About
Leland Bybee is an Assistant Professor of Finance at the University of Chicago Booth School of Business. He leverages machine learning and natural language processing to address economic and financial questions, particularly focusing on belief measurement with applications to asset pricing and behavioral economics.
- Ph.D. in Financial Economics, Yale School of Management (2024)
- M.S. in Statistics, University of Michigan (2017)
- B.A. in Economics, University of Chicago (2013)
His research integrates computational methods with economic theory to analyze:
- Textual analysis of business news for macroeconomic tracking
- Narrative-driven asset pricing models
- Memory-based belief formation using kernel methods
- Macroeconomic determinants of currency returns
He has received multiple awards including:
- Dimension Fund Advisors Distinguished Paper Award
- BlackRock Applied Research Award
- HEC Top Finance Graduate Award
- The Brattle Group PhD Candidates Award
- EFA Engelbert Dockner Memorial Prize
Bybee teaches Machine Learning in Finance and participates in finance seminars, contributing computational tools like regIPCA (Python) and changepointsHD (R) to the research community.
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