قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| نموذج TGARCH البيزي (نموذج الانحدار الذاتي الشرطي غير المتجانس مع تقدير بيزي)× | نموذج EGARCH (نموذج التباين الشرطي المتغير الأسي)× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1994 / 2008 | 1991 |
| صاحب الطريقة≠ | Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008) | Daniel B. Nelson |
| النوع≠ | Volatility model with asymmetric threshold and Bayesian inference | Volatility / conditional variance model |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| ذات صلة | 6 | 6 |
| الملخص≠ | Bayesian TGARCH combines the Threshold GARCH volatility model — which captures the asymmetric response of volatility to positive versus negative shocks — with full Bayesian inference via Markov Chain Monte Carlo sampling. The result is a principled, uncertainty-aware framework for modeling leverage effects and fat-tailed financial returns. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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