风险相关性下的银行非预期操作风险集成度量——基于动力学模型视角

Unexpected operational risk aggregation considering risk correlation: A dynamical modeling perspective

依据我国商业银行1994年~2012年操作风险历史数据,建立考虑不同时点风险单元间相关性的动力学模型来描述操作风险损失产生、传导及演化的机制.该模型指出操作风险损失产生的机制有三种:自发产生的损失、不同事件类型之间的相互影响以及银行覆盖预期损失的资本金储备.通过对损失演化模型的仿真计算,获得具有低频高损特征的非预期操作风险损失情景模拟,并计算年度总体非预期损失的VaR.实证结果表明:动力学模型能够很好地描述不同风险事件类型间不同时点的相依性结构,并通过稳健性检验;在较高置信水平下,线性叠加VaR会高估风险,高估程度会随置信水平的提升而提升;内部欺诈已成为中国商业银行操作风险最主要的风险事件类型.

Based on historical operational loss data in Chinese commercial banks from year 1994 to 2012,a dynamical model containing different-time correlations is established to describe the mechanism of unexpected loss occurrence,transmission and evolution. The model takes into account the interactions among different event types,the spontaneous generation of losses and the economical capital reservation set by banks to cover expected losses. Through simulations of loss evolution model,unexpected operational risk loss scenarios（ low frequency high severity） and calculation of one-year VaR of total unexpected aggregate losses can be achieved.The empirical results demonstrate that the dynamical model is good for description of different-time dependence structures among event types and can pass the robustness test. At a high confidence level,additive sum of VaR systematically overestimates total risk and the degree of overestimation will go up with rising of confidence level. Internal fraud has become a main type of operational risk in Chinese commercial banks.