Misspecification of Generalized Autoregressive Score Models: Monte Carlo Simulations and Applications

Oluwagbenga T. Babatunde; OlaOluwa S. Yaya; Damola M. Akinlana

doi:https://doi.org/10.14445/22315373/IJMTT-V65I3P511

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 65 | Issue 3 | Year 2019 | Article Id. IJMTT-V65I3P511 | DOI : https://doi.org/10.14445/22315373/IJMTT-V65I3P511

Misspecification of Generalized Autoregressive Score Models: Monte Carlo Simulations and Applications

Oluwagbenga T. Babatunde, OlaOluwa S. Yaya, Damola M. Akinlana

Citation :

Oluwagbenga T. Babatunde, OlaOluwa S. Yaya, Damola M. Akinlana, "Misspecification of Generalized Autoregressive Score Models: Monte Carlo Simulations and Applications," International Journal of Mathematics Trends and Technology (IJMTT), vol. 65, no. 3, pp. 72-80, 2019. Crossref, https://doi.org/10.14445/22315373/IJMTT-V65I3P511

Abstract

The specification and misspecification of a new class of volatility model that is robust to jumps and outliers is investigated via Monte Carlo experiment and real life examples. The class includes the Generalized Autoregressive Score (GAS) model derived from the classical Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. The Exponential GAS (EGAS) and Asymmetric Exponential GAS (AEGAS) models form the variants of the GAS model. Using three different levels of volatility persistence and GARCH probability distributions which are Normal (N), Student-t (T) and Skewed-Student-t (SKT), with estimates of Akaike Information Criterion (AIC) and kurtosis as criteria, we obtained useful information for studying the misspecification and tail behaviour of the newly proposed volatility model. The results of the Monte Carlo experiment, the crude oil and gas prices showed that the best misspecified model for AEGAS-SKT and EGAS-T is EGAS-SKT.

Keywords

Misspecification, Volatility Persistence, Monte Carlo, Generalized Autoregressive Score

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