Graduation Year


Date of Submission


Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts



Reader 1

George Batta

Reader 2

Weiqing Gu

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Terms of Use for work posted in Scholarship@Claremont.


This study evaluates the performance of linear model trees to forecast recovery rates of defaulted bonds. The linear model trees are built based on regression trees, with a linear regression model in each leaf. I use bond characteristics, firm characteristics, industry indicators, and macroeconomic indicators as explanatory variables. The relevance of explanatory variables is assessed using the Mutual Information Feature Selection method. The results show that the linear model trees present better out-of-sample forecasts of recovery rates in comparison with some other widely-used models.

This thesis is restricted to the Claremont Colleges current faculty, students, and staff.