Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| GJR-GARCH (GARCH Asymmetric)× | Mfumo wa ARIMA (Autoregressive Integrated Moving Average)× | Exponential GARCH (EGARCH)× | |
|---|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model | Regression model |
| Mwaka wa asili≠ | 1993 | 2015 | 1991 |
| Mwanzilishi≠ | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) | Box & Jenkins (Box-Jenkins methodology) | Nelson |
| Aina≠ | Asymmetric conditional volatility model | Univariate time-series model | Conditional volatility model (asymmetric GARCH variant) |
| Chanzo asilia≠ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| Majina mbadala≠ | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| Zinazohusiana≠ | 5 | 5 | 4 |
| Muhtasari≠ | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. |
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