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Selection Criteria in Regime Switching Conditional Volatility Models

  • Thomas Chuffart

    (AMSE - Aix-Marseille School of Economics - EHESS - École des hautes études en sciences sociales - Centre national de la recherche scientifique (CNRS) - Ecole Centrale Marseille (ECM) - AMU - Aix-Marseille Université)

A large number of non linear conditional heteroskedastic models have been proposed in the literature and practitioners do not have always the tools to choose the correct specification. In this article, our main interest is to know if usual choice criteria lead them to choose the good specification in regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH model and the Markov-Switching GARCH models. Thanks to simulation experiments, we highlight that information criteria and loss functions can lead practitioners to do a misspecification. Indeed, depending on the Data Generating Process used in the experiment, the choice of a criteria to select a model is a difficult issue. We argue that if selection criteria lead to choose the wrong model, it's rather due to the difficulty to estimate such models with Quasi Maximum Likelihood Estimation method (QMLE).

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Paper provided by HAL in its series Working Papers with number halshs-00844413.

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Date of creation: Jul 2013
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Handle: RePEc:hal:wpaper:halshs-00844413
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