论文标题
使用随机算法估算系统不足的风险度量
Estimation of Systemic Shortfall Risk Measure using Stochastic Algorithms
论文作者
论文摘要
引入了系统性风险措施，以捕获由金融机构互连系统产生的全球风险和相应的传染效应。为此，建议了两种方法。在第一个中，系统性风险措施可以解释为在汇总个人风险后确保系统所需的最小现金量。在第二种方法中，可以将系统性风险措施解释为通过在汇总个人风险之前向每个机构分配资本来确保系统的最小现金。尽管几位作者对这些风险措施的理论进行了很好的研究，但到目前为止，数值部分已经忽略了。在本文中，我们使用随机算法方案来估计MSRM，并证明所得估计器是一致的，并且渐近地正常。我们还在数字上测试了这些算法在几个示例中的性能。
Systemic risk measures were introduced to capture the global risk and the corresponding contagion effects that is generated by an interconnected system of financial institutions. To this purpose, two approaches were suggested. In the first one, systemic risk measures can be interpreted as the minimal amount of cash needed to secure a system after aggregating individual risks. In the second approach, systemic risk measures can be interpreted as the minimal amount of cash that secures a system by allocating capital to each single institution before aggregating individual risks. Although the theory behind these risk measures has been well investigated by several authors, the numerical part has been neglected so far. In this paper, we use stochastic algorithms schemes in estimating MSRM and prove that the resulting estimators are consistent and asymptotically normal. We also test numerically the performance of these algorithms on several examples.
