Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Panel EGARCH× | EGARCH modelis (eksponenciālais GARCH)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 (EGARCH); panel extensions widely used from 2000s | 1991 |
| Autors≠ | Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature | Daniel B. Nelson |
| Tips≠ | Volatility model | Volatility / conditional variance model |
| Pirmavots | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Citi nosaukumi | Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | 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 Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. |
| ScholarGateDatu kopa ↗ |
|
|