Document Type
Discussion Paper
Publication Date
10-1-2008
CFDP Number
1679
CFDP Pages
30
Abstract
Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed quantile estimators are established under mild conditions, allowing for global misspecification of parametric copulas and marginals, and without assuming any mixing rate condition. These results lead to a general framework for inference and model specification testing of extreme conditional value-at-risk for financial time series data.
Recommended Citation
Chen, Xiaohong; Koenker, Roger; and Xiao, Zhijie, "Copula-Based Nonlinear Quantile Autoregression" (2008). Cowles Foundation Discussion Papers. 1993.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1993