摘要
在度量操作风险时,由于数据不足的问题可能造成监管资本配置的偏差,进而导致防范和控制风险的能力降低.本文在对操作风险度量模型分析的基础上,应用贝叶斯推断来度量操作风险.结合实际数据,对操作风险的损失频率和损失金额的分布函数进行了估计,并利用蒙特卡罗模拟方法对操作风险损失值进行了模拟.实证分析表明:应用贝叶斯推断来度量操作风险,可以较好地解决目前操作风险损失事件数据不足的问题.
The key problem is scarce of data about operational risk event in measuring operational risk, and it will lead to deflection of regulating capital collocation and low capacity of precautioning and controlling risk. This paper measures the operational risk applying Bayesian inference based on analysis of measuring model of operational risk. The distribution of loss frequency and loss amount of operation loss event were estimated by using actual data. The loss amount of operational risk was simulated by means of Monte Carlo simulation. By the empirical analysis the result shows that the problem of scarce of data about operational risk event can be solved well by applying Bayesian inference to measure the operational risk.
出处
《系统工程学报》
CSCD
北大核心
2009年第3期286-292,349,共8页
Journal of Systems Engineering
关键词
操作风险
贝叶斯推断
蒙特卡罗模拟
operational risk
Bayesian inference
Monte Carlo simulation
