I am an economics PhD candidate at the University of Pennsylvania. My interests lie at the intersection of econometrics, finance, and machine learning. In particular, I study how uncertainty and learning interact in driving risk in the big data environments we now live in. In particular, I develop machine learning and Bayesian methods to identify and measure these risks and study their asset pricing implications.
In my job market paper, I build an interpretable nonparametric framework relating high-frequency and daily returns. This framework provides a sufficient statistic for time-varying news risk, which I estimate using high-frequency data. I use this to identify how investors' risk aversion and time-inseparable preferences interact in driving risk premia.