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Outlier Detection in GARCH Models.

Abstract:

We present a new procedure for detecting multiple additive outliers in GARCH(1,1) models at unknown dates. The outlier candidates are the observations with the largest standardized residual. First, a likelihood-ratio based test determines the presence and timing of an outlier. Next, a second test determines the type of additive outlier (volatility or level). The tests are shown to be similar with respect to the GARCH parameters. Their null distribution can be easily approximated from an extre...

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Jurgen A. Doornik More by this author
Marius Ooms More by this author
Volume:
2005-092/4
Series:
Discussion Paper
Publication date:
2005
URN:
uuid:97e168a4-4baa-4557-8ae8-bdf4916f9ee1
Local pid:
oai:economics.ouls.ox.ac.uk:12927
Language:
English

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