A Bootstrap Test for the Existence of Moments for GARCH Processes
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 t...
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Main Author | |
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Format | Journal Article |
Language | English |
Published |
05.02.2019
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Online Access | Get full text |
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Summary: | 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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DOI: | 10.48550/arxiv.1902.01808 |