Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Generalised Autoregressive Conditional Heteroskedasticity (GARCH)× | GJR-GARCH (GARCH Asimetris)× | |
|---|---|---|
| Bidang | Ekonometrika | Ekonometrika |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1986 | 1993 |
| Pencetus≠ | Tim Bollerslev | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| Tipe≠ | Conditional volatility model | Asymmetric conditional volatility model |
| Sumber perintis≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ |
| Alias | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| Terkait | 5 | 5 |
| Ringkasan≠ | GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns. | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). |
| ScholarGateSet data ↗ |
|
|