Faculty
Andrew W. Lo is the Charles E. and Susan T. Harris Professor, a Professor of Finance, and the Director of the Laboratory for Financial Engineering at the MIT Sloan School of Management.Lo's current research spans four areas: evolutionary models of investor behavior and adaptive markets, artificial intelligence and financial technology, healthcare finance, and impact investing. Recent projects include: an evolutionary explanation for bias and discrimination and how to reduce their effects; a new analytical framework for measuring the impact of impact investing; the potential for large language models to provide trustworthy financial advice to retail investors; new statistical tools for predicting clinical trial outcomes, incorporating patient preferences into the drug approval process; and accelerating innovation in deep tech via novel business, financing, and payment models.Lo has published extensively in academic journals (see http://alo.mit.edu) and his most recent book is The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics. His awards include Batterymarch, Guggenheim, and Sloan Fellowships; the Paul A. Samuelson Award; the Eugene Fama Prize; the IAFE-SunGard Financial Engineer of the Year; the Global Association of Risk Professionals Risk Manager of the Year; the Harry M. Markowitz Award; the Managed Futures Pinnacle Achievement Award; one of TIME’s “100 most influential people in the world”; and awards for teaching excellence from both Wharton and MIT. His book Adaptive Markets: Financial Evolution at the Speed of Thought has also received a number of awards. He is a Fellow of the American Finance Association, Academia Sinica, the American Academy of Arts and Sciences, the Econometric Society, and the Society of Financial Econometrics.Lo is also a principal investigator at the MIT Computer Science and Artificial Intelligence Laboratory, an external faculty member of the Santa Fe Institute, and a research associate of the National Bureau of Economic Research. He has co-founded several asset management and biotech companies, and sits on the boards of several for-profit and non-profit public and private healthcare organizations.Lo holds a BA in economics from Yale University and an AM and PhD in economics from Harvard University.
Hasanhodzic, Jasmina, Andrew W. Lo, and Emanuele Viola. Journal of Portfolio Management. Forthcoming. SSRN Preprint.
Thakor, Richard T. and Andrew W. Lo. Research Policy. Forthcoming. SSRN Preprint.
Lo, Andrew W., and Ruixun Zhang. Oxford, UK: Oxford University Press, Forthcoming.
Chaudhuri, Shomesh E., Zied Ben Chaouch, Brett Hauber, Brennan Mange, Mo Zhou, Stephanie Christopher, Dawn Bardot, Margaret Sheehan, Anne Donnelly, Lauren McLaughlin, Brittany Caldwell, Heather L. Benz, Martin Ho, Anindita Saha, Katrina Gwinn, Murray Sheldon, and Andrew W. Lo. Journal of Biopharmaceutical Statistics. Forthcoming.
Lo, Andrew W. and Dennis G. Whyte, Working Paper. October 2024.
Lo, Andrew W. and Ruixun Zhang. Vol. 70, No. 10 (2024): 7161-7186.
In a research paper MIT professors Andrew W. Lo and Dennis G. Whyte propose five initiatives for accelerating progress in fusion based on lessons learned from the last 50 years of biotechnology.
Marta Ortega-Valle, SF ’08, is addressing one of the most pressing challenges faced by farmers: crop threats. She co-founded GreenLight Biosciences with fellow MIT alumni to help farmers create sustainable agricultural systems through the integration of science with technology.
The glaring problem with publicly available AI tools is that they're "inherently sociopathic."
"An LLM (Large Language Model) can role-play a financial advisor convincingly and often accurately for a client."
In this podcast episode, professor Andrew W. Lo shared his journey from academia to entrepreneurship.
"The stakes are high. There's a lot of money in this space, a lot of financial advisors, and a lot of problems with having bad financial advice."
This online program from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) challenges common misconceptions surrounding AI and will equip and encourage you to embrace AI as part of a transformative toolkit. With a focus on the organizational and managerial implications of these technologies, rather than on their technical aspects, you’ll leave this course armed with the knowledge and confidence you need to pioneer its successful integration in business.
Machine learning, a branch of artificial intelligence, is the science of programming computers to improve their performance by learning from data. Dramatic progress has been made in the last decade, driving machine learning into the spotlight of conversations surrounding disruptive technology. This six-week online program from the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) aims to demystify machine learning for the business professional – offering you a firm, foundational understanding of the advantages, limitations, and scope of machine learning from a management perspective.
