Clarendon Lectures in Finance: The Adaptive Markets Hypothesis · PDF fileClarendon Lectures...

Clarendon Lectures in Finance: The Adaptive Markets Hypothesis

© 2013 by Andrew W. Lo All Rights Reserved

Andrew W. Lo, MIT Lecture 2: Adaptive Markets in

Theory and Practice June 13, 2013

Clarendon


Bounded Rationality

Simon’s (1956) Notion of “Satisficing”: Heuristics, not optimization Develop mental models to simplify decisions Impact on AI, but not on economics How do we know what is “good enough”?

AMH ⇒ We Don’t! Our Heuristics Evolve Apply evolutionary principles to heuristics Use neuroscience to guide our modeling Apply to financial market dynamics

Slide 2 Lecture 2

Clarendon Bounded Rationality

Consider Getting Dressed: 5 Jackets, 10 Pants, 20 Ties, 10 Shirts, 10 Pairs of

Socks, 4 Pairs of Shoes, 5 Belts 2,000,000 Possible Outfits! Takes 1 Second To Evaluate Each Outfit How Long To Get Dressed? 23.1 Days!

How Do We Get Dressed So Quickly? ⇒ Trial-and-error coupled with selection, i.e., evolution

© 2013 by Andrew W. Lo

All Rights Reserved Lecture 2 Slide 3

Clarendon Bounded Rationality and Intelligence

What Is The Opposite of Intelligence? Stupidity Behavior that is detrimental to well being and survival

A Definition of Intelligent Behavior: Any behavior that confers reproductive advantage May seem vacuous but it has very specific implications


Slide 4 Lecture 2

Clarendon


Bounded Rationality and Intelligence

Recall: Action = 1 for a, 0 for b; assumed to be

independent of xa and xb

What If Some Individuals Can Predict xa and xb? (A1’’) Assume: Φ(xa,xb) is IID across individuals Φ(xa,xb) is IID across time; correlated

with x

Specifically: This captures the essence of intelligence

Slide 5 Lecture 2

I fi



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Clarendon

Growth-Optimal Behavior: Another source of probability matching



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Measure of Intelligence


The individuals with the highest ρ will dominate Now suppose that ρ is a function of state variables z Then let:

But ρ(z) need not be globally concave, continuous, etc. There may be many z* = arg Max ρ(z) Diversity of (f*,z*), implying

multiple types of intelligence Maximum predictive ability

defines bound on rationality


Lecture 2 Slide 8

Clarendon


Lecture 2 Slide 9


www.viscog.com

Clarendon Basic Neuroanatomy


Lecture 2 Slide 10

Brain Stem (“reptilian”) Amygdala

(“mammalian”)

Neocortex (“hominid”)

Emotional Stimulus Can Hinder The Neocortex Too flustered to speak, fight-or-flight response, road

rage ⇒ Kahneman’s “Thinking Fast and Slow”

Clarendon An Example of Conflict In The Brain

Say the colors of the following word: RED GREEN BLUE YELLOW ORANGE BLUE BROWN RED GREEN PURPLE PINK BLACK BLUE YELLOW GREEN


Lecture 2 Slide 11

Clarendon An Example of Conflict In The Brain

Say the colors of the following word: RED GREEN BLUE YELLOW ORANGE BLUE BROWN RED GREEN PURPLE PINK BLACK BLUE YELLOW GREEN


Lecture 2 Slide 12

Clarendon


Lecture 2 Slide 13

Narrative and the Left Brain Split-Brain Experiments: Roger Sperry and Michael Gazzaniga (late 1950s– ) Corpus callosum connects brain hemispheres Severed in patients with intractable epileptic seizures

Corpus callosum: Latin for “tough body” 250 million interconnections between the left and the right hemispheres of the brain

Clarendon


Lecture 2 Slide 14

Narrative and the Left Brain Split-Brain Experiments: Eyes are cross-wired to

opposite hemispheres Each hemisphere interprets

data independently, but subjects get no conscious knowledge from the left eye

Right hemisphere unable to describe what it sees

But the left hand (right hemisphere) can still point! Sperry (1968)

http://www.youtube.com/watch?v=ZMLzP1VCANo

Clarendon


Lecture 2 Slide 15

Narrative and the Left Brain

Clarendon

“Shovel used to clean chicken coop” “Chicken goes with the chicken foot”


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Gazzaniga (2000)

Right Brain Left Brain

Clarendon


Lecture 2 Slide 18

Narrative and the Left Brain Left Brain

Interpretation Linguistic Executive function

– Planning, hypothesizing

Semantic Fooled into probability

matching

Right Brain Observation Attentional Visuospatial processing

– Contours, shapes, faces

Episodic No probability matching

– Exception: probability matching for facial hair task (Miller and Valsangkar-Smyth, 2005)!

