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Fractionally integrated generalized autoregressive conditional heteroskedasticity. (English) Zbl 0865.62085
Summary: The new class of fractionally integrated generalized autoregressive conditionally heteroskedastic (FIGARCH) processes is introduced. The conditional variance of the process implies a slow hyperbolic rate of decay for the influence of lagged squared innovations. Unlike I(\(d\)) processes for the mean, maximum likelihood estimates (MLE) of the FIGARCH parameters are argued to be \(T^{1/2}\)-consistent. The small sample behavior of an approximate MLE procedure is assessed through a simulation study, which also documents how the estimation of a standard GARCH model tends to produce integrated, or IGARCH, like estimates. An empirical example with daily Deutschmark-U.S. dollar exchange rates illustrates the practical relevance of the new FIGARCH specification.

62P20 Applications of statistics to economics
91B84 Economic time series analysis
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
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