The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics
The Adaptive Markets Hypothesis (AMH) presents a formal and systematic exposition of a new narrative about financial markets that reconciles rational investor behaviour with periods of temporary financial insanity. In this narrative, intelligent but fallible investors learn from and adapt to randomly shifting environments. Financial markets may not always be efficient, but they are highly competitive, innovative, and adaptive, varying in their degree of efficiency as investor populations and the financial landscape change over time.

Andrew Lo and Ruixun Zhang develop the mathematical foundations of the AMH—a simple yet surprisingly powerful set of evolutionary models of behaviour—and then apply these foundations to show how the most fundamental economic behaviours that we take for granted can arise solely through natural selection. Drawing on recent advances in cognitive neuroscience and artificial intelligence, the book also explores how our brain affects economic and financial decision making.

The AMH can be applied in many contexts, ranging from designing trading strategies, to managing risk and understanding financial crises, to formulating macroprudential policies to promote financial stability. This volume is a must read for anyone who has ever been puzzled and concerned by the behaviour of financial markets and the implications for their personal wealth, and seeks to learn how best to respond to such behaviour.
1142806064
The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics
The Adaptive Markets Hypothesis (AMH) presents a formal and systematic exposition of a new narrative about financial markets that reconciles rational investor behaviour with periods of temporary financial insanity. In this narrative, intelligent but fallible investors learn from and adapt to randomly shifting environments. Financial markets may not always be efficient, but they are highly competitive, innovative, and adaptive, varying in their degree of efficiency as investor populations and the financial landscape change over time.

Andrew Lo and Ruixun Zhang develop the mathematical foundations of the AMH—a simple yet surprisingly powerful set of evolutionary models of behaviour—and then apply these foundations to show how the most fundamental economic behaviours that we take for granted can arise solely through natural selection. Drawing on recent advances in cognitive neuroscience and artificial intelligence, the book also explores how our brain affects economic and financial decision making.

The AMH can be applied in many contexts, ranging from designing trading strategies, to managing risk and understanding financial crises, to formulating macroprudential policies to promote financial stability. This volume is a must read for anyone who has ever been puzzled and concerned by the behaviour of financial markets and the implications for their personal wealth, and seeks to learn how best to respond to such behaviour.
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The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics

The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics

The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics

The Adaptive Markets Hypothesis: An Evolutionary Approach to Understanding Financial System Dynamics

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Overview

The Adaptive Markets Hypothesis (AMH) presents a formal and systematic exposition of a new narrative about financial markets that reconciles rational investor behaviour with periods of temporary financial insanity. In this narrative, intelligent but fallible investors learn from and adapt to randomly shifting environments. Financial markets may not always be efficient, but they are highly competitive, innovative, and adaptive, varying in their degree of efficiency as investor populations and the financial landscape change over time.

Andrew Lo and Ruixun Zhang develop the mathematical foundations of the AMH—a simple yet surprisingly powerful set of evolutionary models of behaviour—and then apply these foundations to show how the most fundamental economic behaviours that we take for granted can arise solely through natural selection. Drawing on recent advances in cognitive neuroscience and artificial intelligence, the book also explores how our brain affects economic and financial decision making.

The AMH can be applied in many contexts, ranging from designing trading strategies, to managing risk and understanding financial crises, to formulating macroprudential policies to promote financial stability. This volume is a must read for anyone who has ever been puzzled and concerned by the behaviour of financial markets and the implications for their personal wealth, and seeks to learn how best to respond to such behaviour.

Product Details

ISBN-13: 9780199681143
Publisher: Oxford University Press
Publication date: 05/22/2024
Series: Clarendon Lectures in Finance
Pages: 800
Product dimensions: 9.50(w) x 6.60(h) x 1.60(d)

About the Author

Andrew W. Lo, Charles E. and Susan T. Harris Professor, MIT Sloan School of Management,Ruixun Zhang, Assistant Professor and Boya Young Fellow,, Peking University

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.

Table of Contents

1. Introduction and Roadmap2. The Origin of Behaviour3. Mutation4. Group Selection5. Probability Matching6. Risk Aversion7. Cooperation8. Bounded Rationality and Intelligence9. Learning to be Bayesian10. The Madness of Mobs11. Fear, Greed, and Financial Crises12. The Psychophysiology of Trading13. What Makes a Good Day Trader? 14. A Computational View of Market Efficiency15. Maximizing Relative vs. Absolute Wealth16. Hedge Funds: The Galápagos Islands of Finance17. What Happened to the Quants in August 2007? 18. Co-Evolution of Financial Markets and Technology19. The Role of Culture in Finance20. Regulation and Adaptive Markets
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