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Too Much Information

In the late 1950s, in his book Common Stocks and Uncommon Profits, Phil Fisher recommended making investment decisions based on “scuttlebutt,” the kind of information an investor could get by asking around. This entailed tracking down and interrogating customers and competitors, employees, and former employees. Doing research, in the sense of gathering evidence and analyzing it to reach a conclusion, was hard work, but enabled analysts committed to such intellectual labor to obtain an edge over their competitors simply by having better, and more complete, information.

Indeed, when I started my career in investing in the late 1970s, obtaining even basic financial info about a German car company still required going to Germany and knocking on the company’s door.

Now gathering information no longer takes much effort. We are deluged by floods of data—not only the details of prices, volumes, margins, and capital investments of individual companies, but also highly granular data about credit card receipts, numbers of cars in parking lots, or words used in media reports. These new, “alternative” sources of information have briefly given some stock pickers a slight edge in predicting short-term stock price movements. The informational advantage provided by such data is but fleeting, however; once this data is commercially accessible to everyone, the advantage disappears. Thus, even for the short-term investor, information gathering itself no longer provides a lasting edge.

For long-term investors, the relationship to information has changed even more fundamentally. You no longer need to seek information; it finds you. Your job, rather, is to act as what Lou Gerstner, the former CEO of IBM, called an “intelligent filter”—determining the information that is important and ignoring data that (in the case of the investor) doesn’t help you forecast cash flows and estimate the value of a security.

The fact that filtering information is the long-term investor’s task, of course, doesn’t prevent most from feverishly pursuing every bit of information they can about the companies they follow. Egged on by the 24/7 news cycle, internet chat rooms, and by data providers to know their companies in as much depth as possible, investors often seek to become experts in every aspect of each company’s business. It’s dubious whether this helps them make better estimates of what a company’s shares are worth. Instead, the evidence suggests that, beyond a certain amount, each extra piece of information has zero marginal impact on forecast accuracy. The impact remains positive, however, on the investor’s confidence in their forecast.

The evidence suggests that, beyond a certain amount, each extra piece of information has zero marginal impact on forecast accuracy. The impact remains positive, however, on the investor’s confidence in their forecast.

In one unpublished study, described in Winning Decisions by J. Edward Russo and Paul J. H. Schoemaker, people who handicap horse races were asked to predict, based on increasing amounts of information, which horse would win a race. They found that, beyond a very limited amount of data, forecast accuracy did not improve with more data, but the handicappers’ confidence in their forecasts continued to grow with each extra bit of information.

Knowing more makes you feel better, in other words, but doesn’t help your decision-making. In investing, feelings and actual results arguably are even more disconnected. After all, feeling good about a decision is rarely a help in successful investing—to have a good outcome, an investment view must be different from that of most other investors, and standing apart from the herd almost always leads to discomfort.

Sitting on Our Asses

The job of an investment analyst, then, when forecasting a company’s business prospects and the price that should be paid for its stock is to distinguish between what is important—the signal—and what is useless noise. That’s what we do at Harding Loevner. Our “common language” is designed to guide investment collaboration by helping us focus on low-frequency signals that are important to a long-term investment thesis and avoid being distracted by torrents of high-frequency information that obscure the relevant underlying issues.

We recognize that our industry has an extensive tradition of emphasizing high-frequency signals to induce transacting. In the past, much of the revenue associated with financial services was transaction-based. Brokers were paid only when customers transacted (indeed, when I started my career, so were investment managers!). Unsurprisingly, brokers devoted great effort to stimulating customers to act. Customers responded as you’d expect them to—humans like action, not sitting still. Although the investment management industry has shifted in recent years to replace commissions with asset-based fees, there remains a popular expectation that a good investor will be active, including taking advantage of the most readily available and highest-frequency bits of information: stock price movements (both up and down).

Few investors, though, are able to capture any benefit from high-frequency signals. Our analysts don’t even look at stock prices until a company has been thoroughly researched and qualified as meeting our quality and growth criteria, its long-term cash flows have been forecast, and the fair value of its shares estimated.

Stock prices are much more volatile than the underlying qualities of the business they are supposed to reflect. Investors should remember the words of Charlie Munger, who said successful investing is a matter of “finding a few great companies, then you can sit on your ass.”1 Of course, while we spend a lot of time following Mr. Munger’s advice, that doesn’t mean we are sitting still. We are constantly questioning our assumptions, testing our hypotheses, updating our information and, occasionally, as a result, changing our minds. Usually, though, ignoring the calls of those whose business model, if not entire worldview, revolves around urging you to move is the key to success.

Compounding the Effect

An investment process structured around the long term, and asking questions about long-term strategy not short-term results, will focus on a few fundamental signals that show a company’s progress in creating value for its shareholders. It will focus on competitive structure of an industry, and durable competitive advantages, rather than on the outcomes of the recent past. It will take what you’ve learned and use that to forecast a company’s investments in its business and the cash flows those investments should generate over long periods of time. Only then can you make an informed guess as to what a company is worth and compare it to what the market is inviting you to pay.

A process focused on the long term also recognizes the importance of compounding—that over a long holding period, even if you did overpay, the rate at which a company continually reinvests its cash flows will be a much more important contributor to your return. In an era when information is so democratized, our one true edge is an ability to latch onto a few incremental competitive advantages that we’ve identified in a company, and allow the company to do its job over the long term and provide the power of compounding to our clients’ portfolios.

In an era when information is so democratized, our one true edge is an ability to latch onto a few incremental competitive advantages that we’ve identified in a company, and allow the company to do its job over the long term and provide the power of compounding to our clients’ portfolios.

Humans invariably underestimate this phenomenon. Compound interest is one of the wonders of the world, yet few people understand how powerful it is. It appears our brains are designed to deal with linear, not exponential progressions.

If there was any doubt about our difficulty in intuiting the power of exponential growth rates, look at how unperturbed most people were a year or so ago when COVID-19 began spreading, first in tiny increments. People could not grasp what the impact of a very standard exponential growth curve could be until it was sloping nearly vertically upwards.

A long investment time-horizon also benefits from the long term being more predictable, despite being the sum of a series of short-terms. When some luck is involved, individual outcomes are unpredictable, but the rules of probability dominate as the number of independent trials and outcomes increase. The outcome of a single spin of a roulette wheel, a roll of dice, or draw of a card is unpredictable, but in the long run the house’s victory is as near a certainty as we can get in this world.

Our job is to turn the coins we toss into unevenly weighted ones, by being disciplined about the information we use, diligent in our research, and allowing the companies in which we invest our clients’ capital to do the heavy lifting for us.


1Charlie Munger, Berkshire Hathaway Annual Meeting, 2000.

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Don’t Just Do Something—Stand There

Humans prefer to do something rather than nothing. We like office environments that are a “hive of activity” and commend “men of action.” When stuck in a traffic jam, we will take an alternate route just to keep moving, even if it prolongs the journey. We tend, though, to conflate activity with productivity, mistaking the people whom we see doing the most with those who are the most valuable.

We see this bias in many domains. Our political leaders tend to respond to a crisis with ill-considered policies that capture attention but often do little good and may even do harm. It would be unacceptable for them to stand by and simply do nothing. While serving as both vice chairman of Harding Loevner and as chairman of a professional soccer club that competes in the English Football League (EFL), I have been struck by the parallels between investing and sports when it comes to the biases that damage effective decision-making. Studies have looked at penalty kicks in soccer. When a penalty is awarded, the ball is placed 12 yards from the center of the goal and a kicker gets the opportunity to score with only the goalkeeper standing in the way. It turns out that because of the goalkeeper’s bias for action, the optimal place to kick the ball is directly at the center of the goal. A goalkeeper will almost always dive one way or another in anticipation. If he dives the wrong way, he’s forgiven as having simply guessed wrong, or as being sent the wrong way by the kicker’s supposed feint. If he dives the right way, he has a chance to stop the ball entering the goal. If he merely stands in the middle, however, he is the subject of much abuse for doing nothing.

Investors fall victim to similar pressures and impulses. The immediate costs of transacting are low, and the propensity to transact is high. The result is that investors transact too much, and their returns suffer. They tend to transact at the wrong time, buying after prices have risen, and selling after prices have fallen.

Underlying these behaviors is a general misunderstanding of the roles of luck and skill. In sports and in investing, short-term results are the outcome of a combination of the two. Yet, we tend both to attribute the outcome more to skill than to luck and to extrapolate a series of outcomes (good or bad) into the future. This tendency stems from our deep-seated need for explanation, and a need to feel we are in control even when we are not. This occurs particularly in those sports, like soccer, that are generally low-scoring affairs. Unlike in basketball, for example, where there will be more than a hundred points in a game, the average number of goals in a professional soccer game is roughly three. The result of a single game will largely be driven by luck—one bobble of the ball, the inches between hitting a goalpost and scoring, a poor refereeing decision. Yet the narrative in post-match interviews is seldom “we got lucky.” At least, it’s seldom the case that “we got lucky” when the interviewee’s team wins. When the team loses, the loss is the result of bad luck! How similar this is to investment narratives, where there seems to be only two kinds of investment managers: the talented, and the unlucky.

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Down the Rabbit Hole

In trying to make sense of the state of things today, I found myself thinking of snippets I’ve heard from Lewis Carroll’s Alice in Wonderland. Until recently, however, I had never actually read the story. So, I went to and ordered a copy of the entire Alice in Wonderland Collection (Alice’s Adventures UndergroundAlice’s Adventures in WonderlandAlice Through the Looking Glass, and The Hunting of the Snark). While I was underwhelmed by the character development in these stories, I did find some takeaways that seem relevant today. Still, perhaps the most provocative line from Alice that I came across is one that was written not by Lewis Carroll but by Czech film director Jan Švankmajer for his 1988 film Alice.

The film opens with Alice saying, in part, “But, I nearly forgot, you must close your eyes otherwise you won’t see anything.” After all, Alice would never have experienced Wonderland or journeyed through the looking glass if she had not closed her eyes. And we’d have no Mad Hatter, no March Hare, and, of course, no Red Queen.

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Stock Portfolios, Football Teams, and the Stories We Tell Ourselves about Each

The world is complex and unpredictable, but humans prefer order, and cause and effect, so therefore tell stories that purport to explain what is simply random. Narratives pre-date writing. They help make events coherent and memorable, while arousing emotions in the listener. Behavioral biases, which all humans share, are in many cases essentially products of the stories we tell ourselves. The more detailed the story, the more entertaining it is and the more powerfully it can affect our emotions. We love stories. That can often be wonderful, but in decision making it can be dangerous.

In investing, there has been at least a little progress towards improving decision making by resisting the power of stories. Quantitative investors describe how they adhere to purely objective rules (rules and lines of code that, of course, they themselves have written) to govern their behavior and reduce bias. “Quantamentalists,” another breed of investor, allow some judgement to enter their decision making once they have established the framework. They do this in part in recognition that, as a rule, most humans don’t like rules. We suffer from what psychologists call “algorithm aversion,” i.e. preferring to go with our gut. That preference results from our need to remain in control, or at least to believe we are. Permitting human override of an algorithm may degrade the quality of its output, but in granting themselves the comfort of exercising some degree of control, decision makers likely improve their rate of adherence, for an overall improvement in outcomes. I fully expect self-driving cars to come with a steering wheel that will have no impact on direction of travel, but will allow the human passenger to feel more secure than if she were simply sitting back and giving herself over fully to the computer under the hood.

In his book The Success Equation, Michael Mauboussin writes extensively about the importance of a strong process and rules in activities where the immediate outcome is driven by luck and skill. He describes how it is possible to improve skill through what has become known as deliberate practice: repetitive, purposeful, and systematic repetition with immediate and specific feedback. Luck, however, can only be managed by having a strong process, with rules or standards constraining decision making and the urge to impute too much importance to our role in any one result. In activities such as investing or team sports—arenas where skill and luck both come into play—narrative is particularly seductive, making adherence to this recipe for success a constant battle.