Changes of structure in financial time series and the GARCH model

Thomas Mikosch and Catalin Starica ()
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Thomas Mikosch: Dept. Actuarial Mathematics, University of Copenhagen

Econometrics from EconWPA

Abstract: In this paper we propose a goodness of fit test that checks the resemblance of the spectral density of a GARCH process to that of the log-returns. The asymptotic behavior of the test statistics are given by a functional central limit theorem for the integrated periodogram of the data. A simulation study investigates the small sample behavior, the size and the power of our test. We apply our results to the S&P500 returns and detect changes in the structure of the data related to shifts of the unconditional variance. We show how a long range dependence type behavior in the sample ACF of absolute returns might be induced by these shifts.

Keywords: integrated periodogram; spectral distribution; functional central limit theorem; Kiefer--Muller process; Brownian bridge; sample autocorrelation; change point; GARCH process; long range dependence; IGARCH; non-stationarity (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-fin
Date: 2004-12-06
Note: Type of Document - pdf; pages: 22
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Persistent link: http://EconPapers.repec.org/RePEc:wpa:wuwpem:0412003

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