Three-stage semi-parametric estimation of T-copulas: Asymptotics, finite-sample properties and computational aspects

Dean Fantazzini

Computational Statistics & Data Analysis, 2010, vol. 54, issue 11, 2562-2579

Abstract: A two-stage semi-parametric estimation procedure for a broad class of copulas satisfying minimal regularity conditions has been recently proposed. In addition, a three-stage semi-parametric estimation method based on Kendall's tau in order to estimate the Student's t copula has also been designed. Its major advantage is to allow for greater computational tractability when dealing with high dimensional issues, where two-stage procedures are no more a viable choice. The asymptotic properties of this methodology are developed and its finite-sample behavior are examined via simulations. The advantages and disadvantages of this methodology are analyzed in terms of numerical convergence and positive definiteness of the estimated T-copula correlation matrix.

Date: 2010
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