B1660
Title: On the pseudo-likelihood estimator for copula models parameters
Authors: Alexandra Dias - University of York (United Kingdom) [presenting]
Abstract: A commonly used method for estimating dependence parameters in copula models is maximum pseudo-likelihood. It has been shown that despite its good asymptotic properties, this estimation method does not perform well when compared with methods of moments estimators for small and weakly dependent samples. We show that by changing the adjustment on the empirical distribution function the performance of the maximum pseudo-likelihood method can be improved, surpassing the performance of the methods of moments estimators. For now, the focus is on the Clayton copula model.
