ScholarGate
Асистент

Сравнение на методи

Прегледайте избраните методи един до друг; редовете с разлики са откроени.

Експоненциален GARCH (EGARCH)×Модел GARCH (Прогнозиране на волатилността)×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19911986
СъздателNelsonTim Bollerslev
ТипConditional volatility model (asymmetric GARCH variant)Conditional volatility model
Основополагащ източникNelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Други названияexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Свързани45
РезюмеEGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 1 Източници
  3. PUBLISHED

Към търсенето Изтегляне на слайдове

ScholarGateСравнение на методи: EGARCH · GARCH Model. Извлечено на 2026-06-20 от https://scholargate.app/bg/compare