Methoden vergleichen

	APARCH	GARCH-Modell (Volatilitätsvorhersage)
Fachgebiet	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	1993	1986
Urheber	Ding, Granger & Engle	Tim Bollerslev
Typ	Conditional heteroscedasticity model	Conditional volatility model
Wegweisende Quelle	Ding, Z., Granger, C. W. J., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1(1), 83–106.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Aliasnamen	Asymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Verwandt	3	5
Zusammenfassung	APARCH, introduced by Ding, Granger, and Engle (1993) while studying long-memory properties of stock market returns, extends the GARCH family by allowing both the power transformation of conditional volatility and an asymmetric response to positive and negative shocks. The model nests at least seven well-known ARCH-type specifications as special cases, making it a unifying framework for volatility modelling in financial econometrics.	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.