Its a statistical phenomenon and not a social psychological effect
In 1906 an English country fair was holding a contest to guess the dressed weight of an ox. Roughly 800 people guessed the weight. Some guessed very high and some guessed very low. Sir Francis Galton, a brilliant English statistician (amongst other things) was there. Galton got his hands on all the answers and averaged them. Remarkably the average was very close to the real weight.
What Galton had stumbled on was the statistical phenomenon known as ‘decorrelation of error’. When a large enough sample of people guess at something like the number of marbles in a jar, averaging shaves off the high and low guesses leaving an estimate very close to the actual number. Put another way, with a sufficiently large sample, the errors made both high and low tend to average out towards zero.
This statistical effect was at the heart of a 2004 book by James Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations.
Many have come to think that the stock market is an example of ‘collective wisdom’ and that this explains stock market efficiency. Today, it’s popularly called the Wisdom of the Crowd. Let’s look at that idea.
As Daniel Kahneman, a behavioral psychologist and Nobel laureate, points out, “…the magic of error reductions works well only when the observations are independent and their errors uncorrelated. If the observers share a bias, the aggregation of judgment s will not reduce it. Allowing the observers to influence each other effectively reduces the size of the sample, and with it the precision of the group estimate.” Kahneman, Thinking Fast and Slow, 2011.
We can do a thought experiment. Imagine a jar full of marbles. Rather than having the subjects of the test write their guesses down secretly on a piece of paper, we have the first subject write their guess on a blackboard for all to see. The second subject is then asked to make a guess and write it down on the blackboard beside the first. Then the thirds subject make their guess and writes it on the board. The observations are not independent.
In a paper titled: How social influence can undermine the wisdom of crowd effect, by Jan Lorenza, Heiko Rauhutb, Frank Schweitzera , and Dirk Helbingb, the authors write: “…we demonstrate by experimental evidence that even mild social influence can undermine the wisdom of crowd effect in simple estimation tasks. In the experiment, subjects could reconsider their response to factual questions after having received average or full information of the responses of other subjects.”
I am not a psychologist, but let me explain as best I can what is at work here: The first guess might act as an ‘anchor’ for the second and subsequent guesses. An information cascade will likely occur. Social proofing may come into play. Groupthink may set in. We may be affected by herding behavior. What on earth are all these things? Together they may be thought of as social influence.
I’ll explain briefly, but you can Google them all.
As to Anchoring, Kahneman writes: “This is a very common effect. It occurs when people consider a particular value for an unknown quantity before estimating that quantity. What happens is one of the most reliable and robust results of experimental psychology: the estimates stay close to the number that people considered – hence the image of an anchor.” Kahneman adds: “Many psychological phenomena can be demonstrated experimentally, but few can actually be measured. The effect of anchors is an exception. Anchoring can be measured, and it is an impressively large effect.” (Kahneman, Thinking Fast and Slow, 2011)p.123. The subjects in our marble thought experiment will be influenced by the anchor of the previous estimate or estimates. In our investing, when we consider the intrinsic value of a stock, the market price acts as a prime and as an anchor.
Social proofing –
Another psychological bias is at work: Social proof is the influence that the actions and attitudes of the people around us (either in real life or online) have on our own behavior. The “proof” element is the idea that if other people are doing it (or saying it), it must be correct. Wikipedia
Psychologists’ conclusions are of interest to investors. Robert Shiller, a behavioral economist and Nobel laureate, reports on experiments by Morton Deutsch and Harold Gerard which examined the question whether crowd behavior could be explained by social pressure within the group or the fear on the part of one member of the group of being seen as foolish or different. The explanation they came up with is that an individual in a group tends to accept the views of the rest of the group because they simply think the others can’t be wrong The conclusion as described by Shiller is that: “The experiments demonstrate that people are ready to believe the majority view or to believe authorities even when they plainly contradict matter-of-fact judgment. And their behavior is in fact largely rational and intelligent. Most people have had many prior experiences of making errors when they contradicted the judgments of a larger group or of an authority figure, and they have learned from these experiences.” It is to be noted that Shiller is here referring to reliance on views considered to be authoritative or having expertise. This would be in contrast to reliance on an authority figure, i.e. a person in authority. Shiller concludes: “it is not at all surprising that many people are accepting of the perceived authority of others on such matters as stock market valuations.” (Shiller, Irrational Exuberance. 2005 Second Edition)p.159.
“An Information cascade or informational cascade is a phenomenon described in behavioral economics and network theory in which a number of people make the same decision in a sequential fashion. It is similar to, but distinct from herd behavior.
An information cascade is generally accepted as a two-step process. For a cascade to begin an individual must encounter a scenario with a decision, typically a binary one. Second, outside factors can influence this decision (typically, through the observation of actions and their outcomes of other individuals in similar scenarios).” Wikipedia:
“Herd behavior is the behavior of individuals in a group acting collectively without centralized direction….everyday decision-making, judgement and opinion-forming, are all forms of human based herd behavior. Wikipedia
This “occurs within a group of people in which the desire for harmony or conformity in the group results in an irrational or dysfunctional decision-making outcome. Cohesiveness, or the desire for cohesiveness, in a group may produce a tendency among its members to agree at all costs. This causes the group to minimize conflict and reach a consensus decision. Wikipedia
All of these phenomena are from behavioral psychology, not statistics. The paper by Lorenza et al makes clear: “The wisdom of crowd effect is a statistical phenomenon and not a social psychological effect, because it is based on a mathematical aggregation of individual estimates.”
The wisdom of crowds seems to work best in simple estimating tasks like guessing an ox’s weight or the number of marbles or coins in a jar so long as the estimates are completely independent. It also seems to work well with questions about geography or general world knowledge. These are situations where averages of independent guesses or estimates can ‘decorrelate’ errors.
There are other types of cases that might better be thought of as a summing of human knowledge. For example, there have been well documented cases where participants with access to a group’s knowledge are able to supplement and build on their own knowledge by reference to the knowledge of other group members. These may be thought of as useful collectives of human knowledge such as we can access through the internet. Wikipedia is an example.
Which brings me to earnings estimates, price targets, value estimates and stock prices. Earnings estimates are put out by individual analysts. Every analyst is aware of the estimates of other analysts, the high estimate, the low estimate and the ‘consensus’ estimate. Similarly, analysts are aware of other analysts’ price targets and value estimates. The argument would have to be that, like estimating the weight of the ox, 10 or 20 analysts are estimating earnings and decorrelation of error takes place with their consensus. The problem is that the estimates are not independent and are susceptible to social influence. The case of stock market prices is the most tantalizing. Investors might be thought of like visitors to the fair and closing prices would be average of high and low estimates of value, thus producing prices close to fair value. Of course, all of these estimates, targets and prices are effectively written down on a big blackboard for all to see. This also is a perfect case for social influence. And we know from the Lorenza study that “even mild social influence can undermine the wisdom of crowd effect.” Stock prices can surely act as anchors. They can cause social proofing and an information cascade. Finally, they can lead to groupthink, herding and what has been called the Madness of Crowds, a phenomenon first described by Charles MacKay in his well-known book, Extraordinary Popular Delusions and the Madness of Crowds, published in 1841.
The reality of the Wisdom of Crowds is that in an investment context the behavioral tail can wag the statistical dog.
Readers wishing to dig deeper into the impact crowds and herding have on our investing behavior can take a look in the Motherlode at Chapter 19. Our Urge to Do what Everyone Else is Doing
One of the features of the Motherlode is the gap-to-edge rules. An example for Chapter 19 is linked below.
This Chapter continues with these Sections:
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