银行集中信用违约预警模型

集中信用违约会导致银行遭受重大亏损，甚至面临破产风险.在假定银行开展业务和集中信用违约同时发生的基础上，利用冲击模型构建了一种新的银行集中信用违约预警模型.银行开展业务时，先确定一个合理的预警域.当违约的时间间隔小于预警域时，银行就采取相应的风险防范措施：相反，当违约的时间间隔大于预警域时，银行就不采取任何措施.在其它参数不变的条件下，违约速度上升的越大，真实生存函数与假想生存函数之间的差值也就越大，银行也就能够更好地预警集中信用违约.算例表明：当集中信用违约在时间上随机发生的时候，模型也能够很好地进行预警.

Early warning model of concentrated credit defaults for bank

The concentrated defaults may result in bank's large loss and bankruptcy. Assuming that concentrated credit defaults happen when the bank's business begins, a new kind of early warning model is constructed through the shock model. When the business starts, the bank makes a warning region. When a default interval falls into the region, bank will take measures to lower risk; otherwise, the bank will ignore the risk. Under the condition that other parameters are unchanged, larger the default speed is, greater the difference between the true survival and the imaginary function is. So the bank can warn the risk early. Finally, it is found that the model can also be used well in the situation in which the moment of changing speed is random through numerical examples.