Out of
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In addition to tariffs, the regime implemented strict import quotas and licensing systems, restricting both the volume and type of goods allowed into the country. These measures were designed to conserve foreign currency reserves and shield domestic firms from international competition. The government also nationalized key industries such as railroads and energy, shifting control from foreign hands to the state.

Initially, the strategy appeared to succeed as industries such as auto manufacturing, textiles, and steel expanded rapidly. But this protection led to complacency—Argentine cars grew costly and outdated, unable to compete with imports. The heavily shielded textile industry became a major employer but remained inefficient and high-cost, limiting global competitiveness. State-owned heavy industrial companies such as steelmaker Somisa faced similar issues: overstaffing, obsolete equipment, and reliance on government support.

Booming global demand for Argentina’s agricultural exports in the immediate post–World War II period had provided the foreign exchange needed to finance the country’s industrial push. But as postwar Europe recovered and commodity prices fell, Argentina’s export revenues fell sharply. With foreign currency scarce and domestic industries now dependent on protection, the limitations of the model became apparent. Production quality lagged, costs rose, and Argentina became increasingly inward-looking and uncompetitive on the global stage.

What began as a drive for economic sovereignty ultimately resulted in deep structural weaknesses—fiscal imbalances, declining productivity, and persistent inflation— and the onset of Argentina’s prolonged economic decline. Inflation escalated from 20% annually in the early 1950s to severe, chronic levels that persisted for decades, eventually culminating in hyperinflation by the late 80s. The policies introduced under Perón cast a long shadow: once one of the world’s ten wealthiest nations by GDP per capita, Argentina steadily fell behind its peers, dropping to 79th place by 2023.

While the Trump administration’s protectionist turn echoes elements of Argentina’s economic nationalism, it lacks several core features that defined the Peronist model. There is no nationalization of industry, nor a broad push to reshape the domestic economy through state planning or import substitution. Instead, Trump’s approach reflects a singular obsession with applying punitive tariffs to reduce the trade deficit—ignoring the basic accounting reality that cutting the trade deficit necessarily shrinks the capital surplus.

The flipside of the US trade deficit is its capital surplus, when the US runs a trade deficit—importing more goods and services than it exports—those dollars don’t simply vanish. Instead, they return in the form of foreign investment, with foreign capital flowing in to support equities, bonds, and the dollar.

If fewer dollars flow abroad through trade, fewer dollars will be recycled back into US assets. This shift could weaken demand for Treasuries, forcing yields higher and tightening financial conditions across the economy. US equities, long buoyed by steady foreign inflows, would face downward pressure, while a stronger dollar—resulting from tariffs or restricted trade—could further erode US export competitiveness.

The flipside of the US trade deficit is its capital surplus, when the US runs a trade deficit—importing more goods and services than it exports—those dollars don’t simply vanish. Instead, they return in the form of foreign investment, with foreign capital flowing in to support equities, bonds, and the dollar.

In short, efforts to shrink the trade deficit cannot occur in isolation; they will directly impact the capital account, reducing foreign demand for US assets and challenging the fundamental financial stability that has long underpinned US economic dominance.

Argentina’s experience vividly demonstrates how pursuing economic self-reliance can become self-defeating, as protectionist policies breed inefficiency, deter investment, and ultimately trigger spiraling inflation. Although the United States today operates in a markedly different context, its sheer economic magnitude, central position within the global economic system, and reliance on global capital flows mean that even a modest inward pivot carries outsized risks.

What hasn’t changed is our view that US policymaking in the new administration bears many of the hallmarks that we’ve come to associate over the last 35 years with emerging markets—and not the best performing ones, either. The erosion of institutional continuity and effectiveness tends to enable more erratic policymaking. This institutional disruption doesn’t just affect the regulatory stability that companies rely on to make long-term investment decisions, it also undermines predictability of enforcing contracts with suppliers, service providers, and customers. Just seven years ago, investors howled when Mexican President López Obrador unilaterally canceled the completion of an already-under-construction Mexico City Airport, leaving contracts unpaid and long-term investment plans disrupted. Now, the US government—reprising a pattern from President Trump’s business career—is terminating both employment contracts and commercial services contracted for various government agencies.

In our third quarter 2024 letter, we wrote about our potential exposure to new US tariffs and asserted—optimistically—that the risks were modest and manageable. That view was shaped by Trump campaign’s focus on China as the key malefactor behind US trade imbalances. That has proven a misjudgment on our part, as early salvos in the new trade war quickly hit China, the US’s primary geopolitical rival, but then were re-targeted at its closest neighbors, Canada and Mexico, and then at its closest allies in Europe. Before the April 2 “reciprocal tariff” shock, the most directly affected company in our International Equity portfolio was Canadian National Railway, a critical freight transport provider that, despite its name, links US states with each other, but of course also connects the US with its largest trading partner, and—no small thing—one of its top export destinations.

Another area of policy more often seen in developing countries than mature democracies is the practice of governments extracting concessions or favors from companies or individuals in exchange for letting them get on with their normal course of business. The recent case of TSMC investing a further US$100bn in the US after being threatened by targeted, ultra-high tariffs is a distasteful example of such a commitment being demanded from a company. Especially a company that had already responded voluntarily (and at large scale) to Biden-era Chips Act incentives, building a new semiconductor fab in Arizona, slated to ramp up high-volume, advanced chip production this year.

Our point here isn’t to dispute the policies¹ themselves, but rather to highlight the harm to predictability, and by extension to business confidence, from abrupt, poorly signaled shifts and their frequent reversal (and the reversal of the reversals.) This is not a business-friendly environment. When the rules of the road become increasingly arbitrary, companies—domestic and foreign alike—become less willing to commit capital. Uncertainty undermines both the appetite for investment and the demand outlook that would justify it. While TSMC’s investment commitment garnered headlines, there will be no headlines for the thousands of business projects that quietly get canceled in the US due to rising policy uncertainty. International Equity portfolio holding Air Liquide is already reversing its plans to build four hydrogen gas pipeline hubs in the US due to abrupt (if not entirely unexpected) regulatory shifts by the new administration. Meanwhile, US consumer confidence is falling as inflation expectations rise in anticipation, rationally, of the higher cost for most of the goods consumers want to buy. This does not strike us as a backdrop that supports elevated stock price valuations in the US. The relative outperformance of non-US markets this quarter—the largest quarterly lead over US stocks in fifteen years—offers a taste of how that could play out.

The world economic order that created vast wealth through open trade and cooperation now faces potentially radical disruption as the US reshapes its own role in that order. As stewards of your capital, our task is to see the world as it is, not as we might wish it to be.

From our vantage point as global investors “here at the edge of the stage,” the challenge of protecting and growing our clients’ wealth feels more daunting than usual. The world economic order that created vast wealth through open trade and cooperation now faces potentially radical disruption as the US reshapes its own role in that order. As stewards of your capital, our task is to see the world as it is, not as we might wish it to be, and anticipate the possible consequences of chaotic and self-destructive economic, business, and foreign policies, even when they stop making sense to us.

From a portfolio perspective, our investment process has always prompted us to understand the industry dynamics that affect how companies operate, to grasp and assess the source of a company’s superior profitability, and to have insight whether that source will endure or evaporate easily as foreseeable pressures arise. Thus, we’ve long harbored an aversion to companies whose profits were especially vulnerable, as we once put it, to “the whims of faceless bureaucrats and capricious politicians.” That practice has given us a leg up in parsing our portfolio holdings and potential new investments for companies situated to better avoid the fallout from a damaging trade war, regardless of its origin. That’s no small task given the size and interconnectedness of the global economy, and the central role of the US within it. Our experience of investing across emerging markets has prepared us to find resilient, growing companies that are operating well outside the line of fire of volatile or heavy-handed governments.

A process grounded in identifying and evaluating resilient companies and assessing their growth prospects feels particularly well suited to the moment.

