Default Estimation and Expert Information
针对银行中风险贷款违约率估计问题，提出贝叶斯方法，利用行业专家先验信息，并扩展二项模型以处理违约相关性，通过ε混合先验检验稳健性。
Default is a rare event, even in segments in the midrange of a bank's portfolio. Inference about default rates is essential for risk management and for compliance with the requirements of Basel II. Most commercial loans are in the middle-risk categories and are to unrated companies. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using a prior distribution assessed from an industry expert. The binomial model, most common in applications, is extended to allow correlated defaults. A check of robustness is illustrated with an ε-mixture of priors.