قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| نموذج TGARCH القوي× | نموذج ARCH القوي× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1994–2000s | 2002–2008 |
| صاحب الطريقة≠ | Zakoian (1994) for TGARCH; robust extensions developed through quasi-maximum likelihood and M-estimation literature | Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s |
| النوع≠ | Volatility model with asymmetry and robust estimation | Volatility / conditional heteroscedasticity model |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | robust GJR-GARCH, robust threshold GARCH, heavy-tail TGARCH, outlier-robust TGARCH | robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model |
| ذات صلة | 6 | 6 |
| الملخص≠ | Robust TGARCH extends the Threshold GARCH model by replacing the conventional maximum likelihood objective with an estimator that is resistant to heavy-tailed innovations and outlying observations. It captures asymmetric volatility responses — where negative shocks amplify variance more than positive shocks — while remaining reliable when the return distribution deviates strongly from normality. | The Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time series. |
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