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摘要翻译：
提出了一种新的研究银行操作风险的动态模型，适用于风险价值的计算。该运动方程考虑了银行不同过程之间的相互作用、通过噪声项自发产生的损失以及银行为避免其发生所做的努力。由于该模型是非常通用的，它可以根据特定银行的内部组织结构，从历史经营损失中估计其某些参数。在耦合矩阵中没有因果环的情况下，精确地求解了该模型，并说明了如何利用该解估计噪声参数。用少量的模拟数据来估计模型的参数，研究了模型的预测能力，结果表明，当F=0.75$时，模型的VaR可以预测，误差为10^-3}$。
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英文标题：
《A Dynamical Model for Forecasting Operational Losses》
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作者：
Marco Bardoscia, Roberto Bellotti
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最新提交年份：
2012
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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英文摘要：
A novel dynamical model for the study of operational risk in banks and suitable for the calculation of the Value at Risk (VaR) is proposed. The equation of motion takes into account the interactions among different bank's processes, the spontaneous generation of losses via a noise term and the efforts made by the bank to avoid their occurrence. Since the model is very general, it can be tailored on the internal organizational structure of a specific bank by estimating some of its parameters from historical operational losses. The model is exactly solved in the case in which there are no causal loops in the matrix of couplings and it is shown how the solution can be exploited to estimate also the parameters of the noise. The forecasting power of the model is investigated by using a fraction $f$ of simulated data to estimate the parameters, showing that for $f = 0.75$ the VaR can be forecast with an error $\simeq 10^{-3}$.
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PDF链接：
https://arxiv.org/pdf/1007.0026
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