ScholarGate
Avustaja

Vertaile menetelmiä

Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.

Epälineaarinen TGARCH-malli×EGARCH-malli (Exponential GARCH)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi1993–19941991
KehittäjäJean-Michel Zakoian; related work by Glosten, Jagannathan & RunkleDaniel B. Nelson
TyyppiConditional heteroskedasticity modelVolatility / conditional variance model
AlkuperäislähdeZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
RinnakkaisnimetNL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variantExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Liittyvät46
TiivistelmäThe Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series.The 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.
ScholarGateAineisto
  1. v1
  2. 2 Lähteet
  3. PUBLISHED
  1. v1
  2. 2 Lähteet
  3. PUBLISHED

Siirry hakuun Lataa diat

ScholarGateVertaile menetelmiä: Nonlinear TGARCH model · EGARCH model. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare