Asymptotic subadditivity/superadditivity of Value‐at‐Risk under tail dependence

• Published in: Mathematical finance Vol. 33; no. 4; pp. 1314 - 1369
• Main Authors: Zhu, Wenhao, Li, Lujun, Yang, Jingping, Xie, Jiehua, Sun, Liulei
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.10.2023
• Subjects: Asymptotic methods; Asymptotic properties; Dependence; Empirical analysis; Random variables; Risk; Value; Values
• ISSN: 0960-1627; 1467-9965
• DOI: 10.1111/mafi.12393

Abstract This paper presents a new method for discussing the asymptotic subadditivity/superadditivity of Value‐at‐Risk (VaR) for multiple risks. We consider the asymptotic subadditivity and superadditivity properties of VaR for multiple risks whose copula admits a stable tail dependence function (STDF). For the purpose, a marginal region is defined by the marginal distributions of the multiple risks, and a stochastic order named tail concave order is presented for comparing individual tail risks. We prove that asymptotic subadditivity of VaR holds when individual risks are smaller than regularly varying (RV) random variables with index −1 under the tail concave order. We also provide sufficient conditions for VaR being asymptotically superadditive. For two multiple risks sharing the same copula function and satisfying the tail concave order, a comparison result on the asymptotic subadditivity/superadditivity of VaR is given. Asymptotic diversification ratios for RV and log regularly varying (LRV) margins with specific copula structures are obtained. Empirical analysis on financial data is provided for highlighting our results.