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Модель EGARCH (Экспоненциальная GARCH)×Модель TGARCH (Threshold GARCH)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления19911993-1994
Автор методаDaniel B. NelsonZakoian (1994); Glosten, Jagannathan & Runkle (1993)
ТипVolatility / conditional variance modelAsymmetric volatility model
Основополагающий источникNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗
Другие названияExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Связанные66
СводкаThe Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: EGARCH model · TGARCH model. Получено 2026-06-17 из https://scholargate.app/ru/compare