Andrew Lo (Massachusetts Institute of Technology)
David Brower Center, 2150 Allston Way, Berkeley
Financial AI seems so close, yet so far. We have automated trading algorithms, machine-learning models of credit risk, electronic exchanges, robo advisors, and cryptocurrencies, but machines still haven’t replaced portfolio managers, financial advisors, and bankers. So what’s missing? Not artificial intelligence. What's missing is that we have yet to develop an algorithmic understanding of human behavior as it is, rather than as it should be. In other words, we need a theory of artificial stupidity, and in this talk, Professor Lo will motivate the need for this theory with several examples and propose some first steps in constructing it.
Andrew W. Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management, director of the MIT Laboratory for Financial Engineering, a principal investigator at the MIT Computer Science and Artificial Intelligence Laboratory, and an affiliated faculty member of the MIT Department of Electrical Engineering and Computer Science. He is also an external faculty member of the Santa Fe Institute and a research associate of the National Bureau of Economic Research.
He has published numerous articles in finance and economics journals, and has authored several books including Adaptive Markets: Financial Evolution at the Speed of Thought, The Econometrics of Financial Markets, A Non-Random Walk Down Wall Street, Hedge Funds: An Analytic Perspective, and The Evolution of Technical Analysis. He is currently co-editor of the Annual Review of Financial Economics and advisor to the Journal of Investment Management and the Journal of Portfolio Management.
Lo’s current research spans five areas: evolutionary models of investor behavior and adaptive markets, systemic risk and financial regulation, quantitative models of financial markets, financial applications of machine-learning techniques and secure multi-party computation, and healthcare finance. Recent projects include: deriving risk aversion, loss aversion, probability matching, and other behaviors as emergent properties of evolution in stochastic environments; constructing new measures of systemic risk and comparing them across time and systemic events; applying spectral analysis to investment strategies to decompose returns into fundamental frequencies; and developing new statistical tools for predicting clinical trial outcomes, incorporating patient preferences into the drug approval process, and accelerating biomedical innovation via novel financing structures.
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 received a B.A. in economics from Yale University in 1980 and an A.M. and Ph.D. in economics from Harvard University in 1984. From 1984 to 1988, he was an assistant and associate professor of finance at the University of Pennsylvania’s Wharton School. He has been at MIT since 1988.
Theoretically Speaking is a lecture series highlighting exciting advances in theoretical computer science for a broad general audience. Events are held at the David Brower Center in Downtown Berkeley, and are free and open to the public. No special background is assumed.
Seating is first come, first served. Light refreshments will be served before the lecture, at 5:30 p.m.