Empirical Modeling of Latin American Stock and Forex Markets Returns and Volatility using Markov-Switching GARCH Models

Miguel Ataurima, Erika Collantes () and Gabriel Rodríguez

No 2017-436, Documentos de Trabajo / Working Papers from Departamento de Economía - Pontificia Universidad Católica del Perú

Abstract: Using a sample of weekly frequency of the stock and Forex markets returns series, we estimate a set of Markov-Switching-Generalized Autoregressive Conditional Heterocedasticity (MS-GARCH) models to a set of Latin American countries (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. The estimates are compared with a standard 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 and a lower likelihood with the other model than 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 American stock and Forex 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. JEL Classification-JEL: C22, C52, C53

Keywords: MS-GARCH Models; GARCH Models; Returns; Volatility; Latin-American Stock market; Latin-American Forex market. (search for similar items in EconPapers)
Pages: 62
Date: 2017
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