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| Modèle DCC-GARCH avec rupture structurelle× | Modèle EGARCH à rupture structurelle× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2002-2006 | 1990–1991 |
| Auteur d'origine≠ | Engle (2002) for DCC; break-augmented extensions by Pelletier (2006) and subsequent literature | Nelson (1991) for EGARCH; Lamoureux and Lastrapes (1990) for break-augmented GARCH variants |
| Type≠ | Multivariate volatility model with regime change | Volatility model with structural breaks |
| Source fondatrice≠ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | DCC-GARCH with structural breaks, break-adjusted DCC-GARCH, regime-shift DCC-GARCH, SB-DCC-GARCH | SB-EGARCH, EGARCH with regime shifts, break-adjusted EGARCH, structural change EGARCH |
| Apparentées | 5 | 5 |
| Résumé≠ | Structural break DCC-GARCH extends Engle's Dynamic Conditional Correlation GARCH framework by explicitly allowing the correlation and volatility structure to shift at one or more structural break points in the sample. It models time-varying co-volatility between multiple financial series while accounting for sudden regime changes caused by crises, policy shifts, or market microstructure changes. | Structural Break EGARCH combines Nelson's Exponential GARCH framework with explicit allowance for one or more structural breaks in the volatility process. By letting the intercept and persistence parameters of the log-variance equation shift at detected break dates, the model avoids the spurious long-memory and inflated persistence that standard EGARCH suffers when the data contain regime changes. |
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