Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Paneeli-TGARCH (Kynnys-GARCH paneeliaineistoille)× | DCC-GARCH (Dynamic Conditional Correlation)× | |
|---|---|---|
| Tieteenala≠ | Ekonometria | Rahoitus |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1993–1994 (panel extension: 2000s onward) | 2002 |
| Kehittäjä≠ | Glosten, Jagannathan & Runkle (1993); Zakoian (1994); extended to panel settings by subsequent applied finance literature | Robert F. Engle |
| Tyyppi≠ | Asymmetric conditional volatility model | Multivariate volatility model |
| Alkuperäislähde≠ | 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. Journal of Finance, 48(5), 1779–1801. DOI ↗ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ |
| Rinnakkaisnimet | Panel GJR-GARCH, Panel Asymmetric GARCH, Panel Threshold GARCH, TGARCH panel model | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon |
| Liittyvät≠ | 4 | 5 |
| Tiivistelmä≠ | Panel TGARCH extends the Threshold GARCH (GJR-GARCH) model to panel data, allowing each cross-sectional unit to exhibit asymmetric volatility responses — where negative shocks generate larger variance increases than positive shocks of the same magnitude — while exploiting the cross-sectional dimension to obtain more efficient parameter estimates. | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. |
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