Keynote Speakers

Whitney Newey
Ford Professor of Economics at Massachusetts Institute of Technology

Whitney Newey is Ford Professor of Economics at MIT and a Research Associate of the National Bureau of Economic Research. He is a fellow of the Econometric Society and an elected member of the American Academy of Arts Arts and Sciences. He served as chair of MIT Economics, on the Executive Committee of the Econometric Society, co-editor of Econometrica, and program co-chair for the 2005 World Congress of the Econometric Society. Current research interests include debiased machine learning, panel data, and economic models with general heterogeneity.

Bryan Kelly
Professor of Finance at Yale University

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.

Dacheng Xiu
Professor of Econometrics and Statsitics at University of Chicago

Dacheng Xiu’s research interests include developing statistical methodologies and applying them to financial data, while exploring their economic implications. His earlier research involved risk measurement and portfolio management with high-frequency data and econometric modeling of derivatives. His current work focuses on developing machine learning solutions to big-data problems in empirical asset pricing.

Xiu’s work has appeared in Econometrica, Journal of Political Economy, Journal of Finance, Review of Financial Studies, Journal of the American Statistical Association, and Annals of Statistics. He is a Co-Editor for the Journal of Financial Econometrics, an Associate Editor for the Review of Financial Studies, Management Science, Journal of Econometrics, Journal of Business & Economic Statistics, Journal of Applied Econometrics, the Econometrics Journal, and Journal of Empirical Finance. He has received several recognitions for his research, including Fellow of the Society for Financial Econometrics, Fellow of the Journal of Econometrics, Swiss Finance Institute Outstanding Paper Award, AQR Insight Award, and Best Conference Paper Prize from the European Finance Association.