Hi, I'm Steven Fortney

I am currently an Applied Scientist working at Uber on research projects relating to NLP and causal machine learning. Follow this space where I plan to post periodic updates on my outward-facing research!

Prior to joining Uber I was a Post-Doctoral Research Associate at the Yale School of Management. I graduated with my PhD in Financial Economics from Yale University in 2021.

During my PhD, my research interests included corporate finance, financial contracting, banking, machine learning and textual analysis. In my research I use tools from machine learning and natural language processing to make sense of the complexity of textual data in finance. A particular emphasis of my research agenda focuses on the importance of debt covenants in all of their forms. My job market paper uses a natural language processing technique which is unique to my paper to assemble a novel database of the universe of syndicated lending covenants from unstructured text data. I use this data to understand how corporate bond and loan contracts use debt covenants heterogeneously and how they interact. Another one of my papers looks at affirmative covenants in syndicated lending contracts and shows that they act as a 'pre-tripwire' for lenders. Other co-authored papers explore questions such as corporate refinancings and the effects of SNAP benefits on consumer behavior.

Contact Information

Email: steven.fortney@uber.com

For more details click here: CV