报告人：蒋学军
报告题目：Efficient and robust estimation of GARCH and DTARCH models
报告时间：2014年10月22日周三下午3:00
报告地点：江苏师范大学数学与统计学院学术报告厅（静远楼1506室）
报告内容摘要：Double-threshold autoregressive conditional heteroscedastic (DTARCH) models and Generalized autoregressive conditional heteroscedastic (GARCH) models have been a powerful tool for modeling volatility. In this paper we propose an efficient and robust estimation method for estimating the parameters of DTARCH & GARCH models. This method involves a sequence of weights and takes a data-driven weighting scheme to maximize the asymptotic efficiency of the estimators. Under regularity conditions, we establish asymptotic distributions of the proposed estimators for a variety of heavy- or light-tailed error distributions. Simulations endorse our theoretical results. A real example illustrates the use of our approach.
蒋学军博士简介：
南方科技大学助理教授，2009年于香港中文大学统计系获博士学位，2011年任中南财经政法大学副教授，2013年任职于南方科技大学。研究领域包括Statistics in Financial Econometrics，Quantile Regression, Variable Selection，Survival analysis Nonparametric regression等，在Statistica Sinica，Canadian Journal of Statistics, The Econometrics Journal等SCI期刊发表文章十余篇。现任深圳羽邦融资担保股份有限公司独立董事，深圳天润华担保投资有限公司技术顾问，并担任国际(SCI)杂志Statistica Sinica, Communication Statistics, Journal of Testing and Evaluation, Austin Mathematics的编委。