Bandingkan kaedah
Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.
| Model GARCH Parameter-Variabel Masa (TVP-GARCH)× | Model EGARCH (Exponential GARCH)× | |
|---|---|---|
| Bidang | Ekonometrik | Ekonometrik |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1982–2013 | 1991 |
| Pengasas≠ | Engle (1982) for ARCH/GARCH foundation; extended by Creal, Koopman & Lucas (2013) and others for time-varying parameter variants | Daniel B. Nelson |
| Jenis≠ | Volatility model with time-varying coefficients | Volatility / conditional variance model |
| Sumber perintis≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | TVP-GARCH, time-varying GARCH, TV-GARCH, state-space GARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Berkaitan≠ | 5 | 6 |
| Ringkasan≠ | The Time-Varying Parameter GARCH model extends the standard GARCH framework by allowing the conditional variance parameters — including the ARCH and GARCH coefficients — to change over time rather than remaining fixed throughout the sample. This makes it well-suited to financial and macroeconomic series where volatility dynamics evolve across different market regimes or economic episodes. | 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. |
| ScholarGateSet data ↗ |
|
|