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Model stability and forecast performance of Beta--EGARCH

Author

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  • Szabolcs Blazsek
  • Helmuth Chavez
  • Carlos Mendez

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.

Suggested Citation

  • Szabolcs Blazsek & Helmuth Chavez & Carlos Mendez, 2016. "Model stability and forecast performance of Beta--EGARCH," Applied Economics Letters, Taylor & Francis Journals, vol. 23(17), pages 1219-1223, November.
    • Handle: RePEc:taf:apeclt:v:23:y:2016:i:17:p:1219-1223
    DOI: 10.1080/13504851.2016.1145343
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    Cited by:

    1. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.

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