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 three areas: evolutionary models of investor behavior and adaptive markets, quantitative models of financial markets, and healthcare finance. 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; and new statistical tools for predicting clinical trial outcomes, incorporating patient preferences into the drug approval process, and accelerating biomedical innovation via novel business and financing structures.
Lo has published extensively in academic journals (see http://alo.mit.edu) and his most recent book is Adaptive Markets: Financial Evolution at the Speed of Thought. 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 has also received a number of awards, listed here. He is a Fellow of 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 affiliated faculty member of the MIT Department of Electrical Engineering and Computer Science, an external faculty member of the Santa Fe Institute, and a research associate of the National Bureau of Economic Research. He is a member of the New York Federal Reserve Board’s Financial Advisory Roundtable, FINRA’s Economic Advisory Committee, the National Academy of Sciences Board on Mathematical Sciences and Their Applications, Beth Israel Deaconess Medical Center’s Board of Overseers, and the boards of Roivant Sciences and the Whitehead Institute for Biomedical Research.
Lo holds a BA in economics from Yale University and an AM and PhD in economics from Harvard University.
Chaudhuri, Shomesh E., and Andrew W. Lo. Journal of Econometrics. Forthcoming.
Alhamdan, Abdullah, Zachery M. Halem, Irene Hernandez, Andrew W. Lo, Manish Singh, and Dennis Whyte. Journal of Investment Management. Forthcoming. Practitioners Digest.
Xu, Qingyang, Elaheh Ahmadi, Alexander Amini, Daniela Rus, and Andrew W. Lo. Drug Safety. Forthcoming.
Hasanhodzic, Jasmina, Andrew W. Lo, and Emanuele Viola. Journal of Portfolio Management. Forthcoming. SSRN Preprint.
Dou, Winston, Xiang Fang, Andrew W. Lo, and Harald Uhlig. Annual Review of Financial Economics. Forthcoming. SSRN Preprint.
Lo, Andrew W., and Ruixun Zhang. Oxford, UK: Oxford University Press, Forthcoming.
Evolution can drive prejudices, MIT Sloan economist Andrew Lo finds. To nurture group wisdom, biases in data sets must be documented and understood.
Prof. Andrew Lo and co-author created a mathematical model of natural selection on behavior to study the controversial idea of “group selection."
"We need the private sector to put in billions to match the hundreds of millions that the government has dedicated to this effort."
"We all want to have impact. But very few economists are able to do anything that would actually affect patient lives."
"There is evidence of social contagion of investment behavior in financial markets that does not derive from rational information processing."
"We point out that this is a never-ending journey, that we're constantly looking to improve the way we think about investing."
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.
