Model stability and forecast performance of Beta-t-EGARCH |
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Authors: | Szabolcs Blazsek Helmuth Chavez Carlos Mendez |
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Affiliation: | School of Business, Universidad Francisco Marroquín, Guatemala City, Guatemala |
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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. |
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Keywords: | Model stability density forecasts dynamic conditional score models Beta-t-EGARCH |
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