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| Nieliniowy model ARCH (NARCH)× | Model GARCH (Prognozowanie zmienności)× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1992 | 1986 |
| Twórca≠ | Higgins & Bera | Tim Bollerslev |
| Typ≠ | Volatility model | Conditional volatility model |
| Źródło pierwotne≠ | Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Inne nazwy | NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | 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 Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. |
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