Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Ikke-lineær TGARCH-modell× | ARCH-modell (Autoregressive Conditional Heteroskedasticity)× | |
|---|---|---|
| Fagfelt | Økonometri | Økonometri |
| Familie | Regression model | Regression model |
| Opprinnelsesår≠ | 1993–1994 | 1982 |
| Opphavsperson≠ | Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle | Robert F. Engle |
| Type≠ | Conditional heteroskedasticity model | Conditional volatility model |
| Opprinnelig kilde≠ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ |
| Alias | NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| Relaterte≠ | 4 | 6 |
| Sammendrag≠ | 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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering. |
| ScholarGateDatasett ↗ |
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