PhD student, University of Chicago Booth School of Business.
Rui Da’s research lies in the intersection of finance and econometrics. It aims to to develop empirical methodologies that allow and facilitate empirical understanding of financial markets and institutions.
In past work he has combined insights from asset pricing and econometrics to measure the risk of financial market utilizing transaction-level stock price data.
His current research focuses on formal understanding of the empirical content of finance theories and application of machine learning methods to financial data.
Prior to joining Booth in 2016, Da studied in the physics PhD program at Princeton University and received a BS in physics from Nanjing University.