A Note on Tail Dependence Regression

Posted: 29 May 2013

See all articles by Qingzhao Zhang

Qingzhao Zhang

Chinese Academy of Sciences (CAS)

Deyuan Li

Fudan University

Hansheng Wang

Peking University - Guanghua School of Management

Date Written: May 28, 2013

Abstract

In financial practice, it is important to understand the dependence structure between the returns of individual assets and the market index. This particularly true under extreme situations. Theoretically, this amounts to regress the dependence relationship against a set of pre-specified predictive variables. To this end, we propose here a novel method called tail dependence regression. It assumes a tail dependence index model between individual assets and market index. Subsequently, such a tail dependence index is modeled as a linear combination of the predictors through a monotonic transformation. An approximate maximum likelihood method is then developed to estimate the unknown regression coefficients. The resulting estimator’s asymptotic properties are investigated theoretically. Numerical studies including both simulated and real datasets are presented for illustration purpose.

Keywords: Approximate Maximum Likelihood Estimation, Tail Dependence Index, Tail Dependence Regression

JEL Classification: C10, C13

Suggested Citation

Zhang, Qingzhao and Li, Deyuan and Wang, Hansheng, A Note on Tail Dependence Regression (May 28, 2013). Available at SSRN: https://ssrn.com/abstract=2271415 or http://dx.doi.org/10.2139/ssrn.2271415

Qingzhao Zhang

Chinese Academy of Sciences (CAS) ( email )

52 Sanlihe Rd.
Datun Road, Anwai
Beijing, Xicheng District 100864
China

Deyuan Li

Fudan University ( email )

Beijing West District Baiyun Load 10th
Shanghai, 100045
China

Hansheng Wang (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

HOME PAGE: http://hansheng.gsm.pku.edu.cn

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