Leonid Kogan

Leonid Kogan is the Nippon Telegraph and Telephone Professor of Management and a Professor of Finance at the MIT Sloan School of Management. He is also the faculty leader for the MFin degree program.

Prior to MIT Sloan, Kogan taught at the Wharton School of the University of Pennsylvania. During 2007–08, he was a senior researcher at Lehman Brothers. His research interests include asset pricing theory, macro-finance, empirical asset pricing, and financial engineering. Kogan’s recent research has focused on the links between economic activity of firms and their stock price behavior, the effects of investor heterogeneity on aggregate asset prices, and the computational aspects of option pricing and portfolio choice.

Kogan has published extensively in leading academic journals, including The Journal of Finance, the Journal of Financial Economics, the Journal of Political Economy, and Operations Research. He has won numerous professional awards, including the 1998 Lehman Brothers Fellowship for Research Excellence in Finance for his work on the asset pricing implications of investment irreversibility; the 2004 FAME Research Prize, and the 2006 Smith-Breeden Prize for his work on the price impact and survival of irrational traders; and the 2007 Crowell Memorial Prize for his work on output durability and stock returns. He is currently a Research Associate at the National Bureau of Economic Research.

Kogan holds an MSc in mechanics and applied mathematics from Moscow State University, a PhD in mechanics from Cornell University, and a PhD in finance from MIT.

Current Research Focus: Kogan works on topics in asset pricing and capital markets. His recent projects include: theoretical and empirical analysis of the impact of technological progress on labor income risk and inequality, stock prices, and inflation;  quantitative analysis of information content of patents using large language models; simulation of stock market dynamics using generative AI; development of new statistical methods for measuring the robustness of asset pricing models;  valuation of crypto assets and analysis of automated market-making.