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	असिमेट्रिक पावर आर्क (APARCH): वित्तीय प्रतिफलों के लिए लचीला अस्थिरता मॉडलिंग	गार्छ मॉडल (अस्थिरता पूर्वानुमान)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1993	1986
प्रवर्तक	Ding, Granger & Engle	Tim Bollerslev
प्रकार	Conditional heteroscedasticity model	Conditional volatility model
मौलिक स्रोत	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.
उपनाम	Asymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
संबंधित	3	5
सारांश	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.