2019/02/05 by Alexander Heinemann, Heinemann, Alexander
Economics, Econometrics and Finance · #Econometrics (econ.EM) #FOS: Economics and business #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Monetary Policy and Economic Impact
paper · pdf · doi:10.48550/arxiv.1902.01808
openalex publication_date 2019/02/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.