This study evaluates the sensitivity and robustness of the systemic risk measure, Conditional Value-at-Risk (CoVaR), estimated using the vine copula and APARCH-DCC models. We compute the CoVaR for the two portfolios across five allocation strategies. The novel vine copula captures the complex dependence patterns and tail dynamics. The APARCH DCC incorporates volatility clustering, skewness, and kurtosis. The results reveal that the CoVaR estimates vary based on portfolio strategy, with higher values for the cryptocurrency portfolio. However, CoVaR appears relatively robust across strategies compared to ΔCoVaR. The cryptocurrency portfolio has a greater overall vulnerability. The findings demonstrate the value of CoVaR estimated via the vine copula and APARCH-DCC in assessing portfolio systemic risk. This advanced approach provides nuanced insights into strengthening risk management practices. Future research could explore the sensitivity of the CoVaR to different weighting schemes, such as equal versus market-weighted portfolios. Incorporating the Gram–Charlier expansion of normal density into the APARCH specification enables a nonparametric, data-driven fitting of the residual distribution. Furthermore, comparing the CoVaR to another systemic risk measure could provide further insights into its reliability as a systemic risk measure.

中文翻译：

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评估投资组合对系统性风险的脆弱性：vine copula 和 APARCH-DCC 方法

本研究评估了使用 vine copula 和 APARCH-DCC 模型估计的系统性风险衡量标准、条件风险值 (CoVaR) 的敏感性和稳健性。我们计算了五种分配策略中两个投资组合的 CoVaR。新颖的 vine copula 捕获了复杂的依赖模式和尾部动态。APARCH DCC 包含波动性聚类、偏度和峰度。结果显示，CoVaR 估计值根据投资组合策略而有所不同，加密货币投资组合的价值更高。然而，与 ΔCoVaR 相比，CoVaR 在各种策略中显得相对稳健。加密货币投资组合的整体脆弱性更大。研究结果证明了通过 vine copula 和 APARCH-DCC 估计的 CoVaR 在评估投资组合系统性风险方面的价值。这种先进的方法为加强风险管理实践提供了细致入微的见解。未来的研究可以探索 CoVaR 对不同权重方案的敏感性，例如等权投资组合与市场权重投资组合。将正态密度的 Gram-Charlier 展开合并到 APARCH 规范中可以实现残差分布的非参数、数据驱动拟合。此外，将 CoVaR 与另一种系统性风险衡量标准进行比较可以进一步了解其作为系统性风险衡量标准的可靠性。