Meme Stocks and Market Structure

By Edmund Bellord, Asset Allocation Strategist | June 08, 2021

Unless your investment horizon is measured in milliseconds, it’s usually best to ignore what everyone else is doing. But, occasionally, the market throws up something so peculiar that you have no choice but to sit up and pay attention.

The GameStop debacle, and the meme stock phenomenon more broadly, certainly fit that category. The story bears all the hallmarks of a Hollywood script: how a ragtag group of mostly retail investors, armed with commission-free trading apps and loosely coordinated across online message boards, executed a colossal short squeeze on the hedge funds betting against a down-at-its-heels brick-and-mortar video game retailer while inflicting bloody noses on some of Wall Street’s supposedly most-sophisticated operators. Predictably, several films are already in the works. But beyond the thrill of extravagant market pyrotechnics served up with a generous side of schadenfreude at seeing the odd master of the universe brought low by the great unwashed, why should we care?

Market manipulation is hardly new, and short sellers have always been a vulnerable target. The algebra of short selling, where the size of a losing position balloons ever higher as losses accumulate, is such that short sellers are forever in danger of being squeezed. Wait too long to cover or, worse yet, fail to rebalance at all, and you risk being wiped out. No surprise then that short selling for profit (as opposed to for hedging) is the province of dedicated specialists.

Despite their somewhat louche reputation, attested to by the prevalence of short-selling bans that reflexively blossom every time the market wilts, short sellers are nonetheless a key part of a healthy market ecosystem. A healthy market, one that allocates capital to its most productive use at the lowest possible cost, is predicated on many financial species with different time horizons, preferences, and liquidity needs co-existing in symbiosis. Despite what the textbooks might say, liquidity and price discovery are not created in a vacuum; they spring from the unceasing dance between three types of market inhabitants: long-term investors, arbitrageurs, and liquidity providers. Long-term investors attempt to steer capital towards its most productive use, arbitrageurs improve price discovery by correcting the occasional mis-pricings that emerge between assets with similar payoffs, and liquidity providers lubricate transactions, which helps to shrink transaction costs. If any one of these groups grows too dominant, the dance can quickly turn into a scrum.

It may be too early to add dedicated short selling to the long list of business models disrupted by the internet just yet, but it’s safe to assume that the shorts’ cost of capital has gone up.

Dedicated short sellers are a rare breed of arbitrageur whose relatively small number and modest asset base belie their importance. Much like value investors, whose tendency to buy when others are selling has a stabilizing effect on falling markets, short selling has a similar calming effect in the opposite direction. By leaning against unwarranted price increases, short sellers are a counterweight to market excess, one that makes for a more hospitable environment for beta grazers and alpha hunters alike. In helping to expose flimsy business models, ferret out accounting malfeasance, and unearth cases of outright fraud, short sellers are natural predators that benefit the market’s ecology. Enron, Lehman Brothers, Valeant, and, more recently, Wirecard and Luckin Coffee all owe their comeuppance in large part due to the sleuthing of dedicated short sellers.

Although short sellers are at the center of the GameStop saga, most of the ink spilled has focused on the more conspicuous elements of the story: the evident power of massed retail investors, their copious use of derivatives to magnify leverage, and the populist tendencies that seemingly motivated many of the squeeze’s participants. What has received less coverage is the potential impact of meme stock manias on market structure.

On the face of it, the debacle mirrors many previous episodes of market manipulation, no different, say, than the Hunt brothers ill-fated attempt to corner the silver market in 1980. But there is a crucial difference. A conspiracy to manipulate markets pre-supposes a central origin, a mastermind to hatch the plot before putting it into action. But on this occasion the conspiracy, such as it was, emerged spontaneously. It began with local, seemingly random interactions online that began to feed on themselves in an accelerating feedback loop.

There was no syndicate head, no directives whispered into disposable cell phones, no encrypted texts, none of the subterfuges typically associated with a conspiracy. Quite the contrary, discussions were held in the open, within freely accessible (albeit anonymous) web forums, where anyone was able to proffer their views about the fundamental value of the business, comment on the high short interest, or add an opinion about the implications of the tight float of underlying shares outstanding.

Decentralized and self-organizing short squeezes that materialize spontaneously represent a new type of concern for regulators because it’s unclear which rules, if any, are being violated. Moreover, it’s far from clear what mechanisms can be put in place to prevent it from happening again. But while this may be a headache for regulators, it represents an existential threat to short sellers. It may be too early to add dedicated short selling to the long list of business models disrupted by the internet just yet, but it’s safe to assume that the shorts’ cost of capital has gone up.

The impact of this new regimen on short sellers is impossible to gauge with any precision. They are a secretive bunch, after all. But we can guess at their travails by looking at the performance of the most shorted stocks as represented by the Citibank US Short Interest Equity Index. The index is akin to a long/short portfolio constructed according to the level of short activity for each stock in the Russell 3000, measured as the ratio of the amount of stock on loan relative to its overall trading volume. After ranking stocks according to this ratio and removing stocks with the most extreme metrics such as high borrow cost, the index simply shorts the 10 percent of stocks with the highest short ratio and goes long the 10 percent of stocks with the lowest short ratio. Historically, simulating short sellers in this way has been a profitable strategy: from its inception in June 2015 through the end of 2019 the index generated a cumulative return of 35%, with a highly respectable return to risk (Sharpe ratio) of close to one. At the onset of the pandemic in early 2020, which coincided with a jump in retail trading reminiscent of the tech bubble, the index collapsed. Over the following months it gave up almost its entire accumulated historical performance before reaching its nadir in January of this year, just as the GameStop episode reached its crescendo. Given the index’s long exposure to the least-shorted stocks, it likely understates the actual damage inflicted on many actual short sellers.

Source: Bloomberg

It’s a truism that no one enjoys losing money, ever. And if the performance of the index is indicative of the damage inflicted on short sellers, we can expect an imminent thinning of their ranks and with it a weakening of their stabilizing influence.

There is a small town in Thailand whose large population of macaque monkeys draws a steady stream of tourists. The locals sell bananas to the tourists who feed them to the monkeys. When the flow of tourists dried up during the pandemic, this balance was thrown into turmoil. Within weeks, the town was overrun by gangs of starving monkeys. Whole neighborhoods were declared no-go areas by authorities after videos of rampaging monkeys went viral.

It’s probably a stretch to claim that having fewer short sellers would have quite such a dramatic impact on market structure as the loss of tourists had on this Thai town, or that the monkeys are now calling the shots, but markets are notoriously susceptible to unforeseen events. A seemingly inconsequential disturbance in one area can ripple out, propagating and growing until it ultimately leads to systemwide effects. While our attention is often drawn to conspicuous price movements, it’s easy to overlook the veiled institutional or structural changes that sometimes precede and may even precipitate them. Bananas, anyone?

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Getting Real About Inflation … and Gold

By Edmund Bellord, Asset Allocation Strategist | January 08, 2021

As favorable vaccine news piles up, the winds of reflation are stirring. Early signs of an equity market style rotation in favor of cyclical value stocks, a weakening of the safe-haven US dollar, and a run-up in market-derived measures of inflation expectations all point to a resurgence of animal spirits despite a gloomy outlook for the economy. With our monetary maestros promising easy money into the distant future come what may, it is time to spare a thought for what the possible return of higher inflation might do to your portfolio. Inflation is viewed as the bane of fixed income investments, and rightfully so. But inflation can also wreak havoc on stocks. In theory, inflation should have no impact on equities provided companies are able to pass along higher input costs to their customers. In practice, equity valuations are highly sensitive to changes in the price level, tending to plummet when prices jump. No wonder investors are already casting about for inflation protection.

For a vociferous minority, the only bankable hedge for inflation is gold. For them, every spike in the gold price is reproof of government perfidy and foreshadows an inflationary surge. The evidence linking gold’s price and inflation, however, is curiously threadbare. If gold is an unreliable hedge against rising prices, what role, if any, should it play in a portfolio?

