So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Mô hình Tham số Thay đổi theo Thời gian TGARCH (TVP-TGARCH)× | Mô hình EGARCH (Exponential GARCH)× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1990s–2000s | 1991 |
| Người khởi xướng≠ | Extension combining Zakoïan (1994) TGARCH and time-varying parameter methods | Daniel B. Nelson |
| Loại≠ | Volatility model with asymmetry and parameter evolution | Volatility / conditional variance model |
| Công trình gốc≠ | Zakoïan, 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 ↗ |
| Tên gọi khác | TVP-TGARCH, time-varying TGARCH, threshold GARCH with time-varying parameters, TVP Threshold GARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | The TVP-TGARCH model extends Threshold GARCH by allowing its volatility parameters to evolve over time via a state-space representation. It captures both the leverage effect — that negative return shocks increase volatility more than positive ones — and structural change in that asymmetry, making it well-suited for long financial time series subject to regime shifts. | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|