השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מודלי קופולה (גאוסיאנית, t, קלייטון, גומבל, פרנק)× | Exponential GARCH (EGARCH)× | |
|---|---|---|
| תחום≠ | מימון | אקונומטריקה |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1959 | 1991 |
| הוגה השיטה≠ | Sklar (1959); dependence-concept treatment by Joe (1997) | Nelson |
| סוג≠ | Dependence model | Conditional volatility model (asymmetric GARCH variant) |
| מקור מכונן≠ | 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 ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| כינויים | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| קשורות≠ | 5 | 4 |
| תקציר≠ | 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. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. |
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