Article2015

DETECTING FOR SMOOTH STRUCTURAL CHANGES IN GARCH MODELS

38 citations0/0 files storedEconometric Theory

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Financial Risk and Volatility Modeling Monetary Policy and Economic Impact Stochastic processes and financial applications

Abstract

Detecting and modeling structural changes in GARCH processes have attracted increasing attention in time series econometrics. In this paper, we propose a new approach to testing structural changes in GARCH models. The idea is to compare the log likelihood of a time-varying parameter GARCH model with that of a constant parameter GARCH model, where the time-varying GARCH parameters are estimated by a local quasi-maximum likelihood estimator (QMLE) and the constant GARCH parameters are estimated by a standard QMLE. The test does not require any prior information about the alternatives of structural changes. It has an asymptotic N(0,1) distribution under the null hypothesis of parameter constancy and is consistent against a vast class of smooth structural changes as well as abrupt structural breaks with possibly unknown break points. A consistent parametric bootstrap is employed to provide a reliable inference in finite samples and a simulation study highlights the merits of our test.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1990Statistical Inference in Instrumental Variables Regression with I(1) Processes 1990Persistence in Variance, Structural Change, and the GARCH Model 2008The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes 2001The New Econometrics of Structural Change: Dating Breaks in U.S. Labor Productivity 1994Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator 2004Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes

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2012Nonparametric estimation of a time-varying GARCH model 2014Time Series Segmentation Procedures to Detect, Locate and Estimate Change-Points

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