Investor Psychology: Three Concepts from Behavioral Economics (2024)

1. Three questions

This essay originated in three questions, all emerging from the Efficient-Markets Hypothesis:

1. If markets are so efficient, why are there such high volumes of trading? Why is there such an incipient fear about short sellers?
2. If markets are so efficient, why are professional investment managers, say, hedge fund managers, paid so much?
3. If markets are so efficient, why is there so much speculation “pushing” prices to the “right” level?

(Obiter dictum: Anxiety about short sellers can be traced back to late nineteenth-century stock markets in America. There is abundant legislation putting boundaries on their speculative activities: imprisonment for six months, fines for $5,000. My own position is that expert short sellers are the “canary in the coal mine”: Vital for healthy capital markets, they point to what needs attention.)

2. The Efficient-Markets Hypothesis (EMH)

Maybe there was something in the air in 1965. In that year, Paul Samuelson, the first American to win the Nobel Prize in economics, argued, “By positing a rather general stochastic model of price change, I shall deduce a fairly sweeping theorem in which next-period’s price differences are shown to be uncorrelated with (if not completely independent of) previous period’s price differences.” That same year, University of Chicago economist and Nobel laureate Eugene Fama described the “efficient market” as one in which

[T]here are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value.

(The italics are mine).

From this passage, three characteristics of the investor stand out:

• possessing rational (as opposed to emotionally skewed) intelligence;
• profit-maximizing competitiveness, and;
• the faculty for (accurate) prediction.

But what if all three characteristics are fraught with cognitive biases, namely, mental distortions that lead us to making less-than-optimal decisions under conditions of risk or uncertainty? Behavioral economists call them “heuristics.” Think of them as mental shortcuts or rules-of-thumb.

A behavioral economist would argue the investor’s decisions are based on a two-step model:

1. Ex-ante beliefs about the (subjective) probabilities of risky events; and
2. Preferences about the decision weights to assign to these events.

This complex pas de deux of beliefs and preferences is a wholly subconscious “dance” that we are all engaged in. But unlike most of us, the investor is immersed daily in an environment of risk and uncertainty with high-stakes outcomes. His cognitive habitat is a permanent one, one that affects others, especially if he is investing on behalf of others.

I examine three concepts from behavioral economics that cast light on the investor’s psychology. Then I posit six more, my contribution to the research.

A quick clarification of terms: throughout this essay, I use the term “investor.” This describes any individual who invests with the intention of declaring a profit. This would include both professional investors (such as equity and futures traders) and investment managers who compose and manage portfolios of funds (hedge funds, mutual funds, private equity funds, etc.) on behalf of paying clients who are the underlying investors.

Seasoned investors will claim they have a robust stomach for volatility. Perhaps this is accurate. But insofar as they are human, they are all subject to these cognitive biases. As are we.

3. “Availability”

The investor estimates the “correct” intrinsic value of a security based on available information about that security. This estimation reflects, the EMH argues, both past prices and anticipated prices. Given the volume of information available, how does the investor know which information to choose?

The “availability heuristic” attempts to answer this question. The availability heuristic is the mind’s bias to use easily available, effortlessly recalled, top-of-the-mind information to explain phenomena and influence decisions. If an event is “available” to the memory, we will use it to predict the future or explain the present.

Priming and framing can artificially induce this bias, which makes the availability heuristic dangerous, cognitively speaking, to making rational investment decisions. Priming, or influencing a person by supplying highly relevant information often of an emotional nature, influences investors’ assessment of probabilities. Framing, our cognitive bias to make decisions based on how information is presented or “framed,” also impresses investors’ brains.

For instance, the availability heuristic shows up investors’ responses to negative financial news such as consumer sentiment news, negative stock price changes, analyst downgrades, and sweeping negative market movements.In other words, investors regularly change their probability assessments of risk in response to negative news that is immediately available to them. And consider there is a lot of available information, the relentless ambient sound of the financial press, both in print and on television.

But why is negative news considered more salient? To explain that, we have to turn to two of the seminal concepts in behavioral economics: Prospect theory and loss aversion (more on these in the next section, “Extrapolating Erroneously during Tail Events”). The short answer: Investors have different weighting functions for losses versus gains. When an outcome is deemed to be highly probable, investors will seek out risks when losses loom large and avoid risks when gains are likely. The reverse is true when an outcome has low probability: investors become risk seeking for gains and risk averse for losses.

