报告题目： Markov Regime-switching Model with Multiple Change-points
报告人: Yuehua Amy Wu 教授, York University
报告摘要： Change-point problems can be found in many areas including financial econometrics. To detect all the change-points in a data sequence before the modelling is of great importance.?A statistical analysis without considering their existence may lead to an incorrect or improper conclusion. We will present some numerical examples to illustrate a change-point problem, and show the importance to include a change-point in data modelling.? A Markov regime-switching log-normal (RSLN) model has been used to capture the time-varying features of stock return and volatility. The model displays a better ability to depict a fat tail distribution as compared with using a log-normal model, which means that the RSLN model can describe observed market behaviour better. However, the analysis of the behaviour of calibrated regime-switching parameters over different lengths of time intervals reveals the existence of change-points. An algorithm is thus presented for identifying the change-points in the series corresponding to the times when there are changes in parameter estimates. This algorithm for identifying change-points is tested on the Standard and Poor's 500 monthly index data from 1971 to 2008, and the Nikkei 225 monthly index data from 1984 to 2008. It is evident that the change-points we identify match the big events observed in the US stock market and the Japan stock market (e.g., the October 1987 stock market crash), and that the segmentations of stock index series, which are defined as the periods between change-points, match the observed bear-bull market phases. Further development will also be discussed.
Wu教授是加拿大约克大学数学与统计系资深教授。1989年获得美国匹兹堡大学统计学博士学位，师从世界著名统计学家C. Rao。研究领域非常广泛，包括空间统计、M-估计、模型选择、变点检测、非参数估计、金融统计等，以及在环境科学、信息科学、计量经济学、生物医学等领域中的应用，目前是国际统计学会的会员。在Proceeding of National Academy Science, USA,（美国国家科学院院刊），Computational Statistics & Data Analysis（计算统计与数据分析）、Statistica Sinica（泛华统计）、Journal of Multivariate Analysis（多元统计分析）等期刊发表学术论文100多篇，其中4篇论文发表在国际最顶级期刊PNAS（美国国家科学院院刊）上。承担加拿大环境署（Environment Canada）、加拿大自然科学基金（NSERC Discovery Grant）等多项重要科研项目。