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Обобщена авторегресионна условна хетероскедастичност (GARCH)×GJR-GARCH (Асиметричен GARCH)×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19861993
СъздателTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
ТипConditional volatility modelAsymmetric conditional volatility model
Основополагащ източникBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
Други названияGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Свързани55
РезюмеGARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
ScholarGateНабор от данни
  1. v1
  2. 1 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: GARCH · GJR-GARCH. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare