Selection Criteria in Regime Switching Conditional Volatility Models
AbstractA 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 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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Bibliographic InfoPaper provided by Aix-Marseille School of Economics, Marseille, France in its series AMSE Working Papers with number 1339.
Length: 20 pages
Date of creation: 14 Jul 2013
Date of revision: 14 Jul 2013
Conditional volatility; model selection; GARCH; Regime Switching;
Other versions of this item:
- Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," Working Papers halshs-00844413, HAL.
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