Efficient Estimation of Semiparametric Multivariate Copula Models
نویسندگان
چکیده
منابع مشابه
Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models Under Copula Misspecification∗
Recently Chen and Fan (2003a) introduced a new class of semiparametric copula-based multivariate dynamic (SCOMDY) models. A SCOMDY model specifies the conditional mean and the conditional variance of a multivariate time series parametrically (such as VAR, GARCH), but specifies the multivariate distribution of the standardized innovation semiparametrically as a parametric copula evaluated at non...
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We consider a general multivariate model where univariate marginal distributions are known up to a common parameter vector and we are interested in estimating that vector without assuming anything about the joint distribution, except for the marginals. If we assume independence between the marginals and maximize the resulting quasilikelihood, we obtain a consistent but inefficient estimate. If ...
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The authors extend to multivariate contexts the copula-based univariate time series modeling approach of Chen & Fan [X. Chen, Y. Fan, Estimation of copula-based semiparametric time series models, J. Econometrics 130 (2006) 307–335; X. Chen, Y. Fan, Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification, J. Econometrics 135 (2006) ...
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Outline Introduction Semi-parametric dynamic copula Motivation Local likelihood estimation Variance of the estimator Bias of the estimator Bandwidth selection Estimation of joint likelihood Modeling of marginal distributions Simulations and applications Simulations Empirical example Conclusions Problems and Solutions Problems Modeling dependence is critical for financial time series Model volat...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2006
ISSN: 0162-1459,1537-274X
DOI: 10.1198/016214506000000311