Gold as Currency

Gold, having shed its function as a means of exchange and unit of account, is still used as a store of value. Its inflation-hedging bona fides spring from the notion that, unlike other stores of value, it cannot be debased. Central bankers have the power to conjure fiat money at the stroke of a keyboard, but they are powerless when it comes to the quantity of gold. The price of gold may vary from day to day, but with a fixed supply on the order of 250,000 tons, of which one fifth remains lodged in the earth’s crust waiting to be mined, scarcity ensures that over long time spans its purchasing power remains intact. In 1934 an ounce of gold would have set you back US$26; had you buried it in the ground only to dig it up today, 86 years later, it would be worth almost US$2,000. Not a bad return when you consider that a paper dollar lost approximately 99% of its purchasing power in the interim.

But, of course, this simple illustration is dreadfully misleading. It is true that, had you let slip a dollar bill down the back of the couch while resting after burying your gold some 86 years ago, that dollar bill would buy you far fewer goods at the cash register today. Most dollars, however, are not left lying around to gather dust; they are deposited for safekeeping and, until recently, they earned interest. Fairer would be to evaluate gold relative to what you would have earned holding cash on deposit. According to Barro and Misra¹, the long-term compounded return on cash (T-Bills), after accounting for inflation, has been 1% per year, just shy of gold’s 1.1% real return. Gold may have won by a nose, but that extra 10 basis points came at the expense of frequent eye-watering price fluctuations and the occasional sleepless decade.

Echoes of the Gold Standard

It turns out that gold’s reputation as an inflation hedge is really founded on just two episodes: the end of the gold standard and the oil shock of 1979. Between 1971 and 1975 the price of gold quadrupled as the US severed the official link between the US dollar and gold. Again between 1977 and 1980 the price of gold tripled as the inflationary impact of the second oil shock rippled through the entire energy-dependent supply chain. Outside of these two peculiar instances, the relationship between gold and inflation largely falls apart. Remove just the years of 1974, 1979, and 1980, and as we can see the positive correlation between inflation and gold disappears entirely.

Figure 1: Correlation between change in Gold price vs. Inflation 1971-2020

If inflation isn’t driving the gold price, what is? The evidence suggests that a big part of what’s moving gold prices are real interest rates—or the difference between 10-year treasury yields and inflation—whose movements up or down are an important indicator of the underlying state of an economy and its expected growth. This inverse relationship between gold and real rates is born out in the next figure, which shows yearly changes in the price of gold and real interest rates from 1971 to 2020. The large increases in the gold price in 1974, 1979, and 1980, in addition to the price spikes of 2011 and 2020, all occurred against a backdrop of negative real rates. Correspondingly, the gold price declines of the early ’80s coincided with soaring real rates, a consequence of the tight monetary policy enacted during Paul Volker’s chairmanship of the US Federal Reserve.

This relationship between real rates and gold echoes the historical linkages between gold and the US dollar. Under a gold standard, because currency values in terms of gold were fixed, trade imbalances between countries were routinely resolved by a physical flow of gold. Gold would flow into countries that exported more than they imported and had high real exchange and interest rates, and out of countries where the opposite conditions held. But under a fiat system, where currency values in terms of gold are no longer fixed, real interest rates continue to exercise their pull, except now rebalancing occurs with a change in the price of gold instead of a flow. Perhaps because of its ongoing role as a central bank reserve asset and store of value, gold behaves like a shadow currency. A currency where, absent the prospect of a future cashflow, assessing how much to own comes down to what else you could be doing with that fraying dollar bill.

Hedging Inflation: It Depends

Just because gold has kept pace with the price of goods and services does not make it an effective inflation hedge in every scenario. And that’s because the alternate sources of expected inflation—diminished supply versus excess demand—have drastically different implications for real rates and hence for hedging strategies. If you think the world is in the thick of a deflationary or stagflationary bust that will depress real interest rates, then by all means buy gold. The current pandemic, like natural disasters more broadly, can certainly fit the pattern and to the extent it continues to depress consumption could still prove to be one of those kinds of periods. But if you are concerned about monetary excess, adding gold to a portfolio may turn out to be futile and may even magnify risks. If central bankers succeed in reviving inflation by stimulating demand growth, then we should also expect real rates to increase and the gold price to weaken. In that scenario, to hedge inflation you are better off buying TIPS and selling conventional bonds.

