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비대칭 파워 ARCH (APARCH): 금융 수익률의 유연한 변동성 모형화×GJR-GARCH (비대칭 GARCH)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도19931993
창시자Ding, Granger & EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
유형Conditional heteroscedasticity modelAsymmetric conditional volatility model
원전Ding, 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 ↗
별칭Asymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCHasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
관련35
요약APARCH, 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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