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Muundo wa Nonlinear TGARCH×Modeli wa GARCH (Utabiri wa Msukosuko)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili1993–19941986
MwanzilishiJean-Michel Zakoian; related work by Glosten, Jagannathan & RunkleTim Bollerslev
AinaConditional heteroskedasticity modelConditional volatility model
Chanzo asiliaZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Majina mbadalaNL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variantGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Zinazohusiana45
MuhtasariThe 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 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.
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ScholarGateLinganisha mbinu: Nonlinear TGARCH model · GARCH Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare