Fractionally integrated generalized autoregressive conditional heteroskedasticity

Journal Article (Journal Article)

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 T1/2-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.

Full Text

Duke Authors

Cited Authors

  • Baillie, RT; Bollerslev, T; Mikkelsen, HO

Published Date

  • January 1, 1996

Published In

Volume / Issue

  • 74 / 1

Start / End Page

  • 3 - 30

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/S0304-4076(95)01749-6

Citation Source

  • Scopus