Abstract: The key issue in importance sampling is the choice of the alternative sampling distribution, which is often chosen from the exponential tilt family of the underlying distribution. However, when the problem exhibits certain kind of nonconvexity, it is very likely that a single exponential change of measure will never attain asymptotic optimality and may lead to erroneous estimates. In this paper we introduce an explicit iterative scheme which combines the traditional cross-entropy method and the EM algorithm to find an efficient alternative sampling distribution in the form of mixtures. We also study the applications of this scheme to option price estimation. It is joint work with Hui Zhang.

 

About the Speaker: Dr Xiang Zhou received his BSc from Peking University and PhD from Princeton University. Before joining City University in 2012, he worked as a research associate at Princeton University and Brown University. His major research interests include noise-induced transitions and stochastic systems, the study of rare events and its applications in physics, chemistry, biology, engineering and finance.

 

Date&Time: August 13, 2013 (Tuesday), 14:00 - 15:00
Location: 606 Conference Room