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- W2059607233 abstract "Abstract It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. Maximum likelihood estimates at the local and global modes are investigated and turn out to be qualitatively different, leading to different model-based forecast intervals. In the simpler GARCH( p,q ) regression model, we derive analytical conditions for bimodality of the corresponding likelihood. In that case, the likelihood is symmetrical around a local minimum. We propose a solution to avoid this bimodality." @default.
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- W2059607233 date "2008-07-01" @default.
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- W2059607233 title "Multimodality in GARCH regression models" @default.
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- W2059607233 doi "https://doi.org/10.1016/j.ijforecast.2008.06.002" @default.
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