A1455
Title: Tractable unified skew-t distribution and copula for heterogeneous asymmetries
Authors: Michael Smith - University of Melbourne (Australia) [presenting]
Lin Deng - University of Melbourne (Australia)
Worapree Ole Maneesoonthorn - Monash University (Australia)
Abstract: Multivariate distributions that allow for asymmetry and heavy tails are important building blocks in many statistical models. The unified skew-t (UST) is a promising choice because it is scalable and allows for a high level of flexibility in the asymmetry of distribution. However, it suffers from parameter identification and computational hurdles that have to date inhibited its use for modeling data. The aim is to propose a new tractable variant of the unified skew-t (TrUST) distribution that addresses both challenges. Moreover, the copula of this distribution is shown to also be tractable, while allowing for greater heterogeneity in asymmetric dependence over variable pairs than the popular skew-t copula. It is shown how Bayesian posterior inference for both the distribution and its copula can be computed using an extended likelihood derived from a generative representation of the distribution. The efficacy of this Bayesian method, and the enhanced flexibility of both the TrUST distribution and its implicit copula, is first demonstrated using simulated data. Applications of the TrUST distribution to highly skewed Australian electricity prices, and the TrUST copula to intraday U.S. equity returns, demonstrate how the proposed distribution and its copula can provide substantial increases in accuracy in practice.
