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The BDS test as a test for the adequacy of a GARCH (1, 1) specification: a Monte Carlo study

Caporale, Guglielmo Maria, Ntantamis, Christos, Pantelidis, Theologos, Pittis, Nikitas (2005) The BDS test as a test for the adequacy of a GARCH (1, 1) specification: a Monte Carlo study. Journal of Financial Econometrics, 3 (2). pp. 282-309. ISSN 1479-8409. E-ISSN 1479-8417. (doi:10.1093/jjfinec/nbi010) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1093/jjfinec/nbi010

Abstract

In this study we examine the widely used Brock, Dechert, and Scheinkman (BDS) test when applied to the logarithm of the squared 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 the consistency of the QML estimators of the conditional variance parameters under various parameter configurations and alternative distributional assumptions on the innovation process.

Item Type: Article
DOI/Identification number: 10.1093/jjfinec/nbi010
Uncontrolled keywords: BDS test GARCH(1,1) model nuisance-parameter free property QML estimator
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > Kent Business School > Accounting and Finance
Depositing User: Tracey Pemble
Date Deposited: 01 Aug 2016 10:53 UTC
Last Modified: 29 May 2019 17:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/56707 (The current URI for this page, for reference purposes)
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