Сравнение на методи

	Модел ARCH (Авторегресивен условен хетероскедастичност)	АРСС модел (авторегресионна плъзгаща се средна)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	1982	1970
Създател	Robert F. Engle	George E. P. Box and Gwilym M. Jenkins
Тип	Conditional volatility model	Time series model
Основополагащ източник	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Други названия	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Свързани	6	5
Резюме	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 ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.