报告人：帖经智，University of Georgia，USA
Title: An Optimal Mean-Reversion Trading Rule under a Markov Chain Model
Abstract: I will talk about a mean-reversion trading rule. In contrast to most market models treated in the literature, the underlying market is solely determined by a two-state Markov chain. The major advantage of such Markov chain model is its striking simplicity and yet its capability of capturing various market movements. We study an optimal trading rule under such a model. The objective of the problem under consideration is to find a sequence stopping (buying and selling) times so as to maximize an expected return. Under some suitable conditions, explicit solutions to the associated HJB equations (variational inequalities) are obtained. The optimal stopping times are given in terms of a set of threshold levels. A verification theorem is provided to justify their optimality. Finally, a numerical example is provided to illustrate the results.
报告人简介： 帖经智，美国 University of Georgia 教授，1995年于University of Toronto获博士学位，1985年于兰州大学数学系获学士学位。 帖经智教授主要从事Harmonic Analysis、Several Complex Variable, Geometric Analysis、Mathematical Finance 等研究工作。其研究领域包括：Analysis and Geometry on Heisenberg Group, Pseudo-Hermitian manifolds。目前已在Canadian Journal of Mathematics，Journal of Geometric Analysis, Journal of Differential Geometry, Communication in PDEs, Journal of Optimization and Application 等国际学术期刊上发表SCI收录论文30余篇。