Comparar métodos

	Modelo ARCH Bayesiano	Modelo ARCH (Heterocedasticidad Autoregresiva Condicional)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1982 (ARCH); 1989 (Bayesian estimation)	1982
Autor original	Robert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)	Robert F. Engle
Tipo	Volatility model with Bayesian inference	Conditional volatility model
Fuente seminal	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	Bayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Relacionados	6	6
Resumen	The 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.