The Bds Test As A Test For The Adequacy Of A Garch(1,1) Specification: A Monte Carlo Study
AbstractIn this study we examine the widely used Brock, Dechert and Scheinkman (BDS) test when applied to the logarithm of the standardized residuals of an estimated GARCH(1,1) model as a test for the adequacy of this specification. We review the conditions derived by De Lima (1996, Econometric Reviews, 15, 237-259) for the nuisance-parameter free property to hold, and address the issue of their necessity, using the flexible framework offered by the GARCH(1,1) model in terms of moment, memory and time heterogeneity properties. By means of Monte Carlo simulations, we show that the BDS test statistic still approximates the standard null distribution even for mildly explosive processes that violate the majority of the conditions. Thus, the test performs reasonably well, its empirical size being rather close to the nominal one. As a by-product of this study, we also shed light on the related issue of consistency of the QML estimators of the conditional variance parameters under various parameter configurations and alternative distributional assumptions on the innovation process.
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Bibliographic InfoPaper provided by Economics and Finance Section, School of Social Sciences, Brunel University in its series Public Policy Discussion Papers with number 04-14.
Length: 22 pages
Date of creation: Oct 2004
Date of revision:
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Postal: Brunel University, Uxbridge, Middlesex UB8 3PH, UK
Other versions of this item:
- Caporale, Guglielmo Maria & Ntantamis, Christos & Pantelidis, Theologos & Pittis, Nikitas, 2004. "The BDS Test as a Test for the Adequacy of a GARCH(1,1) Specification. A Monte Carlo Study," Economics Series 156, Institute for Advanced Studies.
- Guglielmo Maria Caporale & Christos Ntantamis & Theologos Pantelidis & Nikitas Pittis, 2004. "The Bds Test As A Test For The Adequacy Of A Garch(1,1) Specification: A Monte Carlo Study," Economics and Finance Discussion Papers 04-14, Economics and Finance Section, School of Social Sciences, Brunel University.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-10-21 (All new papers)
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