Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Panel EGARCH× | Model Panel DCC-GARCH× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1991 (EGARCH); panel extensions widely used from 2000s | 2002 |
| Twórca≠ | Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature | Robert F. Engle |
| Typ≠ | Volatility model | Multivariate volatility model |
| Źródło pierwotne≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroscedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ |
| Inne nazwy | Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH | DCC-GARCH panel, panel dynamic conditional correlation, multivariate DCC-GARCH, Panel DCC |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | 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 DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation GARCH framework to panel data settings, jointly modelling time-varying volatility and cross-sectional correlations across multiple units (countries, firms, or assets) over time. It allows pairwise correlations to vary dynamically in response to market shocks while preserving parsimony via a two-step estimation. |
| ScholarGateZbiór danych ↗ |
|
|