विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| डीसीसी-गार्च (गतिशील सशर्त सहसंबंध)× | ऑटोरेग्रेसिव इंटीग्रेटेड मूविंग एवरेज (ARIMA) मॉडल× | कॉपुला मॉडल (गॉसियन, टी, क्लेटन, गंबेल, फ्रैंक)× | |
|---|---|---|---|
| क्षेत्र≠ | वित्त | अर्थमिति | वित्त |
| परिवार | Regression model | Regression model | Regression model |
| उद्भव वर्ष≠ | 2002 | 2015 | 1959 |
| प्रवर्तक≠ | Robert F. Engle | Box & Jenkins (Box-Jenkins methodology) | Sklar (1959); dependence-concept treatment by Joe (1997) |
| प्रकार≠ | Multivariate volatility model | Univariate time-series 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 ↗ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | 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 | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) |
| संबंधित | 5 | 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. | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | 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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