How does the availability heuristic influence investors’ decision making? The most important factor is the unrelenting “availability” of recent market events as decision-making reference points. Investors are likely to overstate the importance — behavioral economists call this “salience” — of market phenomena with top-of-the-mind recall, recent investment outcomes, and newsworthy stock market performance indices as opposed to those on the far horizon.

When you’re watching CNBC throughout the day (and, let’s be honest, even on weekends), there is a highly selective stream of information that is making itself available to your brain. This available information impacts the brain and impresses step two in the two-step model above: subjective preferences about probabilities. The media primes and frames investors’ decision making by making negative information more available and seemingly more salient.

4. Extrapolating erroneously during “tail events”

Well-behaved stock markets do not make history. When asset-price distributions are fat tailed with tight peaks and high kurtosis, when Black Swans appear suddenly with no warning in sight, the investor will extrapolate erroneously.

But first, let us return to a term we encountered in Econ. 101: Expected Utility Theory. Expected Utility is the utility, or payoff, of an outcome multiplied by the probability of its occurrence. During tail events, investors’ probability weighting function becomes distorted. Investors will consider high-impact risky events carrying the possibility of huge losses more probable, not less. These probability weights become decision weights, with investors overweighting the probabilities of tail events.

As an illustration, consider the demand for both lotteries and insurance. On the one hand, people prefer a 0.001 per cent chance of winning $5,000, namely, a $5 win, over a sure chance of receiving $5. On the other hand, people prefer to pay out $5 as insurance against a 0.001 percent possibility of losing $5,000. While these attitudes towards risk seem contradictory, myopic, and illogical, there is overwhelming evidence that, yes, people view loss and gain very differently. When faced by the prospect of extremely unlikely outcomes, in this case, the prospect of gaining versus losing $5,000, the probability weights assigned by investors veers wildly away from rational behavior prescribed by the Expected Utility Theory.

Remember the two-step model I referenced earlier? Beliefs followed by preferences. Investors’ probability assessment of “tail events,” or, how likely they consider the likelihood of a rare, high-impact event, increases allocation to risky assets. Yes, tail events increase allocation to risk. This finding is entirely consonant with prospect theory which states that people overestimate the potential value of losses and underestimate that of gains.

5. Risk as feelings

Feelings influence decisions. The “risk-as-feelings” hypothesis states that risky decisions insert emotions into the decision-making process in place well-deliberated thinking. When stress, worry, dread, fear, and anxiety are involved—namely, a typical weekday for professional investors—the brain makes decisions based on emotions, or more technically, "affect." In other words, how investors feel about risk is just as influential as what they know about risk.

One of the main consequences of interpreting risk as feelings is mood misattribution. If feelings influence our “read” on risk, it follows that moods can be misattributed as information: “The mood-as-information hypothesis argues that our moods inform our decisions; in effect, when we are making a decision we ask ourselves ‘How do I feel about it?’ and this guides our eventual decision.” Equally, if our moods are a weathervane, fluctuating regularly, then these moods can lead to misattributing risk where no risk exists. Consider the inexorable forces on the investors’ moods: analyst upgrades and downgrades, large movements in the stock markets, changes in the political ecosystem.

6. Six new ideas.

These are my contribution to the research. At any rate, they are axiomatic truths about the human mind.

1. Memory: The investor will only transmit information considered most important, most salient, and most relevant for future learning. Investor wisdom is not a random choice. One reason for this is the brain’s capacity to process only a limited number of items at a time.

2. The Movie Reel: The investor will explain stock market behavior as a movie: a narrative that moves through time, chronologically and logically, with each “event” flowing organically from the previous one. If there is stock market volatility, the investor will restructure the narrative to “make it all fit.” Related to the logical fallacy post hoc, ergo propter hoc (“after this, therefore because of this”).

3. The Analogy Principle: The brain loves to think in terms of analogy (“X is just like Y”). If stock market phenomena resemble each other, they must be related. If the connection is tenuous, a relationship will be invented to provide an analogy.

4. Intentionality: If something happens, it must have been willed into happening. The investor will assume a deliberate intentionality can make things happen by sheer force of will. The flip side: if something happened, it must have been willed into happening.

5. Affinity. Related to kinship, consanguinity, and blood ties. Like effects mean like causes. The investor will assume two events that look alike have causes that also look alike.

