Seminar by Dr. Pengyu WEI from Nanyang Business School, Nanyang Technological University

Tail Mean-Variance (TMV) has emerged from the actuarial community as a criterion for risk management and portfolio selection, with a focus on extreme losses. The existing literature on portfolio optimization under the TMV criterion relies on the plug-in approach that substitutes the unknown mean and covariance of asset returns in the optimal portfolio weight with their sample counterparts. The plug-in method inevitably introduces estimation risk and usually has poor out-of-sample performance. We propose an optimal combination of the plug-in and 1/N rules to improve out-of-sample performance. Our proposed combined portfolio consistently outperforms both the plug-in and 1/N portfolios on both simulated and real-world datasets.

Dr. Wei is an Assistant Professor in Nanyang Business School at Nanyang Technological University, Singapore. He obtained his PhD from the University of Oxford in 2018. Prior to joining NBS, he taught at the University of Waterloo (Canada) and the University of New South Wales (Australia). His research interests include Actuarial Science, Insurance Economics, Quantitative Finance and Risk Management.