for the pessimism of economic agents which is important for decision making. We illustrate the procedure by four well-known datasets. We also evaluate the performance of proposed and many other portfolio strategies to compare the in- and out-of-sample value at risk, conditional value at risk and Sharpe ratio. Empirical studies show that the proposed portfolio strategy outperforms many other strategies for most of evaluation measures. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.