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Title:Regime shifts in asymmetric GARCH models assuming heavy-tailed distribution: Evidence from GCC stock markets PDF Logo
Authors:Alfreedi, Ajab A.
Isa, Zaidi
Hassan, Abu
Issue Date:2012
Citation:[Journal:] Journal of Statistical and Econometric Methods [ISSN:] 2241-0376 [Publisher:] International Scientific Press [Volume:] 1 [Year:] 2012 [Issue:] 1 [Pages:] 43-76
Abstract:In this study, we have investigated GCC stock market volatilities exploiting a number of asymmetric models (EGARCH, ICSS-EGARCH, GJR-GARCH, and ICSS-GJR-GARCH).This paper uses the weekly data over the period 2003-2010. The ICSS-EGARCH and ICSS-GJR-GARCH models take into account the discrete regime shifts in stochastic errors. The finding supports the widely accepted view that accounting for the regime shifts detected by the iterated cumulative sums of squares (ICSS) algorithm in the variance equations overcomes the overestimation of volatility persistence. In addition, we have discovered that the sudden changes are generally associated with global, regional, and domestic economic as well as political events. Importantly, the asymmetric model estimations use normal as well as heavy-tailed conditional densities.
Subjects:asymmetric models
ICSS
EGARCH
GJR-GARCH
heavy-tailed process : GCC stock market
Document Type:Article
Appears in Collections:Journal of Statistical and Econometric Methods

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