Синтез та адаптивне настроювання моделей GARCH для прогнозування дисперсій гетероскедастичних процесів з різнотемповою дискретизацією
Theoretical propositions concerning design of GARCH models for forecasting conditional dispersions of heteroscedastic processes under discretization of input disturbances with small sampling periods and output coordinates with large ones are considered. The dynamics of processes in a stochastic medi...
Збережено в:
| Дата: | 2017 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | rus |
| Опубліковано: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2017
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| Онлайн доступ: | http://journal.iasa.kpi.ua/article/view/109779 |
| Теги: |
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| Назва журналу: | System research and information technologies |
Репозиторії
System research and information technologies| Резюме: | Theoretical propositions concerning design of GARCH models for forecasting conditional dispersions of heteroscedastic processes under discretization of input disturbances with small sampling periods and output coordinates with large ones are considered. The dynamics of processes in a stochastic medium is described by models of autoregression and sliding mean with multirate discretization. An algorithm for adaptive setting of the GARCH model coefficients concerning the sliding mean is developed. Experimental results for adaptive setting of GARCH model optimal coefficients as well as forecasting conditional dispersions under optimal coefficients are presented. |
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