Andrew W. Lo

Faculty

Andrew W. Lo

Support Staff

Get in Touch

Title

About

Academic Groups

Academic Area

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.

Honors

Lo wins 2021 digital teaching award

Lo wins Jamieson Prize

Pinnacle Achievement Award Given to Lo

GARP honors Lo as Risk Manager of the Year

Lo’s book wins PROSE Award

Markowitz Award given to Lo

Publications

"Hedging Derivative Securities and Incomplete Markets: An e-Arbitrage Approach."

Bertsimas, Dimitris, Leonid Kogan and Andrew W. Lo. Operations Research Vol. 49, No. 3 (2001): 372–397.

"When Is Time Continuous?"

Bertsimas, Dimitris, Leonid Kogan and Andrew W. Lo. Journal of Financial Economics Vol. 55, No. 2 (2000): 173–204.

"Optimal Control of Execution Costs for Portfolios."

Bertsimas, Dimitris, Andrew W. Lo and Paul Hummel. Computing in Science & Engineering Vol. 1, No. 6 (1999): 40–53.

"Optimal Control of Execution Costs."

Bertsimas, Dimitris and Andrew W. Lo. Journal of Financial Markets Vol. 1, No. 1 (1998): 1–50.

"130/30: The New Long-Only."

Lo, Andrew W. and Pankaj N. Patel. Journal of Portfolio Management Vol. 34, No. 2 (2008): 12-38.

"A Brain Capital Grand Strategy: Toward Economic Reimagination."

Smith, Erin, Diab Ali, Bill Wilkerson, Walter D. Dawson, Kunmi Sobowale, Charles Reynolds III, Michael Berk, Helen Lavretsky, Dilip Jeste, Chee Ng, Jair C. Soares, Gowri Aragam, Zoe Wainer, Husseini K. Manji, Julio Licinio, Andrew W. Lo, Eric Storch, Ernestine Fu, Marion Leboyer, Ioannis Tarnanas, Agustin Ibanez, Facundo Manes, Sarah Caddick, Howard Fillit, Ryan Abbott, Ian H. Robertson, Sandra B. Chapman, Rhoda Au, Cara M. Altimus, William Hynes, Patrick Brannelly, Jeffrey Cummings, and Harris A. Eyre. Molecular Psychiatry Vol. 26, (2021): 3-22.

Load More

Recent Insights

Ideas Made to Matter

The top 10 MIT Sloan news stories of 2021

From a machine learning explainer to trends in data and artificial intelligence, here are the stories that readers needed most this year.

Read Article
Ideas Made to Matter

Reading list: 5 MIT books from 2021

New books about the future of AI, working remotely, the COVID-19 vaccine, and how to build the perfect portfolio.

Read Article
Load More

Media Highlights

Executive Education

Executive Education Course

Machine Learning 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.

  • Jun 8–Jul 26, 2022
  • Aug 17–Oct 4, 2022
  • Oct 26–Dec 13, 2022
View Course
Executive Education Course

Artificial Intelligence

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.

  • Jun 15–Aug 2, 2022
  • Aug 3–Sep 20, 2022
  • Sep 14–Nov 1, 2022
  • Oct 26–Dec 13, 2022
View Course