The new KS method for a structural break detection in GARCH(1,1) models

Dmitriy Borzykh and Artem Yazykov ()

Applied Econometrics, 2019, vol. 54, 90-104

Abstract: We propose a new method of a structural break detection for GARCH(1,1) model. This new method is called the KS method since it is based on Kolmogorov-Smirnov statistics. By using Monte-Carlo experiments we show that the KS method has good statistical properties. We compare our method with three well-known CUSUM methods: (Kokoszka, Leipus, 1999) referred to as KT method, (Inclán, Tiao, 1994) referred to as IT method, and (Lee et al., 2004) referred to as LTM method. To make the experiments closer to real conditions, we generate GARCH processes with coefficients estimated on 26 Russian stocks time series. Based on the results of numerical experiments, we suggest that our method is highly competitive and may be placed somewhere in between the KL method which has high power and high probability of type I error, and IT and LTM methods which have low power and also low probability of type I error.

Keywords: GARCH; volatility; change points; structural breaks; ICSS; CUSUM (search for similar items in EconPapers)
JEL-codes: C32 C58 C63 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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