【Academic Seminar】Mean-Variance Portfolio Management with Functional Optimization
Topic: Mean-Variance Portfolio Management with Functional Optimization
Speaker: Prof. Ka Wai Tsang
Time & Date: 12:00 pm - 01:00 pm, Wednesday, November 25, 2020
Venue: Room 501, Dao Yuan Building
The cornerstones of quantitative finance are asset returns, interest rates, and volatilities. They appear in many fundamental formulas in finance. In this tutorial, we consider their interplay and the underlying statistical issues in a classical topic in quantitative finance, namely portfolio theory. In the classical Markowitz’s portfolio theory, the expectation and the variance of the returns of the underlying assets are assumed to be known. However, in practice, they are estimated by past values of the returns. Moreover, the successful applications of various time series models in the financial market also imply that the current returns depend on their past values. Therefore, it is natural to consider the weight vector of the portfolio as a function of past values. In this tutorial, I will introduce a functional optimization approach to portfolio optimization problems by treating the unknown weight vector as a function of past values instead of treating them as fixed unknown coefficients in the majority of studies.
Prof. Ka Wai Tsang received his B.S. and M.Phil. in Mathematics from the Chinese University of Hong Kong in 2007 and 2009, his M.S. degree in Financial Mathematics in 2011 and his PhD in Computational and Mathematical Engineering in 2015 from Stanford University. He has joined the Chinese University of Hong Kong, Shenzhen since 2015 and has taught various statistics courses, including Financial Data Analysis and Statistical Modelling in Financial Market. He also taught courses for the Stanford’s Quantitative Methods in Finance Graduate Certificate as a visiting instructor at Stanford's Department of Statistics. His research areas include computational mathematics, financial engineering and data analytics, statistical inference and adaptive clinical design.