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主题： Copula Structured M4 Processes with Application to High-Frequency Financial Data

主讲人：张正军教授 （美国威斯康辛大学统计系教授）

时间：2015年6月29日（周一）下午16:00-17:00

地点：北院卓远楼305

主办单位：统计与数学学院

摘要：Statistical applications of classical parametric max-stable processes are still sparse mostly due to lack of 1) efficiency of statistical estimation of many parameters in the processes, 2) flexibility of concurrently modeling asymptotic independence and asymptotic dependence among variables, and 3) capability of fitting real data directly. This paper studies a more flexible model, i.e. a class of copula structured M4 (multivariate maxima and moving maxima) processes, and hence CSM4 for short. CSM4 processes are constructed by incorporating sparse random coefficients and structured extreme value copulas in asymptotically (in)dependent M4 (AIM4) processes. As a result, the new model overcomes all of the aforementioned constraints. The paper illustrates these new features and advantages of the CSM4 model using simulated examples and real data of intra-daily maxima of high-frequency financial time series. The paper also studies probabilistic properties of the proposed model, statistical estimators and their properties. (This presentation is based on a joint work with Bin Zhu)

张正军教授简介：统计学博士，美国威斯康星大学麦迪逊分校统计系教授。研究领域包括金融时间序列分析、极值理论、金融风险分析、贝叶斯统计等。目前担任美国威斯康星大学统计系副主任、招生委员会主任、国际商务及经济期刊Journal of Business & Economic Statistics、国际概率统计期刊JKSS、Statistics and Its Interface等多个国际SCI期刊副主编。