Сравнение методов

	Байесовская модель ARCH	Модель ARCH (авторегрессионная условная гетероскедастичность)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1982 (ARCH); 1989 (Bayesian estimation)	1982
Автор метода	Robert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)	Robert F. Engle
Тип	Volatility model with Bayesian inference	Conditional volatility model
Основополагающий источник	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.
Другие названия	Bayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Связанные	6	6
Сводка	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.