Empirical modelling of latin american stock markets returns and volatility using Markov - Switching garch models

• Autor: Ataurima Arellano, Miguel
• Formato: tesis de maestría
• Fecha de Publicación: 2016
• Institución: Pontificia Universidad Católica del Perú
• Repositorio: PUCP-Tesis
• Lenguaje: inglés
• OAI Identifier: oai:tesis.pucp.edu.pe:20.500.12404/8096
• Enlace del recurso: http://hdl.handle.net/20.500.12404/8096
• Nivel de acceso: acceso abierto
• Materia: Bolsa de valores--América Latina; Bolsa de valores--Modelos estadísticos; Bolsa de valores--Tasa de rendimiento; https://purl.org/pe-repo/ocde/ford#5.02.01

Using a sample of weekly frequency of the stock markets returns series, we estimate a set of Markov-Switching-Generalized Autoregressive Conditional Heterocedastic- ity (MS-GARCH) models to a set of Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico and Peru) with an approach based on both the Monte Carlo Expectation-Maximization (MCEM) and Monte Carlo Maximum Likelihood (MCML) algorithms suggested by Augustyniak (2014). The estimates are compared with a stan- dard GARCH, MS and other models. The results show that the volatility persistence is captured di¤erently in the MS and MS-GARCH models. The estimated parameters with a standard GARCH model exacerbates the volatility in almost double compared to MS-GARCH model. There is di¤erent behavior of the coe¢ cients and the variance according the two regimes (high and low volatility) by each model in the Latin Amer- ican stock markets. There are common episodes related to global international crises and also domestic events producing the di¤erent behavior in the volatility of each time series.