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Panel TGARCH (Threshold GARCH for Panel Data)×GJR-GARCH (비대칭 GARCH)×패널 EGARCH×패널 데이터 고정 효과 모형×
분야계량경제학계량경제학계량경제학계량경제학
계열Regression modelRegression modelRegression modelRegression model
기원 연도1993–1994 (panel extension: 2000s onward)19931991 (EGARCH); panel extensions widely used from 2000s2014
창시자Glosten, Jagannathan & Runkle (1993); Zakoian (1994); extended to panel settings by subsequent applied finance literatureGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Daniel B. Nelson (EGARCH); panel extension by applied econometrics literatureHsiao (textbook treatment); within transformation of panel data
유형Asymmetric conditional volatility modelAsymmetric conditional volatility modelVolatility modelPanel data regression
원전Glosten, 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. Journal of Finance, 48(5), 1779–1801. 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 ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
별칭Panel GJR-GARCH, Panel Asymmetric GARCH, Panel Threshold GARCH, TGARCH panel modelasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCHfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
관련4545
요약Panel TGARCH extends the Threshold GARCH (GJR-GARCH) model to panel data, allowing each cross-sectional unit to exhibit asymmetric volatility responses — where negative shocks generate larger variance increases than positive shocks of the same magnitude — while exploiting the cross-sectional dimension to obtain more efficient parameter estimates.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).Panel EGARCH extends Nelson's (1991) Exponential GARCH model to a panel setting, allowing conditional variance to evolve asymmetrically over time for each cross-sectional unit. The log specification ensures non-negative variance without parameter constraints, and the leverage term distinguishes whether negative shocks amplify volatility more than positive ones of equal magnitude.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGate방법 비교: Panel TGARCH · GJR-GARCH · Panel EGARCH · Panel Fixed Effects. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare