Σύγκριση μεθόδων

	Μοντέλο ARCH (Αυτοπαλίνδρομη Συνθηκική Ετεροσκεδαστικότητα)	Εκθετικό GARCH (EGARCH)	Μοντέλο GARCH (Πρόβλεψη Μεταβλητότητας)
Πεδίο	Οικονομετρία	Οικονομετρία	Οικονομετρία
Οικογένεια	Regression model	Regression model	Regression model
Έτος προέλευσης	1982	1991	1986
Δημιουργός	Robert F. Engle	Nelson	Tim Bollerslev
Τύπος	Conditional volatility model	Conditional volatility model (asymmetric GARCH variant)	Conditional volatility model
Θεμελιώδης πηγή	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Εναλλακτικές ονομασίες	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Συναφείς	6	4	5
Σύνοψη	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.	EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.	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.