Avoiding Confirmation Bias

Sometimes an answer is easier to see if one steps away from the immediate problem, instead looking at an analogous situation.  This is a common teaching method, and one that we use frequently at "A Dash."

Background

Getting away from the immediate question helps to avoid what behavioral psychologists call the confirmation bias.  This tendency to see evidence as supporting one's preconceptions is very powerful.  We believe that even the leading market pundits, who are well aware of the phenomenon, fall victim to its power.

There is another important advantage:  Clarifying our objective.  So many prominent market commentaries claim not to make specific forecasts.  Frequently the authors criticize those who make specific and quantifiable predictions, pouncing on their errors.

We find this position quite remarkable.  If a market pundit is not trying to make some prediction, what is the value to readers?  Those claiming to have a "variant view" are making predictions.  The "variant view" idea involves even more complex predictions.  The author must make his own prediction, and then also prove that the market has not already discounted his widely-publicized idea.

The critical reader should ask whether these predictions are specific, quantifiable, and falsifiable.  If not, the argument is not useful for trading.

Bill Rempel's strongly-stated article on this subject deserves a wide readership:

There are some who would have it both ways. These people actively manage money! Perhaps for client accounts, where they buy or sell based on their technical models. Perhaps in mutual funds, where they decide whether to hedge with index puts, and how much hedging to put on. However, they try to have it both ways by saying “it’s not a prediction” or authoring articles about the fallacies of making predictions.

Please read Bill's entire analysis.  As we attempt to guide readers to the best sources on the Internet -- especially informing the explosion of new readers who have not joined us yet -- Bill's criteria should have a prominent place.

A Test of Confirmation Bias

Let us pretend that we live in Chicago -- something that means living and dying with "Da Bears."  [Giant fans and others can substitute their own team.]  We are interested in whether the Bears will win each game, each week.  We have many sources of information about Bears players, injuries, strategies, coaching, and most importantly, whether "good Rex" or "bad Rex" will be at the helm this week.  There are also many predictions from a community of experts.  Since we are fans, we have a lot of information and plenty of opinions.

This information can be our undoing.  We think that we know more and can parse information better than the real experts.  Everything that we see on TV, hear on talk radio, or read in the paper feeds our confirmation bias.  This is reflected not just in our interpretation of what we read, but also in what we choose to read.

An Alternative

Now let us suppose that we wished to predict the weekly result of the  Phoenix Cardinals, a team in which we have little interest.  Our  search for information  would be much more objective, including  a more open mind about expert predictions, sources, and data.

[It would be an interesting experiment for those like Scott Rothbort and Brett Steenbarger who have a ready audience, the appropriate intellectual interest, and the skill to conduct such tests.]

The Market Application

Let us imagine that a group of potential investors, abandoning the business of condo-flipping, decided to look at stocks with a long-term view.  These investors did not have any preconceived notions.  They had no market theory.  Their only question was whether to invest in stocks, and whether this was the right time.

In doing their research, they discovered that there was a community of experts.  These commentators had no allegiance to a particular viewpoint.  Their earnings were strictly based upon their results.  Poor performance, poor revenue.

The group of new investors might discover Mark Hulbert, who monitors the long-term performance of market advisory letters.  He identified the best and worst performers over the last ten years.  These groups of experts, unlike bloggers or pundits, cannot "fake it."  Revenues flow from performance.

The rookie investors discover the following from Hulbert (Barron's subscription required) -- a truly remarkable result:

The bottom line? None of these nine top timers are bearish. The average equity allocation among all nine is 92%. This is higher than where this average stood a year ago, as well as where it was in early May.

This 92% average is good news for the stock market in its own right, of course. But it's particularly bullish relative to the average forecast of the 10 stock-market timing newsletters with the very worst risk-adjusted performances over the last decade. The average recommended equity exposure among these worst performers right now is 0%.

In other words, the worst market timers are quite bearish right now, while the best timers are quite bullish. Rarely are we presented with a contrast this stark.

There are no guarantees. But to bet on a new bear market right now, you have to bet against the timers with the best long-term records and with those whose records have been awful.

Conclusion

There are many issues surrounding the prospects for stocks.  One needs to understand the worries, the probabilities, and how much current prices already reflect these concerns.

The intelligent investor reads a lot of information and has opinions on everything.  It is an easy question:

Do you think you are smarter and better informed than the consensus of all of the investment newsletter writers?

Or might  you be falling victim to the confirmation bias, spending a little too much time at your favorite bearish blog?

Comments

[Mike C]

I think the previous commenter hit the nail on the head (regarding time frame).

The extremely important question which I think ultimately is unanswerable is what time frame is relevant? Especially if the past 10 years have been radically different then the 30, 50, 80 years that preceded it (in terms of how stocks are valued). Do you base your forward-looking decisions on models that worked over the previous 10 years or models that worked over the past 50 years?

I sincerely do not know the answer, but anybody who doesn't realize they are in fact making that choice is potentially taking a risk they are completely ignoring or unaware of. I suspect 10 years from now we will know the answer.

One should certainly pay alot of attention to those who have solid long-term track records. However, I am inherently skeptical of "consensus" positions. Often, the correct and most profitable positions are those that are anti-consensus and contrarian. What was the consensus view in March 2000? What was the consensus view in October 2002? What was the consensus view on gold in 2001? Central banks who presumably would fit the bill of well-credentialed, "experts" in their field were net sellers of gold from 1999-2001.

Very often the consensus is most bullish at the top and most bearish at the bottom.

Interesting that the question was framed with "bearish" blog instead of "bearish/bullish" blog. I would think one could be equally as susceptible to confirmation bias regardless of whether one is a bull or bear. I don't think it would just be bears who are guilty of confirmation bias.

[Robert]

Another explanation could be that over the last 10 years, a certain method or set of indicators shared by the top 10 has performed well (when viewed from today's market level), relative to other possible methods and indicators. This would make those 10 tend to have a consensus going forward as well. However, it would not (necessarily) mean that their approach will work in the next year (or ten).

There are certainly plenty of behaviors that would have worked over the last 10 years that would not have worked in all 10-year periods, even periods overlapping the trailing 10 years.

An interesting test would be: were these same 10 the top performers when viewed from the bottom of the bear market?

I don't know whether the above is the explanation, but I don't see any evidence to rule it out.

So there's something to be said for looking at indicators or methods that have longer track records. Some of those, such as price to normalized earnings ratio, are currently bearish.

Second, it seems critical to ask what time horizon a given pundit is making a claim about. Price to normalized earnings (a proxy for fundamental value) statistically predicts long-term (7-10 year) returns well, but does not predict much about what will happen next month.

So if you are market-timing day-to-day, fundamental value is not helpful. If you are market-timing to try to limit downside risk over a multiyear market cycle, perhaps it is. Approaches based on fundamental value avoided both the tech bubble gains and tech bubble losses. Some people would consider that a positive and others wouldn't.

Finally, "risk-adjusted" has its limits. Usually this means adjusted for volatility. But risk does not have to be reflected in volatility; a classic example is "pennies in front of a steamroller" strategies such as writing out-of-the-money puts. A steadily-rising bull market getting ahead of fundamentals is not so different; on most days it goes up, but it has the potential to take a big dive. If someone is highly downside-risk averse, staying bearish much more often than necessary is not irrational, and it isn't wrong to say that risk is elevated when valuations are elevated.