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- W2001301175 abstract "The classical forecasting theory of stationary time series exploits the second-order structure (variance, autocovariance, and spectral density) of an observed process in order to construct some prediction intervals. However, some economic time series show a time-varying unconditional second-order structure. This article focuses on a simple and meaningful model allowing this nonstationary behaviour. We show that this model satisfactorily explains the nonstationary behaviour of several economic data sets, among which are the U.S. stock returns and exchange rates. The question of how to forecast these processes is addressed and evaluated on the data sets." @default.
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- W2001301175 date "2004-10-01" @default.
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- W2001301175 title "Forecasting economic time series with unconditional time-varying variance" @default.
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- W2001301175 doi "https://doi.org/10.1016/j.ijforecast.2003.10.002" @default.
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