论文标题
根据俄罗斯银行的数据，间接估算行业目标段默认概率动态的方法
Method of indirect estimation of default probability dynamics for industry-target segments according to the data of Bank of Russia
论文作者
论文摘要
鉴于缺乏统计数据，无法使用行业和目标公司段来计算违约率的直接方法。拟议的论文考虑了一个模型，用于过滤基于俄罗斯银行提供的逾期债务动态的间接数据，以滤除公司公司和其他借款人违约的可能性。该模型基于总债务和逾期债务平衡的方程，相应时间序列的缺失链接是使用Hodrick_prescott过滤方法构建的。在零售贷款领域（抵押，消费者贷款）中，默认统计数据可提供信用局并提供。介绍的方法已在此统计量上进行了验证。在历史性的有限时期，验证表明结果值得信赖。由此产生的默认概率系列是用于部门信用风险的宏观工艺建模的外源变量。
A direct method for calculating default rates by industry and target corporate segments is not possible given the lack of statistical data. The proposed paper considers a model for filtering the dynamics of the probability of default of corporate companies and other borrowers based on indirect data on the dynamics of overdue debt supplied by the Bank of Russia. The model is based on the equation of the balance of total and overdue debts, the missing links of the corresponding time series are built using the Hodrick_Prescott filtering method. In retail lending segments (mortgage, consumer lending), default statistics are available and supplied by Credit Bureaus. The presented method is validated on this statistic. Over a historical limited period, validation has shown that the result is trustworthy. The resulting default probability series are exogenous variables for macro_economic modelling of sectoral credit risks.
