Assessing portfolio vulnerability to systemic risk: a vine copula and APARCH-DCC approach

Abstract

Abstract 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.

Keywords

• Cryptocurrency
• Systemic risk
• Vulnerability
• CoVaR