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Modeli ya EGARCH (Exponential GARCH)×Modeli ya TGARCH (Threshold GARCH)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili19911993-1994
MwanzilishiDaniel B. NelsonZakoian (1994); Glosten, Jagannathan & Runkle (1993)
AinaVolatility / conditional variance modelAsymmetric volatility model
Chanzo asiliaNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗
Majina mbadalaExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Zinazohusiana66
MuhtasariThe 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.The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.
ScholarGateSeti ya data
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  2. 2 Vyanzo
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: EGARCH model · TGARCH model. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare