An empirical application of stochastic volatility models to Latin-American stock returns using GH skew student's t-distribution

• Autor: Lengua Lafosse, Patricia
• Formato: tesis de maestría
• Fecha de Publicación: 2015
• Institución: Pontificia Universidad Católica del Perú
• Repositorio: PUCP-Tesis
• Lenguaje: inglés
• OAI Identifier: oai:tesis.pucp.edu.pe:20.500.12404/6167
• Enlace del recurso: http://hdl.handle.net/20.500.12404/6167
• Nivel de acceso: acceso abierto
• Materia: Estadística bayesiana; Análisis estocástico; Bolsa de Valores; https://purl.org/pe-repo/ocde/ford#1.01.03

This paper represents empirical studies of stochastic volatility (SV) models 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 effects and skewed heavy-tailed disturbances taking into account the GH Skew Student’s t-distribution using the Bayesian estimation method proposed by Nakajima and Omori (2012). A model comparison between the competing SV models with symmetric Student´s t-disturbances is provided using the log marginal likelihoods in the empirical study. A prior sensitivity analysis is also provided. The results suggest that there are leverage effects in all indices considered but there is not enough evidence for Peru, and skewed heavy-tailed disturbances is confirmed only for Argentina, symmetric heavy-tailed disturbances for Mexico, Brazil and Chile, and symmetric Normal disturbances for Peru. Furthermore, we find that the GH Skew Student s 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 Student´s t-disturbance distribution.