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.
