Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| DCC-GARCH (dinamiskā nosacītā korelācija)× | Fiksēto efektu paneļa datu modelis× | |
|---|---|---|
| Nozare≠ | Finanses | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2002 | 2014 |
| Autors≠ | Robert F. Engle | Hsiao (textbook treatment); within transformation of panel data |
| Tips≠ | Multivariate volatility model | Panel data regression |
| Pirmavots≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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