Model stability and forecast performance of Beta-t-EGARCH

ABSTRACT

We show that the model stability of the recent QAR(1) plus Beta-t-EGARCH(1,1) is superior to that of the well-known ARMA(1,1) plus t-GARCH(1,1) because QAR plus Beta-t-EGARCH discounts extreme observations, while ARMA plus t-GARCH accentuates them. Model stability of QAR plus Beta-t-EGARCH is an elegant property; however, we show that the out-of-sample density forecast performance of ARMA plus t-GARCH is superior to that of QAR plus Beta-t-EGARCH. We study model stability and density forecast performance for a set of rolling data windows. We use data on the S&P 500 index for the period 1990–2015. For robustness analysis, we also study Monte Carlo simulations of asset returns for the stochastic volatility model.

KEYWORDS:

• Model stability
• density forecasts
• dynamic conditional score models
• Beta-t-EGARCH

JEL CLASSIFICATION:

• C22
• C52
• C58

Acknowledgements

We appreciate receiving comments and suggestions from Matthew Copley.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the School of Business of Universidad Francisco Marroquín.