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Dynamic asymmetric tail dependence structure among multi-asset classes for portfolio management: Dynamic skew-t copula approach

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  • Ito, Kakeru
  • Yoshiba, Toshinao

Abstract

This study proposes AC dynamic skew-t copula with cDCC model to capture the dynamic asymmetric tail dependence structure among multi-asset classes (government bonds, corporate bonds, equities, and REITs). We provide new evidence that lower tail dependence coefficients increased compared to upper ones for all pairs in the COVID-19 crash and the recent high inflation period, indicating that the diversification effect through multi-asset investment decreased. Our empirical analysis also shows that in terms of AIC and BIC, dynamic AC skew-t copula fits data of multi-asset classes better than other dynamic elliptical copulas because it can consider the above dependence structure characteristics. Furthermore, out-of-sample analysis reveals that considering an asymmetry of tail dependence structure at each point with an AC dynamic skew-t copula enhances expected shortfall (ES) estimation accuracy and the performance of a minimum ES portfolio. These results indicate that capturing dynamic asymmetric tail dependence is crucial for multi-asset portfolio management.

Suggested Citation

  • Ito, Kakeru & Yoshiba, Toshinao, 2025. "Dynamic asymmetric tail dependence structure among multi-asset classes for portfolio management: Dynamic skew-t copula approach," International Review of Economics & Finance, Elsevier, vol. 97(C).
  • Handle: RePEc:eee:reveco:v:97:y:2025:i:c:s1059056024007160
    DOI: 10.1016/j.iref.2024.103724
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