Misspecification Tests for Periodic Long Memory GARCH Models

Abstract

Distributional theory for Quasi-Maximum Likelihood estimators in long memory conditional heteroskedastic models is not formally defined, even asympotically. Because of that, this paper analyses the performance of the Likelihood Ratio and the Lagrange Multiplier misspecification tests for Periodic Long Memory GARCH models. The real size and power of these tests are studied by means of Monte Carlo simulations with respect to the class of Generalized Long Memory GARCH models. An application to the U SD/JP Y exchange rate is also provided.

Volatility persistence in crude oil markets

“…The comparison between the volatility models is evaluated from various in-sample criteria: LogLikehood (LL), Akaike (AIC), Hannan-Quinn (HQ) and stochastic complexity (RCL) (Rissanen, 1987) criteria. 14 Caporin (2003) show that information criteria can clearly distinguish between long and short memory data generating processes. McKenzie (2003, 2008) find that the HQ and RCL criteria exhibit a clear superiority in their ability to accurately select the correct model for ARCH and GARCH processes.…”