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| Mô hình GARCH (Dự báo Biến động)× | Mô hình TGARCH (Threshold GARCH)× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1986 | 1993-1994 |
| Người khởi xướng≠ | Tim Bollerslev | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Loại≠ | Conditional volatility model | Asymmetric volatility model |
| Công trình gốc≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| Tên gọi khác | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | 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. | The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative. |
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