Mathematical Finance & Financial Data Science Seminar
The Virtue of Complexity
Speaker: Bryan Kelly, Yale University and AQR Capital Management
Location: Online Zoom access provided to registrants
Date: Tuesday, April 26, 2022, 5:30 p.m.
We theoretically characterize the behavior of machine learning portfolios in the high complexity regime, i.e. when the number of parameters exceeds the number of observations. We demonstrate a surprising "virtue of complexity:" Sharpe ratios of machine learning portfolios generally increase with model parameterization, even with minimal regularization. Empirically, we document the virtue of complexity in US equity market timing strategies. High complexity models deliver economically large and statistically significant out-of-sample portfolio gains relative to simpler models, due in large part to their remarkable ability to predict recessions.
This is joint work with Semyon Malamud and Kangying Zhou.
Bryan Kelly is Professor of Finance at the Yale School of Management, a Research Fellow at the National Bureau of Economic Research, Associate Director of SOM’s International Center for Finance, and is the head of machine learning at AQR Capital Management. Professor Kelly’s primary research fields are asset pricing, machine learning, and financial econometrics. He is interested in issues related to expected return, volatility, tail risk, and correlation modeling in financial markets; financial sector systemic risk; financial intermediation; and financial networks. He has served as co-editor of the Journal of Financial Econometrics and associate editor of Journal of Finance and Journal of Financial Economics. Before joining Yale, Kelly was a tenured professor of finance at the University of Chicago Booth School of Business. He earned an AB in economics from University of Chicago, MA in economics from University of California San Diego, and a PhD and MPhil in finance from New York University’s Stern School of Business. Kelly worked in investment banking at Morgan Stanley prior to his PhD.
This event is free, but requires registration. Please click here to register. You will then receive the Zoom link by email about a day or so before the event.