ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Модель ARCH (авторегрессионная условная гетероскедастичность)×Экспоненциальный GARCH (EGARCH)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления19821991
Автор методаRobert F. EngleNelson
ТипConditional volatility modelConditional volatility model (asymmetric GARCH variant)
Основополагающий источникEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
Другие названияARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Связанные64
СводкаThe ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.EGARCH 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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: ARCH model · EGARCH. Получено 2026-06-20 из https://scholargate.app/ru/compare