Portfolio Optimization Using Distortion Risk Measures

Speaker: Prof. Sung Yong PARK
Associate Professor, School of Economics, Chung-Ang University

Date: 8 March, 2019 (Friday)
Time: 3:00 p.m.
Venue: E22-2013

Abstract
The mean-variance (MV) efficient portfolio selection method proposed by Markowitz is one of the most frequently used approaches to the portfolio optimization problem. However, it is well known that this approach has some critical drawbacks. In this paper, we propose an optimal portfolio selection rule using various distortion risk measures. The proposed approach can compensate for the pessimism of economic agents, which is especially important for decision making of those at risk. The procedure is illustrated by four well-known datasets. To evaluate the performance of several portfolio strategies, we compare the in- and out-of-sample value at risk, conditional value at risk, Sharpe ratio, certainty equivalent return, maximum drawdown, and portfolio turnover of multiple portfolio selection strategies. As will be shown, the proposed portfolio strategy outperforms other well-known strategies. In addition, we provide the portfolio selection rule that minimizes risk, as well as maximizes return.