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科学研究
RESEARCH
DAAR model: An alternative to GARCH-in-mean
时间  Datetime
2020-11-25 14:00 — 15:00
地点  Venue
腾讯会议 APP()
报告人  Speaker
李东
单位  Affiliation
清华大学
邀请人  Host
王成
备注  remarks
会议 ID:925 469 357 会议密码:654321
报告摘要  Abstract

Abstract: The risk-return trade-off is an important and classical issue in finance. This paper proposes a new model: double absolute autoregressive (DAAR) model, to characterize this relationship. It is an alternative to the GARCH-in-mean model in the literature, which has been used in empirical applications. While it is very difficult to establish asymptotics of the estimation in GARCH-in-mean model. This hinders applications of the latter in practice. For our DAAR model, statistical inference becomes easy. In this talk, we study the QMLE with its asymptotics for the stationary augmented DAAR model. Further, nonstationary first-order DAAR model is also studied entirely. Simulation studies are conducted to assess the performance of the QMLE and two real examples are analyzed to illustrate the usefulness of DAAR models in characterizing risk-return trade-off.


报告人介绍:李东,清华大学统计学研究中心副教授,2010年毕业于香港科技大学,2013年加入清华大学。主要研究兴趣:非线性时间序列分析,金融计量学,网络数据分析与大数据。目前担任全国工业统计学教学研究会常务理事,中国青年统计学家协会常务理事,北京大数据协会常务理事,中国概率统计学会副秘书长,中国现场统计研究会计算统计分会理事,北京应用统计学会理事。