It’s only fair to point out that any notional horse race between gold and other assets assumes a functioning financial system nested in a stable society—not an unreasonable assumption for an optimist. But you don’t have to peer too far back in history to find examples of conflict, dispossession and collapse. Beyond keeping up with the price level, part of gold’s appeal lies in its tantalizing potential to ward off financial devastation. Although, if society deteriorates and its ability to function looks dicey, the risk of confiscation also shoots up and your chances of avoiding devastation by holding onto your lump of gold decline precipitously. This makes gold a bit like owning an out-of-the-money put option on social collapse underwritten by an ultimately insolvent counterparty. There is no chance of collecting, but at least its value should rise when people are fearful.

Endnotes

¹Robert Basra and Sanjay Misra, National Bureau of Economic Research, “Gold Returns,” NBER Working Paper Series (February 2013).

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Don’t Just Do Something—Stand There

By Simon Hallett, Vice Chairman | May 26, 2021

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.

Benevento,Italy,,February,4,,2018:,Lorenzo,Insigne,Of,Napoli,Hits

At my own club, last season, we had a pair of games scheduled close together. In the first, we gave up a 1-0 lead late on and ended up with a tied game. In the second, we scored a late goal from an unexpected source to win 1-0. The narrative of the first was that “we didn’t know how to hold a lead,” and of the second that “we were gutsy and played to the end.” Same team, same players, both close games, but different outcomes drove radical differences in explanation.

As in investing, in sports a series of poor results needs a narrative to explain it, and action to reverse it. Often that action is to replace the coach. Acting to replace him when results go the wrong way attributes far too much causality to the coach. George Steinbrenner famously hired Billy Martin five times as coach of the New York Yankees. Between the Premier League and the three levels of the EFL, more than half of the 92 clubs replaced their manager this season alone. Replacing a manager tends to come at considerable cost—he (it’s always he) will have his own preferences for players and staff, and perhaps may even want to change the style of play completely—with little evidence that the players who actually kick the ball around improve their own performances as a result. Because luck occurs randomly while skill is reasonably constant, after teams are unlucky for a stretch their luck will tend to mean revert. The “manager bounce” is a well-established phenomenon whereby short-term results usually improve after a manager is replaced. It is a statistical phenomenon, though, that has little to do with on-the-pitch performance.

For asset owners, there is a similar temptation to replace a manager after a period when returns have disappointed, but, alas, unlike the fans of a soccer club, the clients of an investment manager do not enjoy the mean-reverting returns that the manager provides those who stuck with them.

For asset owners, there is a similar temptation to replace an investment manager after a period when returns have disappointed. But, alas, unlike the loyal fans of a soccer club, the former clients of an investment manager do not enjoy the mean-reverting returns that the manager provides those who stuck with them. There is plenty of evidence that investors’ urge to act is damaging to their long-term returns. In mutual funds, on average, dollar-weighted returns that shareholders receive from their funds lag the time-weighted returns that the funds generate. This “behavior gap” is directly the result of poorly timed action on the part of shareholders.

Incentives and market structures only make the bias toward action greater. One reason that English soccer coaches get changed is that, once the season starts, players may not be traded outside the month of January. A result is that during the January transfer window it’s almost non-stop activity. The period has become its own media event, with fans, players’ agents, and media pundits all calling for teams to make their moves. This, even though only a few such moves ever have significant impact on a team’s results, and despite evidence that prices paid for players tend to be higher than between seasons.

The investing industry has many incentives to transact; indeed, the revenue models of many participants depend on transactions taking place. When I started in investment management, in London in the late 1970s, our fees were not based on assets managed as is the case today. We were paid when we made a transaction in our clients’ discretionary portfolios. Why is the portfolio turnover of the average equity mutual fund so high, when doing nothing and allowing returns to compound over prolonged periods of time is often a superior way to generate market-beating returns? It’s because the investment industry exploits clients’ bias in favor of action. Managers’ actions are described in emotional terms. We read of “conviction,” of “exciting opportunities” and “story stocks.” The reality is more mundane. Successful investing is about resisting the urge and the calls to action, knowing when to sit on your hands and do absolutely zilch.

