事前信用风险估计的违约概率模型

Anna Burova, H. Penikas, S. Popova
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引用次数: 1

摘要

真正衡量事前信用风险的方法是将借款人的财务状况与违约几率联系起来。对借款人财务状况的理解是由其填满的财务报表的衍生品来代替的,即财务比率。我们确定了入围财务比率与随后违约事件之间的统计显著关系,并开发了违约概率(PD)模型,该模型评估了借款人在一年内违约的可能性。我们将PD模型与在银行风险承担的相关文献中广泛使用的事前信用风险替代度量进行比较,即银行分配给债权人的信用质量组(审慎准备金率)和利率中的信用息差。我们发现,与审慎准备金率相比,PD模型在一年的范围内更准确地预测违约事件。我们得出结论,开发的事前信用风险度量对于估计银行的冒险行为和分析投资组合构成的变化是可行的。
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Probability of Default Model to Estimate Ex Ante Credit Risk
A genuine measure of ex ante credit risk links borrower’s financial position with the odds of default. Comprehension of a borrower’s financial position is proxied by the derivatives of its filled financial statements, i.e., financial ratios. We identify statistically significant relationships between shortlisted financial ratios and subsequent default events and develop a probability of default (PD) model that assesses the likelihood of a borrower going into delinquency at a one-year horizon. We compare the PD model constructed against alternative measures of ex ante credit risk that are widely used in related literature on bank risk taking, i.e., credit quality groups (prudential reserve ratios) assigned to creditors by banks and the credit spreads in interest rates. We find that the PD model predicts default events more accurately at a horizon of one year compared to prudential reserve rates. We conclude that the measure of ex ante credit risk developed is feasible for estimating risk-taking behaviour by banks and analysing shifts in portfolio composition.
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