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Inference in Threshold GARCH Models

时间:2017-05-11

Statistics Seminar2017-09

Topic:Inference in Threshold GARCH Models

Speaker:Dong Li, Associate Professor, Center for Statistical Science, Tsinghua University

Time:Thursday, May 11, 14:00-15:00

Place:Room 217, Guanghua Building 2

Abstract:

This talk studies the asymptotic theory of the quasi-maximum likelihood estimation for a threshold GARCH model. Under some conditions, it is shown that the estimated threshold is n-consistent, which converges weakly to the smallest minimizer of a two-sided compound Poisson process. The remaining parameters are root-n-consistent and asymptotically normal. Simulation studies are carried out to assess the performance of the estimator. Finally, an empirical example is given to illustrate the usefulness of TGARCH models.

Introduction:

李东,男,副教授,清华大学统计学研究中心。2010年博士毕业于香港科技大学,后在美国University of Iowa做博士后研究,曾访问香港科技大学、伦敦政治经济学院。2013年加入清华大学。发表学术论文将近20余篇,目前担任北京应用统计学会的首届理事和中国现场统计研究会计算统计分会的首届理事。

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