Three-Stage Semi-Parametric Estimation of T-Copulas: Asymptotics, Finite-Sample Properties and Computational Aspects
Computational Statistics and Data Analysis, Forthcoming
50 Pages Posted: 4 Feb 2009
Date Written: February 3, 2009
Genest, C., Ghoudi, K., Rivest, L.P. (1995) proposed a two-stage semi-parametric estimation procedure for a broad class of copulas satisfying minimal regularity conditions. A three-stage semi-parametric estimation method based on Kendall's tau has been recently proposed in the financial literature to estimate the Student's T copula, too. 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 pros and cons of this methodology are then analyzed in terms of numerical convergence and positive definiteness of the estimated T-copula correlation matrix.
Keywords: Copulas, Maximum Likelihood, Two-stage estimation, Three-stage estimation, Semi-parametric estimation
JEL Classification: C14, C15, C16, C30, C51
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