Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| DCC-GARCH (Correlación Dinámica Condicional)× | EGARCH de panel× | |
|---|---|---|
| Campo≠ | Finanzas | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2002 | 1991 (EGARCH); panel extensions widely used from 2000s |
| Autor original≠ | Robert F. Engle | Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature |
| Tipo≠ | Multivariate volatility model | Volatility model |
| Fuente seminal≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | 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. | 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. |
| ScholarGateConjunto de datos ↗ |
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