The Pursuit of Useless Information: Does this apply to Stock Picking?
Many in the investing world feel that, when assessing securities for purchase, the more information that can be assembled, the better off the investor. In this view, more review, due diligence, and information is always better, as this will lead to superior decision-making. This seems to make sense on its face, since a more complete picture of reality should facilitate decision making.
But is it true empirically?
In “On the Pursuit and Misuse of Useless Information,” by Bastardi and Shafir (a copy of which can be found here), the authors question the usefulness of missing incremental information and come to some surprising conclusions.
The authors write:
When making decisions under uncertainty, one needs to determine what information may prove instrumental and, therefore, perhaps may be worth paying or waiting for, and what information is unlikely to affect (and thus need not delay) the decision.
The trouble begins when decision makers must weight discrete pieces of information, which forces them to establish a preference hierarchy for that information. This is cognitively difficult since our preferences are often not well-formed, or even can be wholly abstract. When faced with the challenge of identifying a reliable signal within the confusing array of data points, decision makers will often look for additional information to help them make decisions. Often this additional information proves to be effectively useless, as it is irrelevant to the decision.
The authors conducted a study exploring this effect. A group of undergraduates were asked the following “simple version” question:
You are considering registering for a course in your major that has very interesting subject matter and will not be offered again before you graduate. While the course is reputed to be taught by an excellent professor, you have just discovered that he will be on leave, and that a less popular professor will be teaching the course.
a) Decide to register for the course? [82%]
b) Decide not to register for the course? [18%]
(the percentage of participants who chose each option appears in brackets)
Note that in this case, a full 82% of undergraduates chose to take the course, even though the less popular professor will be teaching it. For this group, the fact that the less popular professor was teaching was irrelevant to the decision. They simply wanted to take the course.
Next, a separate group of undergraduates were asked an “uncertain version” of the above question:
“You are considering registering for a course in your major that has very interesting subject matter and will not be offered again before you graduate. While the course is reputed to be taught by an excellent professor, you have just discovered that he may be on leave. It will not be known until tomorrow if the regular professor will teach the course or if a less popular professor will.
a) Decide to register for the course? [42%]
b) Decide not to register for the course? [2%]
c) Wait until tomorrow? [56%]
Note that in this case, instead of being known ahead of time, it was unknown whether the less popular professor was teaching. This information was unavailable. Here, a majority of students, 56%, wanted to wait and see whether the less popular professor was teaching before deciding.
Let’s pause a moment here. We already know, from the “simple version,” that approximately 82% of students will want to take the course regardless of whether the unpopular professor teaches it. As discussed, we know this large majority effectively doesn’t care about the teacher, and cares only about the course. Yet here, in the “uncertain version,” we see that a majority of students chose to wait and see. They apparently feel that knowing whether the unpopular teacher will teach the course is an important consideration.
If this is true, then upon resolution of this uncertainty, and based on the preferences revealed in the “simple version,” it seems reasonable to expect that a) if the popular teacher is in fact teaching, that some percentage higher than 82% will take the class, and b) if the less popular teacher is teaching, that we’ll see that same approximately 82%/18% split from the “simple version.” But that is not what happens.
As a follow-up to the above, “uncertain version,” this group of undergraduates were asked this question:
If you chose (c) in the question above, please answer the following:
“It is the next day, and you find out that the less popular professor will be teaching the course.
a) Decide to register for the course? [29%]
b) Decide not to register for the course? [27%]
The 56% who chose to wait now have made their choice: 29% registered, and 27% did not register. The new distribution of overall preferences under the “uncertain version” is therefore:
a) Decide to register for the course [42% + 29% = 71%]
b) Decide not to register for the course [2% + 27% = 29%]
This is a significantly different outcome than under the “simple version.” Whereas before, under the “simple version,” 82% chose to take the course, in the “uncertain version,” after the introduction of a piece of information that we know to be useless, only 71% chose to take the course.
As the authors eloquently summarize:
Having chosen to pursue noninstrumental information, people then proceeded to endow it with instrumental value.
There are a series of such experiments in the paper, each of which confirms this effect.
The Pursuit of Useless Information Applied to Stock Picking
Consider the diverse factors that investors seek to evaluate when picking stocks. These range from explicitly quantitative measure such as EBIT/EV, book value, and return on equity, to softer, more qualitative considerations such as industry outlook, quality of management team, legislative risk, or voting rights.
It’s hard to know how much weight to give to return on equity. Is it a highly relevant piece of information, or perhaps not so relevant in the grand scheme of things?
If we are unsure how to weight a piece of information, such as return on equity, and remain unsure on our overall view on the stock, we might be tempted to do some additional analysis. Perhaps it seems prudent to try to assess the management team? Surely this will provide additional guidance for making our choice. The authors might counsel you to think twice about this, since you may unwittingly take a piece of noninstrumental information, and because it is not directly available make it instrumental.
As Warren Buffett has put it:
When a management with a reputation for brilliance tackles a business with a reputation for bad economics, it is the reputation of the business that remains intact. – Warren Buffett
In short, a simple, available metric – a company’s return on equity – may well tell you much more than a protracted management quality review process that is difficult and costly to undertake.
Taking a step back, how important are, say, the voting rights associated with a stock that is very cheap? The answer? In many cases, cheapness will be far and away the most important consideration, while the voting rights could be entirely irrelevant. Yet because we are faced with uncertainty, we may incorporate voting rights or other irrelevant considerations into our review, since we have the illusion that these will enhance our ability to make a good judgment.
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Definitions of common statistics used in our analysis are available here (towards the bottom)