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A note on tail dependence regression

Qingzhao Zhang, Deyuan Li and Hansheng Wang

Journal of Multivariate Analysis, 2013, vol. 120, issue C, 163-172

Abstract: In financial practice, it is important to understand the dependence structure between the returns of individual assets and the market index. This is particularly true under extreme situations. Theoretically, this amounts to regressing 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 purposes.

Keywords: Approximate maximum likelihood estimation; Tail dependence index; Tail dependence regression (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.jmva.2013.05.007

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