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Bayesovský model EGARCH×Model EGARCH (Exponenciálny GARCH)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku1991 (EGARCH); 2000s (Bayesian estimation)1991
TvorcaNelson (1991) for EGARCH; Bayesian inference via MCMC developed from early 2000sDaniel B. Nelson
TypVolatility model with Bayesian inferenceVolatility / conditional variance model
Pôvodný zdrojNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
Ďalšie názvyBayesian EGARCH model, Bayesian Exponential GARCH, EGARCH with Bayesian estimation, B-EGARCHExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Príbuzné66
ZhrnutieThe 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.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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ScholarGatePorovnať metódy: Bayesian EGARCH · EGARCH model. Získané 2026-06-17 z https://scholargate.app/sk/compare