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Bayesiansk ARCH-modell×Autoregressiv modell för betingad heteroskedasticitet (ARCH-modell)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår1982 (ARCH); 1989 (Bayesian estimation)1982
UpphovspersonRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Robert F. Engle
TypVolatility model with Bayesian inferenceConditional volatility model
UrsprungskällaEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
AliasBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Närliggande66
SammanfattningThe 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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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ScholarGateJämför metoder: Bayesian ARCH model · ARCH model. Hämtad 2026-06-15 från https://scholargate.app/sv/compare