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Model ARCH Bayesiano×Model ARCH (Autoregressive Conditional Heteroskedasticity)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen1982 (ARCH); 1989 (Bayesian estimation)1982
Autor originalRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Robert F. Engle
TipusVolatility model with Bayesian inferenceConditional volatility model
Font seminalEngle, 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 ↗
ÀliesBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Relacionats66
ResumThe 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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