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Опис документа

Zrazhevsky G., Zrazhevska V.
Quintile regression based approach for dynamical var and cvar forecasting using metalog distribution

Вид документа:  Складова частина документа 
Мова:  Англійська  Обсяг:  P, 139-150 
УДК:  519.6 : 519.81 

Аннотацiя:

The paper proposes a new method of dynamic VaR and CVaR (ES) risk measures forecasting. Quantile linear GARCH model is chosen as the main forecast-ing model for time series quantiles. To build a forecast, the values of quantiles are approximated by the metalog distribution, which makes it possible to use analytical formulas to evaluate risk measures. The method of VaR and CVaR forecasting is formulated as a step-by-step algorithm. At the first stage, an initial model is built to obtain variance estimates. The predicted variance values obtained from the con-structed model are used at the second stage to find the QLGARCH model coeffi-cients by solving the minimization problem. At the third stage, the QLGARCH models are estimated on a non uniform quantile grid. The obtained predicted values of quantiles are used to estimate the approximating metalog distribution. The inves-tigated theory is applied to VaR and CVaR forecasting for time series of daily log return of the DJI index.

Є складовою частиною документа Системні дослідження та інформаційні технології [Текст] = System research & information technologies : міжнар. наук.-техн. журнал. № 1 / ННК "Ін-т прикладного систем. аналізу" НТУУ "КПІ" МОН та НАН України. — Київ : ВПК "Політехніка", 2021.

Теми документа

• УДК/5 Математика та природничi науки/51 Математика/519.6 Обчислювальна математика. Числовий аналіз