Прогнозування максимальних умовних дисперсій багатовимірних процесів із різнотемповою дискретизацією на основі адаптивних моделей GARCH
A method for synthesis of GARCH models for forecasting maximal conditional dispersions of multidimensional heteroskedastic processes under discretisation of input disturbances with small sampling periods and of output coordinates with large ones is considered. The dynamics of processes in a stochast...
Збережено в:
| Дата: | 2009 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | rus |
| Опубліковано: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2009
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| Онлайн доступ: | http://journal.iasa.kpi.ua/article/view/107275 |
| Теги: |
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| Назва журналу: | System research and information technologies |
Репозиторії
System research and information technologies| Резюме: | A method for synthesis of GARCH models for forecasting maximal conditional dispersions of multidimensional heteroskedastic processes under discretisation of input disturbances with small sampling periods and of output coordinates with large ones is considered. The dynamics of processes in a stochastic medium is described by matrix-polinomial models of autoregression and a sliding mean with multirate discretization. An algorithm for adaptive setting of GARCH models is developed. Experimental results for such a setting as well as forecasting of maximal conditional dispersions under optimal coefficients are presented. |
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