How The Market “Gets It”: Why It’s So Hard to Beat the Market Presented by: Michael Mauboussin Chief U.S. Investment Strategist Credit Suisse First Boston.

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Presentation transcript:

How The Market “Gets It”: Why It’s So Hard to Beat the Market Presented by: Michael Mauboussin Chief U.S. Investment Strategist Credit Suisse First Boston

Page 2 How the Market Gets It u How does the stock market “understand” an economic model when so few investors use it? u How do opportunities arise?

Page 3 How the Market Gets It “Perspective is worth 80 IQ points.” Alan Kay

Page 4 u Time allocation u Decision making Why Do These Questions Matter?

Page 5 1.Lead steer (centralized) 2.Complex adaptive systems (decentralized) How Does the Market Understand?

Page 6 u Lead Steer “The relevant question to ask about the ‘assumptions’ of a theory is not whether they are descriptively ‘realistic,’ for they never are, but whether they are sufficiently good approximations for the purpose in hand.” Milton Friedman, Essays in Positive Economics Positive Economics

Page 7  The assumptions are not realistic  and predications fail just when you need them most u Suggests an “efficient market” u population of price changes is normal Lead Steer

Page 8 u “If the population of price changes is strictly normal, on average for any stock…an observation more than five standard deviations form the mean should be observed about once every 7,000 years. In fact such observations seem to occur about once every three to four years.” Eugene Fama, The Behavior of Stock Market Prices Lead Steer

Page 9 u “Much of the real world is controlled as much by the ‘tails’ of distributions as by means or averages: by the exceptional, not the mean; by the catastrophe, not the steady drip; by the very rich, not the ‘middle class’.” Philip Anderson, “Some Thoughts About Distribution in Economics” Lead Steer

Page 10 The dynamic interaction of a diverse group of agents (i.e., investors) creates a market that is efficient Complex Adaptive System

Page 11 u Example u Description u Characteristics Complex Adaptive System

Page 12 u 12 categories u Economic incentive u Not a poll, a prediction u Large sample size u n > 100 Academy Awards Complex Adaptive System  Example

Page 13 u Consensus got 10/12 correct u Best human got 9/12 correct u Average human got 5/12 correct The 2000 Result: Complex Adaptive System  Example

Page 14 Lots of agents with diverse decision rules lead to efficient results The Message: Complex Adaptive System  Example

Page 15 Dynamic Interaction/Decision Rules Market as a Global System Emergence Complex Adaptive System  Definition

Page 16 u No additivity u Can’t understand system through agents u Critical points u Small world work helpful u Evolving decision rules Complex Adaptive System  Characteristics

Page 17 u Markets are generally efficient when agent errors are independent-i.e. there is diversity of decision rules u The structure of double auction markets leads to “mostly” correct answers Complex Adaptive System  Takeaways

Page 18 u Analytical advantage u Diversity breakdown u Information advantage How Do Opportunities Arise?

Page 19 u Information advantage u Possible but tough u Grossman/Stiglitz: “The Impossibility of Informationally Efficient Markets” How Do Opportunities Arise?

Page 20 u Analytical advantage u Quantify expectations u Interpret with best available tools How Do Opportunities Arise?

Page 21 u Diversity breakdown u When agents all pursue the same strategy F Information cascades F Herding = when a large group of investors make the same choice independent of their own knowledge u Results in booms and crashes (i.e., fat tails) How Do Opportunities Arise?

Page 22 u The shift from centralized to decentralized mindset adds perspective (and hopefully IQ points) u Helps investors allocate time u The market is smart, but not because of “super smart” investors Conclusion