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Calculation of Operational Loss Distribution via Bayesian MCMC Algorithm: Evidence from China's Commercial Banks

机译:贝叶斯MCMC算法计算运营损失分布:来自中国商业银行的证据

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this paper reviews the operational risk data of China's commercial banks from 1994 to 2008, and studies its type of distribution. In order to precisely capture the profile of the operational loss and event distribution of China's commercial banks, we select the operational risk loss distribution type with the Bayesian inference and test the GEV distribution on AIC and BIC standard. As closed-form solutions are not available for the operational risk distributions, we turn to the Bayesian MCMC algorithm for robust test on the selection. The result shows that with the increase of the iterations, the variance of estimated parameters becomes smaller, so we conclude that the operational risk loss distribution for China's commercial banks meets the Generalized Extreme Value (GEV) distribution.
机译:本文综述了1994年至2008年中国商业银行的运营风险数据,研究其分销类型。为了精确地捕捉中国商业银行的运营损失和事件分配的概况,我们选择了贝叶斯推理的操作风险损失分布类型,并测试了对AIC和BIC标准的GEV分布。作为操作风险分布的闭合解决方案,我们转向贝叶斯MCMC算法,以便在选择上进行鲁棒测试。结果表明,随着迭代的增加,估计参数的方差变小,因此我们得出结论,中国商业银行的运营风险损失分布符合广义极值(GEV)分布。

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