- Daniel Kahneman and Amos Tversky introduced the concept of availability and representativeness as biases that could negatively impact decisions.
- Dr. Kahneman leveraged neuroscience to identify two types of mental processing that influence decision making: System 1 (fast thinking) and System 2 (slow or controlled thinking).
- The fields of economics, psychology and neuroscience have been bridged in the study of “neuroeconomics” to further identify how emotion impacts financial decisions.
Throughout our Behavioral Finance series, we have discussed the various heuristics, or “rules-of-thumb,” that are a part of the automatic thinking process of humans. The study of these mental shortcuts, which can adversely impact investor decisions, was pioneered by psychologists Daniel Kahneman and Amos Tversky (K&T). The 1974 publication of their study, “Judgment Under Uncertainty: Heuristics and Biases,” introduced the idea of considering availability and representativeness as rules-of-thumb used when assessing the probability of an uncertain event.
Several years later, K&T expanded upon their behavioral science research with the publication of “Prospect Theory: An Analysis of Decision Under Risk.” Prospect Theory offers an alternative to the “expected utility theory”1 of decision making under risk; it is based upon the values and costs that investors associate with gains and losses, rather than the likelihood of each outcome (as proposed by the expected utility theory). Prospect Theory also asserts that investors tend to assign value to gains and losses through rules-of-thumb that limit their ability to make reasonable decisions.2 It was Prospect Theory that paved the way for further study of investor-bias theories such as regret aversion, overconfidence and confirmation bias.
The Thinks We Can Think3
Many investors have probably made mistakes, not realizing errors until it was too late, as relatively few of us are behavioral scientists, financial analysts or unbiased thinkers. We may have then asked ourselves, “What was I thinking?” While the theories outlined in our Behavioral Finance series define the mental shortcuts that we may have relied upon to make a decision, we should consider how we were thinking in addition to what we were thinking.
In Thinking, Fast and Slow, Dr. Kahneman introduced the concept of decision-making “agents” in a two-system model of brain functioning based on automatic and controlled processes.4 System 1 is responsible for fast thinking such as impressions, intuitions and feelings. System 2 handles slow thinking; it takes the impulses sent by System 1 and converts impressions into beliefs, and impulses into actions.5 The automatic operation of System 1, which cannot be turned off at will, is what prompts us to make decisions (and sometimes errors) based upon rules-of-thumb. While System 2 further processes impulses provided by System 1, the biases generated by initial rules-of-thumb may not always be detected since System 2 may not be aware of the error.6 The only way to detect these biases may be through the conscious application of System 2. Essentially, the trick to avoiding mistakes is by knowing when we need to activate the more-controlled thinking of System 2.
Dr. Kahneman’s two-system model of brain functionality suggests that System 1 is typically activated first, with System 2 tapped to provide more-deliberate thinking. However, it is important to note that System 1 provides valuable information when making decisions. If we turn to neuroscience, the study of the brain and nervous system, we can highlight one of many compelling examples in which System 1 can be used to make deliberative decisions.
The automatic, rapid and subconscious system of the brain constantly seeks to automate tasks to preserve the limited capacity of controlled thinking.7 It is important to note that the automatic brain has incredible functionality that enables parallel thinking, such as multitasking and visual identification or pattern recognition.8
Consider a famous study in which chess players were asked to memorize configurations of chess pieces on a board. Researchers found that expert chess players could automatically memorize the positions of pieces on a board if the configuration was part of a plausible game of chess. Further, it was discovered that chess grandmasters were capable of identifying up to 10,000 board configurations from memory and develop instant responses.9 However, when the configurations deviated from the plausible, the experts were no better at memorizing patterns than novice players.
Subsequent research has suggested that pattern matching (automatic thinking), rather than weighing costs and benefits (controlled), is responsible for making decisions.10
The pattern-recognition study is one of many that scientists have performed over the past two decades in an attempt to further understand what drives decision making. In some studies, we can clearly see how the joining of psychology and economics underpinned breakthroughs in the fields of behavioral finance and economics.
As research began to proliferate in the early 2000s, helping to explain what drives our financial decision making processes, advances in behavioral economics started to overlap with neuroscience. The field of neuroeconomics brought together economists, psychologists and neurologists to research the formerly unmeasurable psychological processes and emotions that are activated when decisions are being made. In particular, scientists presented evidence that controlled thinking is not always responsible for decision making. While neuroeconomics is still a relatively young field, current advances in neuroscience might lead to the next generation of breakthroughs in understanding the financial mind.
More from the Behavioral Finance Series
1-2. Kahneman, D. and Tversky, A. “Prospect Theory: An Analysis of Decision under Risk” Econometrica. 1979. p. 263.
3. Dr Seuss, The Thinks We Can Think. Random House Publishers, @1975.
4-6. Kahneman, Daniel. Thinking, Fast and Slow. Penguin Books Limited, ©2011. pp. 13, 24, and 28.
7-8. Camerer, Douglas, Lowenstein, George and Prelec, Drazen. “Neuroeconomics: How Science Can Inform Economics.” Journal of Economic Literature Vol. XLIII (March 2005), pp. 21, 24.
9. Gobet, Ferhand and Herbert A. Simon. 1996. “Recall of Random and Distorted Chess Positions: Implications for the Theory of Expertise.” Memory and Cognition, 24(4): 493–503.
10. Leboeuf, Robyn Aimee. 2002. “Alternating Selves and Conflicting Choices: Identity Salience and Preference Inconsistency.” Dissertation Abstracts International, 63(2–B): p. 1088
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