ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

GARCH-malli (volatiliteetin ennustaminen)×Eksponentiaalinen GARCH (EGARCH)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19861991
KehittäjäTim BollerslevNelson
TyyppiConditional volatility modelConditional volatility model (asymmetric GARCH variant)
AlkuperäislähdeBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
RinnakkaisnimetGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Liittyvät54
TiivistelmäThe 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.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.
ScholarGateAineisto
  1. v1
  2. 1 Lähteet
  3. PUBLISHED
  1. v1
  2. 2 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: GARCH Model · EGARCH. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare