方法对比
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| 高斯、t、Clayton、Gumbel、Frank 联结模型× | VaR（风险价值）× | |
|---|---|---|
| 领域 | 金融学 | 金融学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1959 | 2007 |
| 提出者≠ | Sklar (1959); dependence-concept treatment by Joe (1997) | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan |
| 类型≠ | Dependence model | Financial risk measure |
| 开创性文献≠ | 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 ↗ | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 |
| 别名≠ | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) | VaR, value-at-risk, delta-normal VaR, historical simulation VaR |
| 相关 | 5 | 5 |
| 摘要≠ | 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. | Value at Risk is a financial risk measure that estimates the maximum loss a position or portfolio could suffer over a fixed holding period at a given confidence level. It is the standard benchmark in risk management and regulatory capital calculations, developed in the textbook tradition of Jorion (2007) and the Basel market-risk framework. |
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