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Bayesiansk TGARCH (Tröskel-GARCH med Bayesiansk estimering)×Bayesiansk EGARCH-modell×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1994 / 20081991 (EGARCH); 2000s (Bayesian estimation)
UpphovspersonZakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)Nelson (1991) for EGARCH; Bayesian inference via MCMC developed from early 2000s
TypVolatility model with asymmetric threshold and Bayesian inferenceVolatility model with Bayesian inference
UrsprungskällaZakoian, 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 ↗
AliasBayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-BBayesian EGARCH model, Bayesian Exponential GARCH, EGARCH with Bayesian estimation, B-EGARCH
Närliggande66
SammanfattningBayesian 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 Bayesian EGARCH model combines Nelson's (1991) Exponential GARCH specification — which models the log of conditional variance and captures the leverage effect — with Bayesian posterior inference via Markov Chain Monte Carlo (MCMC). This allows full uncertainty quantification of all volatility parameters, including the asymmetry coefficient, without requiring large-sample normality of the estimates.
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ScholarGateJämför metoder: Bayesian TGARCH · Bayesian EGARCH. Hämtad 2026-06-17 från https://scholargate.app/sv/compare