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| 结构突变DCC-GARCH模型× | 向量自回归 (VAR)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2002-2006 | 1980 |
| 提出者≠ | Engle (2002) for DCC; break-augmented extensions by Pelletier (2006) and subsequent literature | Christopher A. Sims |
| 类型≠ | Multivariate volatility model with regime change | Multivariate time-series model |
| 开创性文献≠ | 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 ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| 别名 | DCC-GARCH with structural breaks, break-adjusted DCC-GARCH, regime-shift DCC-GARCH, SB-DCC-GARCH | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| 相关 | 5 | 5 |
| 摘要≠ | 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. | 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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