Thesis description

Asset securitization is a process of converting illiquid bank assets to marketable securities. Despite concrete efforts to enhance transparency and bolster the resilience and integrity of the securitization process, the market for securitized assets within the EU has yet to return to its pre-2008 level. Compared to the volume of securitizations issued in the United States, Europe's figures are significantly lower. This shortfall highlights the market's failure to rebound to its former transaction volumes and leverage its potential to bolster European market competitiveness. 

You will explore the performance of securitized pools and underlying loans and assess how different supervisory rules shape the securitization volumes and underlying loan riskiness. You will empirically test hypotheses arising from the associated research questions using quantitative empirical methods in a difference-in-difference setting such as OLS, linear probability model, and non-linear models.

What we are looking for:

• You have an excellent academic track record with a current GPA of at least 2.0
• You are currently completing a master’s programme in Management & Technology (with major in “Finance & Accounting”) or Finance and Information Management and have passed two of the following four courses: Asset Management, Derivatives, International Capital Markets and Investment Practice or Advanced Seminar: Finance & Accounting.
• Your bachelor’s degree included a Corporate finance course
• You have some knowledge of empirical methods
• You have already used Python, Stata, or R or are willing to learn how to use them
• You have strong analytical and project management skills
• You have a passion for finance and a keen interest in academia 

What we offer:

• Close supervision, helping you to expand your skillset
• Learn how to conduct empirical research and apply quantitative methods using statistical software
• Participate in seminars by leading scholars in finance, giving you exposure to the current state of research 

If interested, please send an e-mail with CV and academic transcript to aida.cehajic@tum.de.

In case of any questions, please contact Aida Cehajic (aida.cehajic@tum.de).