A Stochastic Volatility Model with GH Skew Student’s t-Distribution: Application to Latin-American Stock Returns

This paper presents an empirical study of a stochastic volatility (SV) model for daily stocks returns data of a set of Latin-American countries (Argentina, Brazil, Chile, Mexico and Peru) for the sample period 1996:01-2013:12. We estimate SV models incorporating both leverage e§ects and skewed heavy-tailed disturbances taking into account the GH Skew Studentís t-distribution using the Bayesian estimation method proposed by Nakajima and Omori (2012). A model comparison between the competing SV models with symmetric Studentís t-disturbances is provided using the log marginal likelihoods and a prior sensitivity analysis is also provided. The results suggest that there are leverage e§ects in all returns considered but there is not enough evidence for the case of Peru. Furthermore, skewed heavy-tailed disturbances are conÖrmed only for Argentina, symmetric heavy-tailed disturbances for Mexico, Brazil and Chile, and symmetric Normal disturbances for Peru. Furthermore, we Önd that the GH Skew Studentís t-disturbance distribution in the SV model is successful in describing the distribution of the daily stock return data for Peru, Argentina and Brazil over the traditional symmetric Studentís t-disturbance distribution. JEL Classification-JEL: C11, C58 Keywords: Stochastic Volatility, Generalized Hyperbolic Skew Studentís t-Distribution, Bayesian Estimation, Markov Chain Monte Carlo, Stock Returns, Latin American Stock