The refinement procedure of ICSS algorithm for structural breaks detection in GARCH-models

Dmitriy Borzykh and Mikhail Khasykov ()
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Mikhail Khasykov: National Research University Higher School of Economics (NRU HSE), Moscow, Russian Federation

Applied Econometrics, 2018, vol. 51, 126-139

Abstract: We suggest a hybrid algorithm for structural breaks detection when using a class of piecewise-specified GARCH(1,1) models. The algorithm comprises two steps. In the first step the moments of structural breaks are detected using KL-ICSS method based on (Kokoszka, Leipus, 1999) and (Inclán, Tiao, 1994). In the second step previously detected moments of structural breaks are refined with the help of a modified MML method. Therefore, the whole procedure is called ML-KL-ICSS algorithm. We also provide five numeric experiments to show the overall performance of the proposed procedure. Four of five experiments show that ML-KL-ICSS method is significantly more accurate in detecting structural breaks as opposed to one-step procedures. In one experiment the accuracy of both methods was comparable but ML-KL-ICSS method performed slightly better. Finally, we test our method using real data. In order to do that we detect structural breaks in common stocks returns volatility for the Russian “Gazprom” company. Detected moments of structural breaks correspond to significant events in the Russian economy.

Keywords: GARCH; volatility; multiple change points; structural breaks; ICSS; CUSUM. (search for similar items in EconPapers)
JEL-codes: C32 C58 C63 (search for similar items in EconPapers)
Date: 2018
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