An Empirical Application of a Random Level Shifts Model with Time-Varying Probability and Mean Reversion to the Volatility of Latin-American Forex Markets Returns [Una aplicación empírica de un modelo de cambios de nivel aleatorios con probabilidades cambiantes y reversión a la media a la volatilidad de los retornos cambiarios en América Latina]

Gabriel Rodríguez and José Carlos Gonzáles Tanaka ()

No 2016-415, Documentos de Trabajo / Working Papers from Departamento de Economía - Pontificia Universidad Católica del Perú

Abstract: Following Xu and Perron (2014), this paper uses daily data for six Forex Latin American markets. Four models of the family of the Random Level Shift (RLS) model are estimated: a basic model where probabilities of level shift are driven by a Bernouilli variable but probability is constant; a model where varying probabilities are allowed and introduced via past extreme returns; a model with mean reversion mechanism; and a model incorporating these two features. Our results prove three striking features: first, the four RLS models fit well the data, with almost all the estimates highly significant; second, the long memory property disappears completely from the ACF, including the GARCH effects; and third, the forecasting performance is much better for the RLS models against an overall of four competitor models: GARCH, FIGARCH and two ARFIMA models.

Keywords: Forecasting; Forex Return Volatility; Latin American Forex Markets; Long memory; Mean Reversion; Random Level Shifts; Time Varying Probability (search for similar items in EconPapers)
JEL-codes: C22 C52 G12 (search for similar items in EconPapers)
Pages: 48
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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