Using a Two-stage Model to Estimate the Loss Given Default Distribution

• Main Authors: Fong-Sian Cing, 馮獻慶
• Other Authors: Chih-Kang Chu
• Format: Others
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/77591969479318458784

碩士 === 國立東華大學 === 應用數學系 === 105 === We propose a new two-stage model to estimate the loss given default (LGD) distribution. The first-stage model is the logistic regression model used to estimate probabilities of LGD equal to 0 and larger 0, respectively. The second-stage model is the right-tail extended beta model applied to generate the distribution of LGD between (0,1) and probability of LGD equal to 1. To implement the newly proposed two-stage model, we collect a sample of 4962 defaulted debts from Moody’s Default and Recovery Database. The empirical results show that the newly proposed two-stage model can generate the accurate LGD distribution estimate. Thus, it is useful for studying the LGD distribution.