Article ID: | iaor2006874 |
Country: | United States |
Volume: | 35 |
Issue: | 3 |
Start Page Number: | 215 |
End Page Number: | 229 |
Publication Date: | May 2005 |
Journal: | Interfaces |
Authors: | Smith L. Douglas, Bilir Canser, Huang Vega W., Hung Kuo-yao, Kaplan Mark |
Keywords: | computers, forecasting: applications |
A new type of hybrid loan in Taiwan consists of a traditional residential mortgage with an attached line of credit. Motivated by declines in Taiwanese property values and unexpected credit losses on all types of loans secured by residential real estate, we developed new statistical models for analyzing the credit risk on traditional mortgages, the hybrid loans, and pure equity lines of credit. Nonstationary Markovian models represent probabilities of transition among different financial states for the three credit instruments. We used logistic and regression models to estimate the losses on defaulted loans and the utilization of credit lines. We calibrated the models with account-level data and integrated them into comprehensive forecasting models that revealed differences in risk profiles among the three types of credit and among different segments of each portfolio.