Researcher ORCID Identifier


Graduation Year


Date of Submission


Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts



Reader 1

George Batta

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2022 Raj Bhutoria


EBITDA is a widely used metric of corporate profitability, used in the vast majority of US syndicated loan agreements; however, minimal research has occurred regarding variation within the contract-to-contract definition of EBITDA. Using machine learning techniques, we extract and analyze significant variation in the contractual definition of EBITDA and construct a ‘permissiveness’ index of the number of adjustments included in EBITDA definitions. We demonstrate that permissiveness is associated with riskier loans and larger firm size. Our findings also suggest permissiveness enhances the informativeness of riskier loan agreements by refining EBITDA to better reflect the borrower’s true financial condition; however, we find this is not a costless endeavor. We find that permissiveness is positively related to credit spreads, suggesting that higher permissiveness in EBITDA definitions may increase creditor’s risk by increasing the incidence of ‘false negative’ financial covenant violations.

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