CAJ | 학술논문

本文借助KMV模型框架，对商业银行拥有的大量公司财务报表数据运用统计方法进行模型参数估计，计算得到了非上市公司的违约距离和经验函数，实现了违约概率的模型估计。实证表明，我国公司在违约距离或违约数量上的真实概率分布均呈现显著的T分布和肥尾特性；违约距离具有较高的风险区分能力；由会计信息进行参数估计的模型导出的具有较高的风险标志精度；进而表明基于会计报表数据的违约风险模型和基于资本市场数据的模型在实证上的有效性非常近似。
본문차조KMV모형광가，대상업은행옹유적대량공사재무보표수거운용통계방법진행모형삼수고계，계산득도료비상시공사적위약거리화경험함수，실현료위약개솔적모형고계。실증표명，아국공사재위약거리혹위약수량상적진실개솔분포균정현현저적T분포화비미특성；위약거리구유교고적풍험구분능력；유회계신식진행삼수고계적모형도출적구유교고적풍험표지정도；진이표명기우회계보표수거적위약풍험모형화기우자본시장수거적모형재실증상적유효성비상근사。
Based on the principle of KMV model and statistical method and using internal financial data of commercial banks to estimate the parameters of KMV model, this paper simulates the distance to default and the EDF for non-listed companies and calculates the probability of default. The research demonstrates that the distribution of samples has the characteristic of T distribution and ＂fat tail＂, the distance to default has a more precise ability to distinguish the credit risk, the EDF which based on financial data can reveals the degree of credit risk exactly, the model based on bond market data and financial data have the same efficiency for the default risk estimation.