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arXiv 0904.4075q-fin.RMq-fin.CP
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对超过时变阈值的运营风险数据进行建模

Modeling operational risk data reported above a time-varying threshold

Pavel V. Shevchenko, Grigory Temnov

摘要:

通常情况下,运营风险损失报告高于阈值。拟合在恒定阈值以上报告的数据是公知的和研究的问题。然而,在实践中,损失在拟合之前针对业务和其他因素进行缩放,因此阈值在缩放的数据样本中是变化的。当银行改变其报告政策时,报告级别也可能改变。我们提出了最大似然和贝叶斯马尔可夫链蒙特卡罗方法来拟合频率和严重性损失分布的情况下,随时间变化的阈值的数据。估计的年度损失分布会计参数的不确定性。

英文摘要:

Typically, operational risk losses are reported above a threshold. Fitting data reported above a constant threshold is a well known and studied problem. However, in practice, the losses are scaled for business and other factors before the fitting and thus the threshold is varying across the scaled data sample. A reporting level may also change when a bank changes its reporting policy. We present both the maximum likelihood and Bayesian Markov chain Monte Carlo approaches to fitting the frequency and severity loss distributions using data in the case of a time varying threshold. Estimation of the annual loss distribution accounting for parameter uncertainty is also presented.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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