A concept of copula robustness and its applications in quantitative risk management
提出连接函数稳健性的一般概念和判定准则，并通过量化风险管理的实例说明，帮助从业者判断当连接函数存在偏差时，风险特征是否仍然可靠。
Abstract In financial and actuarial applications, marginal risks and their dependence structure are often modelled separately. While it is sometimes reasonable to assume that the marginal distributions are ‘known’, it is usually quite involved to obtain information on the copula (dependence structure). Therefore copula models used in practice are quite often only rough guesses. For many purposes, it is thus relevant to know whether certain characteristics derived from $d$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>d</mml:mi></mml:math> -variate risks are robust with respect to (at least small) deviations in the copula. In this article, a general concept of copula robustness is introduced and criteria for copula robustness are presented. These criteria are illustrated by means of several examples from quantitative risk management. The concept of aggregation robustness introduced by Embrechts et al. (Finance Stoch. 19:763–790, 2015) can be embedded in our framework of copula robustness.