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Animal Spirits Neuroscience

October 20, 2011 • Posted in Animal Spirits

Is science making progress in deconstructing the animal spirits at play in financial markets? In the October 2011 draft of his chapter entitled “Fear, Greed, and Financial Crises: A Cognitive Neurosciences Perspective”, Andrew Lo explores the neuroscientific underpinnings of those human behaviors most relevant to financial system risk. Citing a range of uncontrolled (opportunistic) and controlled experiments on brain operations, he finds that:

  • Financial gain activates the same reward circuitry as cocaine. Risk-taking activities resulting in a series of lucky gains may induce a potentially destructive positive feedback loop.
  • Financial loss appears to activate the same fight-or-flight circuitry as a physical attack, sidestepping higher brain functions (“rationality”) in favor of emotional processing and elevating heart rate, blood pressure and alertness. Once triggered, this circuit overrides most other decision-making components and is very difficult to interrupt.
  • Despite its adverse reputation, moderate emotional processing appears essential to making sound risk-reward trade-offs. Both too much and too little emotion can trigger irrational behavior.
  • Risk-seeking (risk-averse ) investors process potential monetary gain (loss) along the same circuitry involved in use of cocaine (contemplation of disgusting things).
  • Economic preferences often involve complicated interactions among multiple brain components and therefore may not be stable over time.
  • There are apparently inherent limits to the level of “hall-of-mirrors” processing (what others are thinking) involved in financial arbitrage strategies.

In summary, evidence supports a belief that human processing of financial situations employs brain circuitry evolved in response to a largely non-financial environment. While associated responses can be extreme, moderate emotional engagement appears to support, rather than undermine, rational evaluation.

Cautions regarding findings include:

  • Due to the generally small scale of brain components (and limitations on invasiveness), the tools of neuroscience are imprecise.
  • Complexity tends to confound inference.
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