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Adaptive Markets
Book

Adaptive Markets

Financial Evolution at the Speed of Thought

Princeton UP, 2017 更多详情

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8

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  • Analytical
  • Overview
  • For Experts

Recommendation

Financial theory has long viewed investment through the lens of the efficient markets model, which posits that stock prices already reflect all known information and, therefore, no investor can beat the market. But this concept hasn’t always held up in real life. Professor Andrew Lo posits an “adaptive market hypothesis” to explain market anomalies in a new way. His is a rich narrative, interspersed with anecdotes and examples, but financial professionals looking for a rigorous framework for formulating predictive models will be disappointed. Nevertheless, he offers another perspective to investors who haven’t always agreed with conventional market thinking. 

Summary

Markets Are Adaptive, Not Necessarily Efficient

Accepted financial theory – based on seminal works such as Eugene Fama’s efficient markets hypothesis and Burton Malkiel’s book, A Random Walk Down Wall Street – holds that financial markets already incorporate all information; therefore, no investor can beat the market. This line of thought underpins the growth of index funds, which track market performance rather than relying on a fund manager’s stock-picking prowess. The efficient markets theory assumes that investors are rational, profit-maximizing and self-interested, meaning that institutions will protect the equity held by their shareholders, thereby making financial markets self-regulating. According to this model, the 2008 financial crisis should not have happened. Indeed, former Federal Reserve chair Alan Greenspan, a champion of “unfettered capitalism,” professed to being “in a state of shocked disbelief” as the crisis developed.

The efficient markets worldview came under fire in the crisis aftermath. But another way to look at markets is through the “...

About the Author

Andrew W. Lo is a professor at MIT’s Sloan School of Management and the director of MIT’s Laboratory for Financial Engineering.


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