Vertaile menetelmiä

	GARCH (Generalized Autoregressive Conditional Heteroskedasticity)	ARIMA (Autoregressive Integrated Moving Average) -malli
Tieteenala	Ekonometria	Ekonometria
Menetelmäperhe	Regression model	Regression model
Syntyvuosi	1986	2015
Kehittäjä	Tim Bollerslev	Box & Jenkins (Box-Jenkins methodology)
Tyyppi	Conditional volatility model	Univariate time-series model
Alkuperäislähde	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
Rinnakkaisnimet	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Liittyvät	5	5
Tiivistelmä	GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.	ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).