Prediction of α‐stable GARCH and ARMA‐GARCH‐M models |
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| Authors: | Mohammad Mohammadi |
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| Affiliation: | Department of Statistics, Behbahan Khatam Alanbia University of Technology, Iran |
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| Abstract: | ![]()
The best prediction of generalized autoregressive conditional heteroskedasticity (GARCH) models with α‐stable innovations, α‐stable power‐GARCH models and autoregressive moving average (ARMA) models with GARCH in mean effects (ARMA‐GARCH‐M) are proposed. We present a sufficient condition for stationarity of α‐stable GARCH models. The prediction methods are easy to implement in practice. The proposed prediction methods are applied for predicting future values of the daily SP500 stock market and wind speed data. |
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| Keywords: | GARCH‐M model α ‐stable distribution conditional expectation prediction volatility |
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