We propose a vine copula model based on a bivariate extended skew-t distribution and derive its corresponding multivariate tail dependence function. Our simulations demonstrate that the proposed estimator dominates the conventional vine copula approach in the estimation of multivariate tail dependence. We apply our model to a safe haven analysis of US dollars (US$) and gold prices against stocks. The estimated multivariate lower tail dependence coefficients suggest that even though either US$ or gold can be safe haven assets against stocks, combining US$ and gold in a portfolio does not provide a safe haven property against stocks. Therefore, incorporating multiple safe haven assets in a portfolio may end in heavier losses in the event of a market downturn. Our results highlight the importance of simultaneously investigating multiple safe haven assets in financial risk analysis.

中文翻译：

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持有多个避风港能否改善投资组合的多元化？扩展的 skew-t vine copula 方法

我们提出了一个基于二元扩展偏斜分布的藤蔓 copula 模型，并推导出其对应的多元尾依赖函数。我们的模拟表明，所提出的估计器在估计多变量尾部依赖性方面主导了传统的藤蔓 copula 方法。我们将我们的模型应用于美元 (US$) 和黄金价格对股票的避险分析。估计的多元低尾相关系数表明，即使美元或黄金都可以是股票的避险资产，但将美元和黄金组合在投资组合中并不能提供股票的避险资产。因此，在市场低迷的情况下，将多个避险资产纳入投资组合可能会导致更大的损失。