Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Nelineārais ARCH (NARCH) modelis× | EGARCH modelis (eksponenciālais GARCH)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1992 | 1991 |
| Autors≠ | Higgins & Bera | Daniel B. Nelson |
| Tips≠ | Volatility model | Volatility / conditional variance model |
| Pirmavots≠ | Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Citi nosaukumi | NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | The Nonlinear ARCH (NARCH) model, introduced by Higgins and Bera (1992), extends Engle's original ARCH framework by allowing the power transformation of volatility to be estimated from the data rather than fixed at two. This flexibility captures a broader class of volatility dynamics observed in financial and macroeconomic time 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. |
| ScholarGateDatu kopa ↗ |
|
|