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Bajezijanski ARCH model×Bajezijanski GARCH model×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka1982 (ARCH); 1989 (Bayesian estimation)1989–2000
TvoracRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Geweke (1989); further developed by Nakatsuma (2000) and Bauwens & Lubrano (1998)
TipVolatility model with Bayesian inferenceBayesian volatility model
Temeljni izvorEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Geweke, J. (1989). Exact predictive densities for linear models with ARCH disturbances. Journal of Econometrics, 40(1), 63–86. DOI ↗
Drugi naziviBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHBayesian GARCH, BGARCH, GARCH with Bayesian inference, Bayesian volatility model
Srodne64
SažetakThe Bayesian ARCH model estimates Engle's Autoregressive Conditional Heteroskedasticity specification within a Bayesian framework. Instead of maximising a likelihood, it combines a prior distribution over the volatility parameters with the data likelihood to obtain a full posterior distribution, providing richer uncertainty quantification than classical maximum-likelihood ARCH.The Bayesian GARCH model combines the GARCH framework for time-varying volatility with Bayesian posterior inference. Instead of maximising a likelihood, it specifies prior distributions for the GARCH parameters and draws from the resulting posterior — typically via Markov chain Monte Carlo (MCMC) — to quantify both point estimates and full uncertainty about volatility dynamics.
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ScholarGateUporedite metode: Bayesian ARCH model · Bayesian GARCH model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare