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GJR-GARCH (Асимметричный GARCH)×Модель с фиксированными эффектами для панельных данных×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления19932014
Автор методаGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Hsiao (textbook treatment); within transformation of panel data
ТипAsymmetric conditional volatility modelPanel data regression
Основополагающий источникGlosten, 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 ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Другие названияasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Связанные55
СводкаGJR-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).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).
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: GJR-GARCH · Panel Fixed Effects. Получено 2026-06-19 из https://scholargate.app/ru/compare