Usporedite metode

	ARCH model (Autoregressive Conditional Heteroskedasticity)	Model GARCH (Prognoziranje volatilnosti)	Kvantilna regresija
Područje	Ekonometrija	Ekonometrija	Ekonometrija
Obitelj	Regression model	Regression model	Regression model
Godina nastanka	1982	1986	1978
Tvorac	Robert F. Engle	Tim Bollerslev	Koenker & Bassett
Vrsta	Conditional volatility model	Conditional volatility model	Conditional quantile regression
Temeljni izvor	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.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Drugi nazivi	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	conditional quantile regression, regression quantiles, Kantil Regresyon
Srodne	6	5	5
Sažetak	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.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.