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Bajezijanski TGARCH (Prag GARCH sa Bajezijanskom procenom)×EGARCH model (eksponencijalni GARCH)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka1994 / 20081991
TvoracZakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)Daniel B. Nelson
TipVolatility model with asymmetric threshold and Bayesian inferenceVolatility / conditional variance model
Temeljni izvorZakoian, 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 ↗
Drugi naziviBayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-BExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Srodne66
SažetakBayesian TGARCH combines the Threshold GARCH volatility model — which captures the asymmetric response of volatility to positive versus negative shocks — with full Bayesian inference via Markov Chain Monte Carlo sampling. The result is a principled, uncertainty-aware framework for modeling leverage effects and fat-tailed financial returns.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.
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ScholarGateUporedite metode: Bayesian TGARCH · EGARCH model. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare