Technological advances have enhanced the speed of the dissemination of firm-specific information, and broadened its distribution. In this new, post-internet paradigm, after also considering the maturity (and size) of the investment management industry, we propose there is very little difference between large and small-capitalization equities in terms of relevant information available to the marginal investor. Consequently, we suggest that the notion that the equity prices of smaller capitalisation companies are somehow less efficiently priced than their larger brethren may potentially be stale.
We are saying nothing here about the small-cap premium, or the tendency for small caps to outperform large caps in some horizons. A current working paper by the team at AQR does a much better job empirically dispelling some of these myths than we ever could. We are simply saying that the notion that small-caps are potentially less efficiently priced than large-caps may be outdated.
Furthermore, we consider that the efficiency in the pricing of some specific, individual securities – in rare cases – may be affected by institutional constraints and behavioural biases that prevent a rational incorporation (or indeed, digestion) of fundamental, public information specific to that company. As such, we wonder if a strategy that seeks to identify those biases – in conjunction with incorporation of accurate, unbiased fundamental analysis – may be one way, if not the only way, for stock-pickers to generate alpha.
This, in turn, leads to a possible counterintuitive conclusion that alpha opportunities may not degrade as one moves up the market capitalization spectrum; and opens up the possibility than in some exceptional cases, mid, large and even mega-caps may offer idiosyncratic opportunities, and equally happy a hunting ground as their small-cap brethren.
The notion that small-caps are more ignored or less well-covered than large-caps is hard to disagree with, not just anecdotally, but empirically. This perception typically leads the active investment community to a conclusion that small-caps are more informationally inefficient, and thereby more suitable for the extraction of alpha. This is a common view, and it is often promoted by many fundamental stock-pickers. Essentially, they imply that an informational advantage can be gained by focusing on less-covered, smaller capitalization stocks, and that these opportunities are a primary source of alpha.
We’ve observed something different. Firstly, it appears to us that it is at least possible that larger (and consequently more well-followed) companies may potentially be more susceptible to the behavioural biases of the consensus investor. Furthermore, it should not be controversial to claim that the more well-followed a company is, the more likely that the consensus view can be identified for that particular security. Thus, if the biases are potentially more likely and identifiable as companies become larger and more well-followed, then could it be that larger-cap stocks could at least potentially offer a more fertile ground for identifying idiosyncratic, inefficient, investment opportunities.
There are a host of behavioural biases that people are learning more and more about as time progresses. Today, even the most ardent efficient market theorist would probably agree that these biases affect each of us as individuals, but the bigger question is if investors in the aggregate are also affected by these biases.
Some Support from the “Grandfather” of Behavioural Finance
One of the people who first wrote about the potential emotional biases affecting investors’ appetites for shares (and affecting share prices) was not Richard Thaler or Bob Shiller or even Daniel Kahneman; but instead was the father of value investing, Benjamin Graham. These excerpts from Security Analysis (which Graham co-authored with David Dodd in 1934) are enlightening:
“At times some specific development greatly strengthens the position of a (company), but the (stock) price is slow to reflect this improvement, and thus a bargain situation is created.”
“Undervaluations caused by neglect or prejudice may persist for an inconveniently long time, and the same applies to inflated prices caused by overenthusiasm or artificial stimulants.”
“…the market is a voting machine, whereon countless individuals register choices which are the product partly of reason and partly of emotion.”
“Evidently, the processes by which the securities market arrives at its appraisals are frequently illogical and erroneous. These processes are not automatic or mechanical, but psychological, for they go on in the minds of people who buy or sell.”
“The mistakes of the market are the mistakes of groups or masses of individuals. Most of them can be traced to one or more of three basic causes: exaggeration, oversimplification, or neglect.”
In other words, the notions we are considering in our analysis today are not outlandish; or at least they wouldn’t be outlandish to one of the best investors of all time.
Imagine there is a small-cap company listed in London, Frankfurt or New York. It is not covered by any sell-side analysts, and its holders consist strictly of systematically active (aka smart beta) quant funds or purely passive index investors – neither of whom cares terribly in which business this small-cap name is engaged. It isn’t difficult for any of us to envision that this company might be inefficiently priced. Now imagine that only one buy-side fundamental investor (and no sell-side analyst) reads through the company’s quarterly report, dials into the conference call, and meets with the CFO during the follow up road-show. Is it possible that this one buy-side investor has an informational edge? Sure, it is possible. What if he runs a $10 billion mutual fund and buys 10% of the company? Is it still mispriced? Maybe. What if two buy-siders do the work? Three? What if a sell-side analyst also publishes a research report? What if two publish?
In other words, how many buy-side and sell-side analysts need to do the work before information is being assimilated by the consensus, marginal, investor? Upton Sinclair once wrote “it is difficult to get a man to understand something, when his salary depends upon his not understanding it.” And it is true, most investors and analysts don’t want to hear the following, but it is at least possible that it doesn’t take many investors at all (or much capital) to fully assimilate information into a stock price. Furthermore, if our suggestion is true, then there are no informational edges in the world of stock-picking. Of course there can be rare cases, but they would usually be the result of cheating with private, inside information.
So, if information is public, but the potential for generating alpha still exists (granted, a big if), then it must be more likely achieved by a process which gathers public information, eliminates the noise, accurately models future fundamentals without bias, and seeks to identify a mismatch between consensus expectations for those very fundamentals. Within that process, the identification of Mr Market’s investment thesis is the most critical. Intuitively, does it not make sense that it should be easier to identify this consensus thesis when a company is well-followed than when it isn’t? And in terms of decision-making biases, isn’t it more likely that they occur in a herd of 30 analysts than in a herd of one or two?
But Can a Stock-Picker Really Generate Alpha, and is it Luck or Skill When it Happens?
In Thinking Fast and Slow, Daniel Kahneman wrote of trips he made with Richard Thaler to visit (and evaluate) different investment firms. Initially, he was baffled by the industry, and his view has evolved to this:
“…my questions about the stock market have hardened into a larger puzzle: a major industry appears to be built largely on an illusion of skill. Billions of shares are traded every day, with many people buying each stock and others selling it to them. Most of the buyers and sellers know that they have the same information, and they exchange stock primarily because they have different opinions. What makes them believe they know more about what the price should be than the market does? For most of them, that belief is an illusion.”
He then describes that it is psychology that drives the illusion. He describes that we all are part of a “powerful professional culture” that can “maintain an unshakeable faith” in any proposition, “however absurd”, because that faith in skill over luck is “sustained by a community of like-minded believers.” He continues with the primary driver of this faith:
“The most potent psychological cause of the illusion is certainly that the people who pick stocks are exercising high-level skills. They consult economic data and forecasts, they examine income statements and balance sheet, they evaluate the quality of top management, and they assess the competition. All this is serious work that requires extensive training…..but unfortunately, skill in evaluating the business prospects of a firm is not sufficient for successful stock trading, where the key question is whether the information about the firm is already incorporated in the price of its stock.”
But what if the stock price is incorporating the wrong information? Perhaps Kahneman is leaving a small crack in the window for all of us stock-pickers out there. It was Kahneman & Tversky (1979) themselves that showed us how we all become risk seeking when facing losses and risk averse when facing gains. This observation in fact became the theoretical underpinning behind the intermediate-term momentum phenomenon. The authors essentially were telling us that human beings (and perhaps Mr. Market himself) incorporate the wrong public information. Maybe ignoring the wrong information and focusing on unbiased analysis of the right information is the only way to be skillful in stock trading?
We have sometimes observed that decision-making biases are often driven by a natural tendency of herding among investors and analysts covering the stock. There are many reasons why people will “herd” around each other, and in fact we believe this herding can drive other behavioural biases (like anchoring and confirmation biases). The literature (and common sense) also suggests that the “herding” phenomenon is more likely when there are many analysts following a stock than when there are just a few. Consequently, the logic follows that we might expect to see more alpha-generation opportunities in the larger-cap, more well-followed names.
The implication is that there is at least the potential that the consensus investor is more easily observed as companies become larger and more followed, but also that “Mr. Market” may be more prone to errors of groupthink and herding in these larger-capitalization names. We correspondingly might also expect that names where there is heavy analyst coverage are more ripe for biases than names which don’t capture much attention. This would (again) run contrary to common conceptions about market efficiency.
Conventional wisdom finds it easier to believe that alpha opportunities are more likely in names which are less followed by the Street (just at it assumes that it is easier to believe that alpha is more likely in small-caps than in large-caps); whereas we are instead exploring if a larger or more well-followed company may be just as likely to be a potential source of alpha as a smaller, less-followed company. We should point out here that simply being over-covered (or the subject of consensus bias) doesn’t necessarily mean a security is cheap. It could just as easily create a situation where a security is too expensive. The bias works both ways, and a winning strategy will be one that avoids where the consensus investor is prejudiced positively, and be attracted to securities where Mr Market is prejudiced negatively.
In summary, even though we tend to mock and ridicule the behaviourally-biased trader, we should simultaneously embrace him. He and his brethren very well may be required in order for more objective thinkers to generate excess returns, and his existence may be integral to the success of an investment process that seeks to capture alpha, sustainably, over time. Moreover, it isn’t impossible that as we address mid and large-cap opportunities, this biased market participant is not only more observable, but potentially more prone to error.
Alquist, Ron and Israel, Ronen and Moskowitz, Tobias J., Fact, Fiction, and the Size Effect (May 12, 2018)
DeBondt, Werner F.M., and Richard H. Thaler, 1985, Does the stock market overreact? Journal of Finance 40, 793-808
Dodd, David, and Benjamin Graham, 1934, Security Analysis, McGraw-Hill
Kahneman, Daniel, 2011, Thinking Fast and Slow, Macmillan
Kahneman, Daniel, and Amos Tversky, 1979, Prospect theory: an analysis of decision under risk, Econometrica 47, 236-292
Shiller, Robert J., 1981, Do stock prices move too much to be justified by subsequent changes in dividends? The American Economic Review, Vol. 71, No. 3 421-436
Sinclair, Upton, 1935, I, Candidate for Governor: And How I Got Licked; University of California Press (reprint 1994)
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