selection criteria in regime switching conditional volatility models

Clicks: 228
ID: 248485
2015
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Abstract
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.
Reference Key
chuffart2015econometricsselection Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Thomas Chuffart
Journal developmental cognitive neuroscience
Year 2015
DOI
10.3390/econometrics3020289
URL
http://www.mdpi.com/2225-1146/3/2/289
Keywords
model selection garch regime switchingeconomics as a science

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