Rational expectations, Homo economicus

Clarendon Human Evolution


Lecture 2 Slide 19

Clarendon


Lecture 2 Slide 20

Human Evolution A Puzzle In The Fossil Record Anatomically modern humans 200,000 years ago Symbolically complex artifacts only 80,000 years ago Gaps in the record? But more complex over time

Earliest known artwork: Blombos Cave, South Africa. Ochre was scraped flat and carved into triangular designs. Dated 77 kya bp. Henshilwood (2002)

Clarendon


Lecture 2 Slide 21

Human Evolution A Puzzle In The Fossil Record Tattersall’s “symbolic revolution” Existing brain potential unlocked by cultural stimulus

– Intentionality: understanding complex motives – Language: communicating symbolic thought,

narrative Cognitive explosion!

Clarendon


Lecture 2 Slide 22

Human Evolution Why Is Symbolic Thought So Powerful? Rapid “fine-tuning” of abilities via natural selection Story-telling, narrative ⇒ prediction Hawkins’s memory/prediction model of intelligence Allows neural reward/punishment mechanisms to

operate on predictions, not just realized events – Yields regret and disappointment

Evolution At The Speed of Thought

Clarendon The Adaptive Markets Hypothesis Behavior is produced by multiple neural components,

and evolution shapes these neural components across time and circumstances

Evolution occurs at the speed of thought via narratives, and even faster via language and shared narratives

Rational (adaptive) behavior arises from proper balance of these components; irrational (maladaptive) behavior arises from improper balance

The environment and selection are the keys to behavior and market dynamics (innovation, competition, growth, decline, etc.)


Lecture 2 Slide 23

Clarendon Alpha Turns To Beta


Lecture 2 Slide 24

Example: Paulson & Co. (Wall Street Journal, January 5, 2009)

Clarendon

Other Examples of Alpha Turning To Beta

Value, growth, momentum, earnings surprise ABS, MBS, CDO, structured credit Equity market neutral Fixed-income arbitrage Merger arbitrage Trend-following The “carry” trade etc.

Wall Street Journal September 7, 2007

Alpha Turns To Beta


Slide 25 Lecture 2

Clarendon Alpha Turns To Beta


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α

Unique

α

α

Novel

α α α

α α α

…

Popular

α α

α

α

α α

α α α

α

α α

α α

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Common

Clarendon


Lecture 2 Slide 27

Conclusion

Symbolic thought and narrative are critical in distinguishing Homo sapiens from other species

Evolution at the speed of thought is hard to beat! But human intelligence is bounded in its rationality due

to evolutionary and physiological constraints The Adaptive Markets Hypothesis reconciles market

efficiency with human behavior – Frictionless model of efficiency is an abstraction – Approximation error varies according to the environment and

natural selection of behaviors among the population of individuals

Thank You!

Clarendon Further Reading Brennan, T. and A. Lo, 2011, “The Origin of Behavior”, Quarterly Journal of Finance 1, 55–108. Brennan, T. and A. Lo, 2012, “An Evolutionary Model of Bounded Rationality and Intelligence”, PLOS ONE 7:

e34569. doi:10.1371/journal.pone.0050310. Farmer, D. and A. Lo, 1999, “Frontiers of Finance: Evolution and Efficient Markets”, Proc. Nat. Acad. Sci. 96,

9991–9992. Hasanhodzic, J. and A. Lo, 2007, “Can Hedge-Fund Returns Be Replicated?: The Linear Case”, Journal of

Investment Management 5, 5–45. Lo, A., 1999, “The Three P’s of Total Risk Management”, Financial Analysts Journal 55, 13–26. Lo, A., 2001, “Risk Management for Hedge Funds: Introduction and Overview”, Financial Analysts Journal 57,

16–33. Lo, A., 2004, “The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective”, Journal of

Portfolio Management 30, 15–29. Lo, A., 2005, “Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis”, Journal

of Investment Consulting 7, 21–44. Lo, A., 2012, “ Adaptive Markets and the New World Order, Financial Analysts Journal 68, 18–29. Lo, A., 2012, “Fear, Greed, and Financial Crises: A Cognitive Neurosciences Perspective”, to appear in J.P. Fouque

and J. Langsam, eds., Handbook of Systemic Risk, Cambridge University Press. Lo, A. and C. MacKinlay, 1999, A Non-Random Walk Down Wall Street. Princeton, NJ: Princeton University Press.


Lecture 2 Slide 29

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