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| Panel TGARCH (Threshold GARCH for Panel Data)× | DCC-GARCH (Dynamic Conditional Correlation)× | Panel Data Fixed Effects Model× | |
|---|---|---|---|
| Fagområde≠ | Økonometri | Finansiering | Økonometri |
| Familie | Regression model | Regression model | Regression model |
| Oprindelsesår≠ | 1993–1994 (panel extension: 2000s onward) | 2002 | 2014 |
| Ophavsperson≠ | Glosten, Jagannathan & Runkle (1993); Zakoian (1994); extended to panel settings by subsequent applied finance literature | Robert F. Engle | Hsiao (textbook treatment); within transformation of panel data |
| Type≠ | Asymmetric conditional volatility model | Multivariate volatility model | Panel data regression |
| Oprindelig kilde≠ | 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. Journal of Finance, 48(5), 1779–1801. DOI ↗ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Aliasser | Panel GJR-GARCH, Panel Asymmetric GARCH, Panel Threshold GARCH, TGARCH panel model | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Relaterede≠ | 4 | 5 | 5 |
| Resumé≠ | Panel 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. | DCC-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. | 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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