6. Five Little Pigs: My ode to Hercule Poirot. The camera angle on a past event offers perspectives that can be recreated without revisiting past event. The investor will assume participants in a past financial phenomenon can offer meaningful and valid perspectives on a current financial phenomenon. Hence the need to anoint financial sages, stock market oracles, and investment philosophers who lived through a stock market event in the distant past. “They were there. They know what it was like.”

7. Practical applications

There is a reason why many successful investors are drawn to transcendental meditation. Detaching from the feverish churn of stress, anxiety, and worry, and calming the brain waves into a self-willed state of relaxed activity makes for more conscious decision making, with greater executive control. A neuroscientist would say that if it is good for the prefrontal cortex, it is good for decision making.

Given that the mind is the last frontier, what can investors learn from behavioral economics?

1. The way investors feel about risk is perhaps more influential than what they know about risk.
2. Judgments about risk seldom occur in emotionally neutral contexts.
3. Emotional reactions to risk often diverge from cognitive evaluations of the same risk. In other words, affect and cognition may tell entirely different stories even to the seasoned investor.
4. The brain loves to think in terms of analogy. See Section 6 above (“The Analogy Principle”) If an investment situation resembles another investment situation, investors will find a series of analogies to justify replicating their decision making.
5. Experienced investors may think they are following Expected Utility Theory, but their brains are probably following Prospect Theory: risk averse for gains and risk seeking for losses.
6. When investors are convinced they have stumbled upon the next Apple, Google, or Snapchat, they are overestimating the probability of a “tail event.”
7. Watching CNBC all day long? Yes, that is influencing your decision making. Negative consumer sentiment announcements, analyst downgrades, large negative movements in stock and futures markets—negative news hurts more than positive news.

Want to read more?

Availability Heuristic: The definitive research paper is that of psychologists Amos Tversky and Daniel Kahneman, both jointly winning the Nobel Prize in 2002, Tversky posthumously. Their 1973 publication on “availability”: https://msu.edu/~ema/803/Ch11-JDM/2/TverskyKahneman73.pdf

The two-step model of decision making to which I refer is the work of Craig Fox and Amos Tversky, specifically their 1998 research paper in Management Science: “A Belief-Based Account of Decision under Uncertainty”

“Priming” and “Framing”: Both concepts have a wealth of research and practical applications in multiple fields. But those interested in the behavioral and brain sciences might start with Amos Tversky and Daniel Kahneman’s 1981 piece in Science: “The Framing of Decisions and the Psychology of Choice.” Kahneman talks about “priming” in his Nobel Prize lecture published here: http://www.cs.unibo.it/~ruffino/Letture%20TDPC/Kahneman.%20am.ec.rev.,%205,%202003.pdf

Prospect Theory: This was the research paper that started it all. Tversky and Kahneman made the stunning (at the time) claim that people seek risk when losses loom and avoid risk when gains seem imminent. Read their 1979 work in full here: https://www.princeton.edu/~kahneman/docs/Publications/prospect_theory.pdf In 1992, they updated the theory: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.320.8769&rep=rep1&type=pdf

Extrapolation, bubbles, behavioral finance: Nicholas Barberis at Yale writes extensively on these topics. His work on tail events is particularly germane to those interested in stock market behavior and human psychology: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2231781

Analyst recommendations, upgrades, etc. influence decision making. My source was “Stock salience and the asymmetric market effect of consumer sentiment news.” Read in full here: http://www.sciencedirect.com/science/article/pii/S0378426612001999

Loss Aversion: This psychological concept was the original research contribution of Amos Tversky and Daniel Kahneman in their paper on Prospect Theory (see above). This Science article explains loss aversion very well: https://www.scientificamerican.com/article/what-is-loss-aversion/

Risk as feelings: This is the original and seminal work of a collaboration of behavioral economists: George Loewenstein, Elke Weber, Christopher Hsee, and Ned Welch. Read their paper here: http://www.cmu.edu/dietrich/sds/docs/loewenstein/RiskAsFeelings.pdf

Disclaimer: The opinions expressed here are mine and do not represent those of the institutions I work for.

Contact me at https://www.linkedin.com/in/devjaniroy

Formerly at Harvard Kennedy School, Center for Business and Government. Now at Texas Tech University Health Sciences Center. Read my other essays here: http://www.linkedin.com/today/author/devjaniroy?trk=pprof-feed