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Selection Criteria in Regime Switching Conditional Volatility Models

Aix-Marseille University (Aix Marseille School of Economics), CNRS & EHESS, Marseille, 13002, France
Academic Editor: Kerry Patterson
Econometrics 2015, 3(2), 289-316; https://doi.org/10.3390/econometrics3020289
Received: 13 January 2015 / Revised: 26 March 2015 / Accepted: 28 April 2015 / Published: 11 May 2015
A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion. View Full-Text
Keywords: conditional volatility; model selection; GARCH; regime switching conditional volatility; model selection; GARCH; regime switching
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MDPI and ACS Style

Chuffart, T. Selection Criteria in Regime Switching Conditional Volatility Models. Econometrics 2015, 3, 289-316. https://doi.org/10.3390/econometrics3020289

AMA Style

Chuffart T. Selection Criteria in Regime Switching Conditional Volatility Models. Econometrics. 2015; 3(2):289-316. https://doi.org/10.3390/econometrics3020289

Chicago/Turabian Style

Chuffart, Thomas. 2015. "Selection Criteria in Regime Switching Conditional Volatility Models" Econometrics 3, no. 2: 289-316. https://doi.org/10.3390/econometrics3020289

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