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

By Simon Hallett, Vice Chairman | July 09, 2021

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.

The pandemic meant the stands were still empty at “Theater of Greens,” the home stadium for Plymouth Argyle this year, but the ideas were plentiful as to how to harness the theories of behavioral economics to put a more competitive squad on the field.

Richard Thaler, who won the Nobel Prize in Economics for his work in behavioral finance, has noted that 1980s basketball superstars like Larry Bird converted their three-point shot attempts at the same near-40% rate as 21st-century sharpshooters such as Steph Curry or James Harden. Yet, Bird took half as many three-point attempts as are normal today, favoring shots closer to the basket, which great players can hit roughly 50% of the time. It took 30 years for the three-point shot to become as popular as it is today or, in other words, for basketball to realize that 0.4 x 3 is greater than 0.5 x 2.

The Bill James Baseball Abstract, an annual compendium of baseball statistics that ultimately legitimized the science of baseball sabermetrics, was neglected for many years before a James disciple, Oakland Athletics General Manager Billy Beane, used the approach to identify underpriced skills for his small-market team, as popularized in Michael Lewis’s 2002 Moneyball. It was only then that James himself landed a job in the front office of the Boston Red Sox, helping the team finally overcome the “Curse of the Bambino,”¹ and win its first World Series in 86 years.

Many baseball fans complain that the influence of Moneyball has been too great—players are chosen purely for their ability to walk or jack balls over the fence; defenders are all stacked on one side of the infield because that’s where the statistics say the vast majority of a given batter’s ground balls will be hit. “It’s no fun anymore!” Clearly, those fans prefer intuition and stories to success and efficiency. They also subscribe to the great man theory, that results are driven by individual managerial genius, the wizened skipper playing a hunch.² And yet, organizations typically strive to create and adhere to processes that can improve their probability of success—to control luck.

I have been involved in two firms with many similarities, one being an investment manager and the other a football (soccer) club. An investment portfolio can, through careful construction, be more than the sum of its individual parts thanks to diversification. It may seem odd, but a football team is a portfolio. It, too, needs careful construction. You can’t simply rank order the most attractively priced available players and take the top 20 to form your squad. You would end up with a team made up only of defenders, and no goal scorers.

More than a decade after John Henry, the Red Sox owner who had hired Bill James, purchased Liverpool FC and brought Moneyball to the UK’s Premier League, systematic use of data analytics has finally worked its way throughout the ranks of English football. At my football club, Plymouth Argyle, which plays in the third tier of the leagues, we have set rules and standards to guide the decision-making of those who select the squad. Beginning with our philosophy, i.e., answering the question “What is the style of football we wish to play?,” we have defined the desired characteristics of each position. Our philosophy includes playing the ball forward from the back with quick passes along the ground to the opposition’s part of the field. Our goalkeeper must, therefore, be able to kick with both feet and play short passes while under pressure from the opposing forwards. We also prefer to play in a tactical lineup, known as a 3-5-2, with a pair of strikers at the front and a couple of fit defenders, one on each side, who dash up and down the wings depending on whether we or the opposition have the ball.

Defining the philosophy this way and defining how we will implement it enables us to search databases for players that match our criteria in each position, such as the defender we recently signed based on some impressive data around his defensive blocks, aerial duels won, and tackles per game. Then, in quantamental fashion, we can conduct research into aspects of players that can’t be quantified (yet!), such as their character, personality, or work ethic.

There are differences between assembling an optimal squad of football players and an investment portfolio. One is that securities prices are freely available, updated continuously, and can be compared with their hypothetical value generated by a model. That is not the case with football players. Transactions can only be made in two “transfer windows,” one midway through the season in January, the other during the summer before the next season starts. And no one has yet come up with a model that can assess players’ value in the way that we forecast cash flows and discount them to a present value to give an idea of what a share of stock is worth. I live in hope, though!

