विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| डीसीसी-गार्च (गतिशील सशर्त सहसंबंध)× | कॉपुला मॉडल (गॉसियन, टी, क्लेटन, गंबेल, फ्रैंक)× | |
|---|---|---|
| क्षेत्र | वित्त | वित्त |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2002 | 1959 |
| प्रवर्तक≠ | Robert F. Engle | Sklar (1959); dependence-concept treatment by Joe (1997) |
| प्रकार≠ | Multivariate volatility model | Dependence model |
| मौलिक स्रोत≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231. link ↗ |
| उपनाम | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) |
| संबंधित | 5 | 5 |
| सारांश≠ | 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. | Copula models are a family of functions that describe the dependence structure between variables separately from their individual (marginal) distributions. The foundation is Sklar's theorem (1959), which shows that any multivariate distribution can be split into its marginals plus a copula; Joe (1997) developed the modern catalogue of dependence concepts. They are central to portfolio risk and credit modelling. |
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