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Adaptive Markets: Financial Dynamics and Human Behavior
Explore a groundbreaking approach to financial markets that bridges rationality and irrationality in this 13-week MIT course.
Explore a groundbreaking approach to financial markets that bridges rationality and irrationality in this 13-week MIT course.
Delve into a revolutionary perspective on financial markets with MIT's "Adaptive Markets" course. Led by finance professor Andrew W. Lo, this program introduces the Adaptive Markets Hypothesis, a framework that reconciles traditional market efficiency theory with behavioral economics. You'll explore how psychology, evolutionary biology, neuroscience, and artificial intelligence shape market dynamics. The course covers the origins of market efficiency, investor behavior foundations, and practical implications for hedge funds, crisis management, and financial regulation. Gain insights into the 2008 financial crisis, post-COVID-19 market navigation, and innovative approaches to global challenges. This interdisciplinary journey offers a fresh understanding of financial markets, blending rigorous theory with real-world applications.
Instructors:
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What you'll learn
Understand the limitations of traditional market efficiency theories
Explore the psychological and neuroscientific bases of investor behavior
Grasp the principles of the Adaptive Markets Hypothesis (AMH)
Analyze the role of hedge funds in financial ecosystems
Examine the dynamics of financial crises through the lens of adaptive markets
Evaluate the ethical implications of new financial theories
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 11 modules in this course
This course offers a groundbreaking approach to understanding financial markets, blending concepts from traditional finance theory with insights from behavioral economics, evolutionary biology, and neuroscience. Led by MIT finance professor Andrew W. Lo, the course introduces the Adaptive Markets Hypothesis (AMH), a new paradigm that reconciles the theory of market efficiency with the realities of human behavior. Students will explore the limitations of rational market theories, delve into the psychological and neuroscientific foundations of investor behavior, and examine how evolutionary principles apply to financial markets. The course covers practical applications of the AMH, including its relevance to hedge fund strategies, the dynamics of financial crises (with a focus on the 2008 meltdown), and navigating post-COVID-19 market challenges. Ethical implications of this new framework are also discussed, along with potential applications to broader societal issues such as cancer research, climate change, and energy crises. Through a combination of theoretical concepts and real-world case studies, students will gain a comprehensive understanding of how markets adapt and evolve, equipping them with valuable insights for both academic research and practical financial decision-making.
Introduction and Financial Orthodoxy
Module 1
Rejecting the Random Walk and Efficient Markets
Module 2
Behavioral Biases and Psychology
Module 3
The Neuroscience of Decision-Making
Module 4
Evolution and the Origin of Behavior
Module 5
The Adaptive Markets Hypothesis
Module 6
Hedge Funds: The Galapagos Islands of Finance
Module 7
Applications of Adaptive Markets
Module 8
The Financial Crisis
Module 9
Ethics and Adaptive Markets
Module 10
The Finance of the Future and the Future of Finance
Module 11
Fee Structure
Instructors
Pioneering Financial Economist and Adaptive Markets Theorist
Dr. Andrew W. Lo is the Charles E. and Susan T. Harris Professor at MIT's Sloan School of Management, where he directs the Laboratory for Financial Engineering. After earning his B.A. in economics from Yale University in 1980 and Ph.D. from Harvard University in 1984, he taught at Wharton before joining MIT in 1988. His research spans evolutionary approaches to investor behavior, systemic risk, financial regulation, and innovative funding models for biomedical research.
Financial Engineering Scholar and Risk Management Expert
Zied Ben Chaouch is a Ph.D. candidate in MIT's Electrical Engineering and Computer Science department, working under the supervision of Professor Andrew Lo at the Laboratory for Financial Engineering. After earning his undergraduate degree in Mathematics and Physics from McGill University in 2014, he completed his Master's at MIT studying opinion dynamics and network consensus under Professor John Tsitsiklis. His research spans risk management, asset pricing, portfolio theory, machine learning, and healthcare finance, with recent work focusing on empirical asset pricing and Bayesian decision analytics for healthcare applications. His teaching excellence was recognized with the Frederick C. Hennie II Teaching Award from MIT's EECS department for his contributions as a TA in probability courses and creating a math camp for incoming doctoral students. Beyond academia, he has published influential papers on COVID-19 vaccine allocation strategies, patient-centered clinical trials, and healthcare finance. His work combines sophisticated mathematical modeling with practical applications in finance and healthcare, reflecting his interdisciplinary background in physics, mathematics, and computer science.
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