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Copula-based nonlinear quantile autoregression

Xiaohong Chen (), Roger Koenker () and Zhijie Xiao
Additional contact information
Roger Koenker: Institute for Fiscal Studies and UCL

No CWP27/08, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

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.

New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2008-10-23
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Journal Article: Copula-based nonlinear quantile autoregression (2009) Downloads
Working Paper: Copula-Based Nonlinear Quantile Autoregression (2008) Downloads
Working Paper: Copula-Based Nonlinear Quantile Autoregression (2008) Downloads
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