Сравнение методов

	Модель ARCH (авторегрессионная условная гетероскедастичность)	Модель GARCH (прогнозирование волатильности)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1982	1986
Автор метода	Robert F. Engle	Tim Bollerslev
Тип	Conditional volatility model	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.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Другие названия	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Связанные	6	5
Сводка	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.	The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.