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| Modello EGARCH Non Lineare× | Modello EGARCH (Exponential GARCH)× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine | 1991 | 1991 |
| Ideatore | Daniel B. Nelson | Daniel B. Nelson |
| Tipo≠ | Conditional volatility model | Volatility / conditional variance model |
| Fonte seminale | 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 ↗ |
| Alias | NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns. | 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. |
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