Un modelo GARCH con asimetría condicional autorregresiva para modelar series de tiempo: Una aplicación para el Indice de Precios y Cotizaciones

A GARCH model with autorregresive conditional asymmetry to model time-series: An application to the returns of the Mexican Stock Market Index

Rocio Durán-Vázquez, Arturo Lorenzo-Valdes and Antonio Ruiz-Porras

MPRA Paper from University Library of Munich, Germany

Abstract: We develop a GARCH model with autoregressive conditional asymmetry to describe time-series. This means that, in addition to the conditional mean and variance, we assume that the skewness describes the behavior of the time-series. Analytically, we use the methodology proposed by Fernández and Steel (1998) to define the behavior of the innovations of the model. We use the approach developed by Brooks, et. al., (2005), to build it. Moreover, we show its usefulness by modeling the daily returns of the Mexican Stock Market Index (IPC) during the period between January 3rd, 2008 and September 29th, 2009.

Keywords: Conditional Asymmetry; GARCH; Skewness; Stock Market Returns; Mexico (search for similar items in EconPapers)
JEL-codes: C22 G10 (search for similar items in EconPapers)
Date: 2012-11-07
New Economics Papers: this item is included in nep-ecm
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