2022 Program

Lin William Cong is the Rudd Family Professor of Management and Associate Professor of Finance at the Johnson Graduate School of Management at Cornell University SC Johnson College of Business. He is also the founding faculty director for the FinTech Initiative at Cornell. Prior to joining Cornell, he was an assistant professor of Finance and Ph.D. advisor at the University of Chicago Booth School of Business and faculty member at the Center for East Asian Studies. He is a a Kauffman Junior Faculty Fellow, a Poets & Quants World Best Business School Professor, a former doctoral fellow at the Stanford Institute for Innovation in Developing Economies, and a former George Shultz Scholar at the Stanford Institute for Economic Policy Research. Cong serves as associate editor for Management Science, Journal of Financial Intermediation, Journal of Corporate Finance, and the Journal of Banking and Finance, has advised FinTech organizations such as Wall Street Blockchain Alliance and ChainLink, was consulted for regulators’ lawsuits against KIN/Kik and Telegram’s TON regarding their ICOs, as well as for the incubation of Dfinity and its initial research. Cong is a member of multiple professional organizations such as the American Economic Association, European Finance Association, and the Econometric Society.

Kay Giesecke is Professor of Management Science & Engineering at Stanford University. He is the Director of the Advanced Financial Technologies Laboratory and the Director of the Mathematical and Computational Finance Program. Kay is a member of the Institute for Computational and Mathematical Engineering. He serves on the Governing Board and Scientific Advisory Board of the Consortium for Data Analytics in Risk. He is a member of the Council of the Bachelier Finance Society.
Kay is currently on leave from Stanford to lead infima Technologies, a startup company building a prediction service for the $25T credit markets.
Kay is a financial technologist and engineer. He develops stochastic financial models, designs statistical methods for analyzing financial data, examines simulation and other numerical algorithms for solving the associated computational problems, and performs empirical analyses. Much of Kay’s work is driven by important applications in areas such as credit risk management, investment management, and, most recently, housing finance. His research has been funded by the National Science Foundation, JP Morgan, State Street, Morgan Stanley, Swiss Re, American Express, Moody’s, and several other organizations.

Stefan Nagel’s research focuses on asset pricing, investor behavior, and risk-taking of financial intermediaries. His most recent work explores the role of personal experiences in shaping expectations about the macroeconomy and financial market returns, novel approaches for measurement of bank tail risk exposures, and the application of machine learning techniques to understand the risk and return of investment strategies in the stock market. Nagel has won various awards for his research, among them the Smith-Breeden Prize of the American Finance Association for the best paper in the Journal of Finance in 2004 and the Fama/DFA prize for the best asset pricing paper in the Journal of Financial Economics in 2006 (first prize) and 2010 (second prize).
Professor Nagel currently serves as the Executive Editor of the Journal of Finance, one of the leading academic finance journals in the world. Previously, he was an editor at the Review of Financial Studies from 2014-2015 and an associate editor at various top journals. He is also a research associate at the National Bureau of Economic Research (Cambridge, MA) and a research fellow at the Centre for Economic Policy Research (London, UK) and CESifo.