In this talk, I shall investigate dynamic portfolio management using semivariance of portfolio payoff as a portfolio risk measure. Comparing with variance, semivariance is considered to be a more plausible risk measure because semivariance applies penalties to adverse situations only. However, in the literature, it was shown that mean-semivariance optimization under the Black-Scholes model has no optimal solution. Motivated by this non-existence result, I shall establish necessary and sufficient conditions under which the mean-semivariance optimization possesses an optimal solution. I shall suggest the models under which such sufficient conditions are satisfied, then, in this case, we can obtain the explicit optimal solution; such models can be applied to the themes of insurance. Besides, I shall establish that utility-semivariance optimization possesses an optimal solution under the Black-Scholes model. In numerical studies, among mostly encountered market values of different model parameters, it is astonishing to observe that embedding downside risk measure into utility maximization framework can significantly reduce the downside risk of the optimal portfolio payoff with an asymmetrically tiny loss in utility. This talk is based on joint works with Paolo Guasoni, Phillip Yam, and Harry Zheng.
Bio: Dr. Kwok Chuen (Ryan) Wong is an Assistant Professor at the School of Mathematical Sciences, Dublin City University. His research interests are in the areas of stochastic control and mathematical finance. More specifically, he researches on solving various portfolio selection problems, some of which have time inconsistency issues. Recently, he is working on applying semivariance as a risk measure for investment management. Before joining DCU, he received a joint-university PhD in Mathematical Finance and Actuarial Science from Imperial College London and the University of Hong Kong.