Date of Award
Spring 5-19-2017
Additional Affiliations
Statistics
Degree Name
Master of Arts (AM/MA)
Degree Type
Thesis
Abstract
The unexpected increase in loan default on the mortgage market is widely considered to be one of the main cause behind the economic crisis. To provide some insight on loan delinquency and default, I analyze the mortgage performance data from Fannie Mae website and investigate how economic factors and individual loan and borrower information affect the events of default and prepaid. Various delinquency status including default and prepaid are treated as discrete states of a Markov chain. One-step transition probabilities are estimated via multinomial logistic models. We find that in general current loan-to-value ratio, credit score, unemployment rate, and interest rate significantly affect the transition probabilities to different delinquency states, which lead to further default or prepaid events.
Language
English (en)
Chair and Committee
Jimin Ding
Committee Members
Todd Kuffner, Renato Feres
Recommended Citation
Yang, Shuyao, "Mortgage Transition Model Based on LoanPerformance Data" (2017). Arts & Sciences Electronic Theses and Dissertations. 1055.
https://openscholarship.wustl.edu/art_sci_etds/1055
Comments
Permanent URL: https://doi.org/10.7936/K72B8WGC