Model Selection: ARMA Versus GARCH-M Model

Sattwik Santra and Samarjit Das ()
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Samarjit Das: Indian Statistical Institute

A chapter in Directional and Multivariate Statistics, 2025, pp 441-449 from Springer

Abstract: Abstract In this article, we consider two competing models, viz., ARMA with conditional heteroscedasticity and GARCH-M models. Both the models capture inherent linear autocorrelation structure in the data. These two models are non-nested in nature. No one is a particular case of other model. Applied researchers are generally tempted to build an appropriate ARMA model based on Box-Jenkins’s methodology, namely based on ACF and PACFs overlooking the existence of other competing models. In this paper, the usual AIC/BIC criteria are used to identify the appropriate model. The detailed simulation study shows that the AIC/BIC can indeed select the true model.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-2004-3_22

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DOI: 10.1007/978-981-96-2004-3_22

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