Процедура уточнения ICSS алгоритма обнаружения структурных сдвигов в GARCH-моделях
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.
интеграционные процессы на финансовых рынках, эффект перетекания волатильности, динамическая корреляция рядов доходности
This paper is an empirical study of the changing nature of the dependence of fundamental factors on the stock market index, which is the trend identified earlier in the Russian stock market. We empirically test the impact of daily values of fundamental factors on the MOEX Russia Index from 2003 to 2018. The analysis of the ARIMA-GARCH (1,1) model with a rolling window reveals that the change in the power and direction of the influence of the fundamental factors on the Russian stock market persists. The Quandt-Andrews breakpoint test and Bai-Perron test identify the number and likely location of structural breaks. We find multiple breaks probably associated with the dramatic falls of the stock market index. The results of the regression models over the different regimes, defined by the structural breaks, can vary markedly over time. This research is of value in macroeconomic forecasting and in the investment strategy development
This paper presents the results of volatility forecasting for indices of the Russian stock market using existing and developed by the authors fuzzy asymmetric GARCH-models. These models consider various switching functions which are taking into account the positive and negative shocks and are built using the tools of fuzzy numbers. Furthermore, in some models there are used switching functions that consider expert macroeconomic information. It was shown that fuzzy asymmetric GARCH-models provide a more accurate prediction of volatility than similar crisp models.
The article considers the procedure of constructing COGARCH volatility models with continuous time based on the Levy processes. The article describes the procedure of constructing the model in the general case and in the case of compound Poisson process.
The paper aims at finding the most accurate VaR model for the four most liquid Russian stocks. Among the possible VaR modeling techniques, the estimates considered in this work are based on GARCH models with six different distributions. A back testing analysis is performed to evaluate the accuracy of the alternative models and to find the worst predictable period in terms of the volatility behavior.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.