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A Bootstrap Test for the Existence of Moments for GARCH Processes

Alexander Heinemann

arXiv 5 Feb 2019 · Econometrics · 2 citations (OpenAlex)

arXiv:1902.01808 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper studies the joint inference on conditional volatility parameters and the innovation moments by means of bootstrap to test for the existence of moments for GARCH(p,q) processes. We propose a residual bootstrap to mimic the joint distribution of the quasi-maximum likelihood estimators and the empirical moments of the residuals and also prove its validity. A bootstrap-based test for the existence of moments is proposed, which provides asymptotically correctly-sized tests without losing its consistency property. It is simple to implement and extends to other GARCH-type settings. A simulation study demonstrates the test's size and power properties in finite samples and an empirical application illustrates the testing approach.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Francq, C. and J.M. Zakoän (2018) Testing the existence of moments for GARCH processes0.92844100%
2Francq, C. and J.M. Zakoïan (2011) GARCH Models: Structure, Statistical Inference and Financial Applications0.84310460%
3Francq, C. and J.M. Zakoän (2015) Risk-parameter estimation in volatility models0.7639344%
4Cavaliere, G., R.S. Pedersen, and A. Rahbek (2018) The fixed volatility bootstrap for a class of ARCH($q$) models0.64422100%
5Ling, S (1999) On the probabilistic properties of a double threshold ARMA conditional heteroskedastic model0.64422100%
6Ling, S. and M. McAleer (2002) Necessary and sufficient moment conditions for the GARCH(r, s) and asymmetric power GARCH(r, s) models0.64422100%
7Beutner, E., A. Heinemann, and S. Smeekes (2018) A residual bootstrap for conditional value-at-risk0.54019416%
8Chang, Y. and J.Y. Park (2003) A sieve bootstrap for the test of a unit root0.51121100%
9Cavaliere, G., H.B. Nielsen, R.S. Pedersen, and A. Rahbek (2018) Bootstrap inference on the boundary of the parameter space with application to conditional volatility models0.40511100%
10Corradi, V. and E.M. Iglesias (2008) Bootstrap refinements for QML estimators of the GARCH(1,1) parameters0.40511100%

Showing the top 10 of 23 scored citations.