Statistics and Data Science Seminar
Qingshuo Song
City University of Hong Kong
Outperformance Portfolio Optimization: Hypothesis Testing Approach
Abstract: We study the portfolio problem of maximizing the out-performance probability over a random
benchmark through dynamic trading with a fixed initial capital. Under a general incomplete
market framework, this stochastic control problem can be formulated as a composite pure
hypothesis testing problem. We analyze the connection between this pure testing problem and
its randomized counterpart, and from latter we derive a dual representation for the maximal
outperformance probability. Moreover, in a complete market setting, we provide a closed-form
solution to the problem of beating a leveraged exchange traded fund. For a general benchmark
under an incomplete stochastic factor model, we provide the Hamilton-Jacobi-Bellman PDE
characterization for the maximal out-performance probability. It's a joint work with
Tim Leung and Jie Yang.
Wednesday June 27, 2012 at 3:00 PM in SEO 636