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Testing constancy of unconditional variance in volatility models by misspecification and specification tests

Annastiina Silvennoinen () and Timo Teräsvirta ()

Studies in Nonlinear Dynamics & Econometrics, 2016, vol. 20, issue 4, 347-364

Abstract: The topic of this paper is testing the hypothesis of constant unconditional variance in GARCH models against the alternative that the unconditional variance changes deterministically over time. Tests of this hypothesis have previously been performed as misspecification tests after fitting a GARCH model to the original series. It is found by simulation that the positive size distortion present in these tests is a function of the kurtosis of the GARCH process. Adjusting the size by numerical methods is considered. The possibility of testing the constancy of the unconditional variance before fitting a GARCH model to the data is discussed. The power of the ensuing test is vastly superior to that of the misspecification test and the size distortion minimal. The test has reasonable power already in very short time series. It would thus serve as a test of constant variance in conditional mean models. An application to exchange rate returns is included.

Keywords: autoregressive conditional heteroskedasticity; modeling volatility; testing parameter constancy; time-varying GARCH (search for similar items in EconPapers)
JEL-codes: C32 C52 (search for similar items in EconPapers)
Date: 2016
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Related works:
Working Paper: Testing constancy of unconditional variance in volatility models by misspecification and specification tests (2015) Downloads
Working Paper: Testing constancy of unconditional variance in volatility models by misspecification and specification tests (2015) Downloads
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