The Adaptive Markets Hypothesis

• 1: Introduction and Roadmap


• 2: The Origin of Behaviour


• 3: Mutation


• 4: Group Selection


• 5: Probability Matching


• 6: Risk Aversion


• 7: Cooperation


• 8: Bounded Rationality and Intelligence


• 9: Learning to be Bayesian


• 10: The Madness of Mobs


• 11: Fear, Greed, and Financial Crises


• 12: The Psychophysiology of Trading


• 13: What Makes a Good Day Trader?


• 14: A Computational View of Market Efficiency


• 15: Maximizing Relative vs. Absolute Wealth


• 16: Hedge Funds: The Galápagos Islands of Finance


• 17: What Happened to the Quants in August 2007?


• 18: Co-Evolution of Financial Markets and Technology


• 19: The Role of Culture in Finance


• 20: Regulation and Adaptive Markets

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. 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.

Ruixun Zhang is an assistant professor and Boya Young Fellow in the School of Mathematical Sciences at Peking University (PKU). He is also affiliated with the PKU Laboratory for Mathematical Economics and Quantitative Finance, the PKU Center for Statistical Science, and the PKU National Engineering Laboratory for Big Data Analysis and Applications. Prior to joining PKU, he worked at several places including Google and Goldman Sachs. Zhang received Ph.D. in applied mathematics from MIT in 2015, and B.S. in mathematics and applied mathematics and B.A. in economics from Peking University in 2011. His research interests include evolutionary models of financial behavior, sustainable investing, FinTech, and applications of machine learning.