A Bootstrap Test for the Existence of Moments for GARCH Processes

Alexander Heinemann

Papers from arXiv.org

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.

Date: 2019-02, Revised 2019-07
New Economics Papers: this item is included in nep-ecm and nep-ets
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