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| Μη Γραμμικό Μοντέλο TGARCH× | Μοντέλο EGARCH (Exponential GARCH)× | |
|---|---|---|
| Πεδίο | Οικονομετρία | Οικονομετρία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 1993–1994 | 1991 |
| Δημιουργός≠ | Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle | Daniel B. Nelson |
| Τύπος≠ | Conditional heteroskedasticity model | Volatility / conditional variance model |
| Θεμελιώδης πηγή≠ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Εναλλακτικές ονομασίες | NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Συναφείς≠ | 4 | 6 |
| Σύνοψη≠ | The Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series. | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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