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डीसीसी-गार्च (गतिशील सशर्त सहसंबंध)×जीजेआर-गार्च (असममित गार्च)×पैनल डेटा फिक्स्ड इफेक्ट्स मॉडल×
क्षेत्रवित्तअर्थमितिअर्थमिति
परिवारRegression modelRegression modelRegression model
उद्भव वर्ष200219932014
प्रवर्तकRobert F. EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Hsiao (textbook treatment); within transformation of panel data
प्रकारMultivariate volatility modelAsymmetric conditional volatility modelPanel data regression
मौलिक स्रोतEngle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. 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 ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
उपनामdynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyonasymmetric 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
संबंधित555
सारांशDCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.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).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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