Estimating default probabilities for no- and low-default portfolios: parameter specification via floor constraints
针对低违约和无违约组合，提出用下限约束确定贝叶斯先验分布的尺度参数，以解决违约概率估计中参数设定的难题，对金融机构信用评级建模有参考价值。
Abstract For low- and no-default portfolios, financial institutions are confronted with the problem to estimate default probabilities for credit ratings for which no default was observed. The Bayesian approach offers a solution but brings the problem of the parameter assignment of the prior distribution. Sequential Bayesian updating allows to settle the question of the location parameter or mean of the prior distribution. This article proposes to use floor constraints to determine the scale or standard deviation parameter of the prior distribution. The floor constraint can also be used to determine the free parameter γ in the Pluto–Tasche approach.