Date Thesis Awarded

5-2020

Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)

Department

Mathematics

Advisor

Heather Sasinowska

Committee Members

Larry Leemis

Thomas LaSalvia

Abstract

In this paper the data, modelling and the environmental factors that contributed to the collapse of the US housing market and the high mortgage loan losses during the Great Recession are explored. Deficiencies in data and modelling are discussed with an emphasis on the deficiencies in the mathematical modeling that failed to predict the high level of risk associated with mortgage originations in the mid-2000's. It is suggested that the lack of effective modelling significantly contributed to banks offering aggressive origination guidelines and that this was a major contributing factor that led up to the housing price collapse in the late 2000's.

Aspects of behavioral economics, longer term trends in housing affordability and ownership to rental payment ratios that were insufficiently considered in the quantitative assessment of the risk of default are reviewed.

Original research is included to obtain the perspectives of risk management experts that managed risk through the impacts of the housing collapse, as well as an evaluation of current models utilized in the industry.

The paper concludes with suggestions as how current risk management and modelling processes could be enhanced to better anticipate and manage mortgage risk and to minimize unexpected volatility in mortgage loan losses. Suggestions focus on going beyond classic regression modelling and including behavioral, demographic and affordability factors.

Share

COinS