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असिमेट्रिक पावर आर्क (APARCH): वित्तीय प्रतिफलों के लिए लचीला अस्थिरता मॉडलिंग×जीजेआर-गार्च (असममित गार्च)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19931993
प्रवर्तकDing, Granger & EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
प्रकारConditional heteroscedasticity modelAsymmetric conditional volatility model
मौलिक स्रोतDing, 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. DOI ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
उपनामAsymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCHasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
संबंधित35
सारांशAPARCH, 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.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
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