Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Paneļa DCC-GARCH modelis× | Vektora autoregresija (VAR)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2002 | 1980 |
| Autors≠ | Robert F. Engle | Christopher A. Sims |
| Tips≠ | Multivariate volatility model | Multivariate time-series model |
| Pirmavots≠ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroscedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Citi nosaukumi | DCC-GARCH panel, panel dynamic conditional correlation, multivariate DCC-GARCH, Panel DCC | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Panel DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation GARCH framework to panel data settings, jointly modelling time-varying volatility and cross-sectional correlations across multiple units (countries, firms, or assets) over time. It allows pairwise correlations to vary dynamically in response to market shocks while preserving parsimony via a two-step estimation. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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