The market for football players is relatively efficient, but not completely so, and becomes less efficient the lower down the leagues you go. In this way, the relative inefficiencies of the market are parallel to those for, say, US large caps compared with those for emerging market small caps.

But surprisingly, perhaps, there are more similarities than differences. The market for football players is relatively efficient, but not completely so, and becomes less efficient the lower down the leagues you go. In the Premier League, the most watched football league in the world, there is a strong correlation between what you pay and the results you achieve. That is not the case lower down, so my club has a strong incentive to improve decision making, to exploit the behavioral biases and subsequent mispricing that is prevalent. In this way, the relative inefficiencies of the market are parallel to those for, say, US large caps compared with those for emerging market small caps. Similarly, though, as the potential gains to improved decision making increase, so does the resistance to replacing intuition with algorithms and process that reduces the degrees of freedom under which individuals operate. Those clubs which can overcome that resistance will generate a competitive advantage—an edge. I believe my football club has such an advantage, but I am on the alert for signs of backsliding—going along with “But that’s the way we’ve always done it!”

We have gone down this path at Plymouth Argyle because we want to spend the Club’s money wisely and compete by being smarter, not by spending more. At Harding Loevner we started down this path 25 years ago as decision making spread beyond the handful of founders to an expanded investment team. Each portfolio remained the product of two single decision makers but was now made with input from over 30 analysts. We had to learn how to structure a process that benefits from group wisdom but is not damaged by “groupthink.” The foundation of that was, and still is today, individual accountability and aggregation of individual decisions. Analysts drive the process and decide what stocks they will cover. They are free from direction by their colleagues, and free from direction by portfolio managers. They are not completely free, though. Just as Argyle’s team must recruit players who meet the objective standards we have established as being consistent with our playing philosophy, Harding Loevner analysts must confine their activities to securities of companies that they judge to conform with our investment philosophy, which focuses on growth, quality—which we have historically equated, in part, with a demonstrated track record of profitability—and price. When we look back at the last 25 years, we can see clearly that the arc of evolution of our investment process has been to define more clearly and rigorously the rules that restrict our analysts’ liberty to follow any company they chose. This has been highly effective at controlling biases and risk, and, overall has been good for returns.

Today, there are any number of voices, both internal and external, calling us away from the framework and structure that have served us well. The rise of the digital economy, and its steady proliferation of fast-growing but still-unprofitable businesses with compelling narratives, continually tests our reliance on an established track record as a guide to the future and the best indicator that a company has the culture and institutional strength to withstand cyclical downturns and shifting competitive landscape. Has the nature of growth changed? Have the kinds of characteristics that define quality shifted? Or are those merely the stories we tell ourselves to justify paying higher prices for the hot new fashion?

I don’t know the answers to those questions yet. I do know that, while it is necessary for portfolio managers to evolve along with markets, such evolution should take place deliberately and only after careful consideration. At Argyle we are at the early stages of translating our playing philosophy into a structured process for how we find players, and how they play on the field. Already, though, there have been occasions when we’ve had to adapt on the fly and adjust our typical tactical lineup. Football, like investing, is a game where the opposition can see what we do, and we must adapt to how they counter our plans. Players get injured, and replacement players may be less capable at implementing the approach. So, how we implement our philosophy must evolve, but we must be clear with ourselves that such adjustments are a change in process, not a change in philosophy. If we were to start changing our philosophy, we would surely be lost, tossed on a swirling sea of narrative.

Endnotes

¹Purportedly begun in 1920 when, after he had led the club to three World Series titles in six years, the Sox traded George Herman “Babe” Ruth to the rival Yankees for $125,000 (about $1.7 million in today’s dollars, or roughly the salary of Boston’s current backup catcher, Kevin Plawecki).

²It could be said the great man theory is also a feature of investment marketing—how often do brand name investment managers attract large amounts of client assets and then collapse in ignominy?

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Out of Our Minds

Meme Stocks and Market Structure

Source: Bloomberg