Selection Criteria in Regime Switching Conditional Volatility Models

Thomas Chuffart

Econometrics, 2015, vol. 3, issue 2, 1-28

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.

Keywords: conditional volatility; model selection; GARCH; regime switching (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2225-1146/3/2/289/pdf (application/pdf)
https://www.mdpi.com/2225-1146/3/2/289/ (text/html)

Related works:
Working Paper: Selection Criteria in Regime Switching Conditional Volatility Models (2015)
Working Paper: Selection Criteria in Regime Switching Conditional Volatility Models (2013)
Working Paper: Selection Criteria in Regime Switching Conditional Volatility Models (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:3:y:2015:i:2:p:289-316:d:49388

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().