قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| نموذج الارتباط الشرطي الديناميكي (DCC-GARCH)× | نموذج الانحدار الذاتي المتجهي (VAR)× | |
|---|---|---|
| المجال≠ | التمويل | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 2002 | 2005 |
| صاحب الطريقة≠ | Robert F. Engle | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| النوع≠ | Multivariate volatility model | Multivariate time-series model |
| المصدر التأسيسي≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| الأسماء البديلة | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| ذات صلة≠ | 5 | 4 |
| الملخص≠ | 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. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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