With the entire non-US stock market as our hunting ground for the International Equity strategy, we face an ample opportunity set as we pursue sound investments. A process grounded in identifying and evaluating resilient companies and assessing their growth prospects feels particularly well suited to the moment. Many industry and societal trends transcend the political aims of any single administration, and there are products and services—indeed, entire economies—that will grow regardless of shifting policy priorities elsewhere. Moreover, due to the sustained fashionableness of US investments in recent years, investors can buy such companies at more modest prices than in many years; market volatility will afford yet more opportunities to invest in them at attractive valuations.

The digital-payments industry is a broad umbrella, comprising everything from consumer services such as digital wallets and peer-to-peer payments to merchant-facing technology that forms the backbone of online shopping, such as merchant acquiring, payment gateways, and payment processing. On the consumer side, digital wallets securely store the same cards found in your physical wallet, while peer-to-peer payment apps such as Venmo are the kind you might use to settle a tab with a friend by wiring them your portion. On the merchant side, a merchant acquirer is an institution that enables retailers to accept credit-card payments. Retailers also need a payment gateway to securely transmit payment information, and a payment processor to authorize and confirm the funds transfer between the cardholder’s issuing bank and the retailer. PayPal is unique because it does all of those things—and nothing else.

Focus is crucial for industries in which consumer habits determine growth. Products and services that become easy routines for people generally see greater usage, resulting in higher revenues; they also have a better chance of holding onto their users even when other good options become available. But for a company to achieve this level of customer loyalty, it must understand its users’ needs and be able to anticipate how those needs might change. The odds of success are likely higher if the product or service is an area of strategic focus. It’s why Spotify, for example, has been able to out-innovate and build a more user-friendly service than Apple Music. Much like music streaming, payments are a small extension of Apple’s core business, while at PayPal, it is the core business. Chief Executive Officer Alex Chriss, who started in late 2023, said at a recent investor presentation that the company is focused on product improvements that should help differentiate PayPal and build habituation among users.

For example, it is applying artificial intelligence to the data it collects from merchants and a shopper’s financial institutions so it can flag which card in their digital wallet would provide the most rewards points or largest discount. PayPal can do this because it is a two-sided network, with both consumers and merchants on its platform. Apple Pay and Google Pay don’t directly partner with merchants or track purchases at the individual product level, so they’re more limited in their ability to offer personalized rewards.

Last year, PayPal also introduced Fastlane, which significantly speeds up the online checkout process by allowing a shopper to skip several steps. No password is needed—Fastlane uses other authentication methods—and the shopper’s billing and shipping information is already securely stored. They can go to their cart and complete the transaction in one click. This is similar to Shopify’s handy Shop Pay functionality. PayPal said in February that 25% of the shoppers using Fastlane were new to PayPal, and more than 50% were PayPal users whose accounts had been inactive.

PayPal is trying to catch up in NFC payments, too. In September, the company began airing a commercial in which Will Ferrell discovers PayPal’s tap-and-go and cash-back features while singing “I want to pay with you everywhere” to the tune of Fleetwood Mac’s “Everywhere.”

L’Oréal also benefited from a subdued competitive environment during the pandemic. Virus-related disruptions resulted in fewer new brands entering the market, and its rivals held off on new product launches. These conditions enabled L’Oréal to increase its sales at 1.7 times the rate of the industry. Now, its growth is settling back to its pre-pandemic level of around 1.2–1.3 times the industry rate.

But global beauty sales are still expected to increase 4.5% this year, compared with a rate of 5% for the years leading up to the pandemic. And L’Oréal is still outpacing the industry—the company’s sales climbed 5.1% in 2024.

Shares of L’Oréal command a sizable premium over other European Consumer Staples stocks, and that gap has widened in recent quarters. For example, Bloomberg data show that L’Oréal’s forward price-to-earnings ratio is more than 50% higher than the average for European staples. Some analysts focused on the European sector thus view L’Oréal’s valuation as relatively expensive and have turned bearish on its stock.

However, that narrow lens is less relevant to a global investor. When you expand an analysis of L’Oréal’s valuation to include US companies, it starts to look more interesting.

For a long time, the average price-to-earnings ratios for US and European Consumer Staples stocks tended to trace each other—until the end of 2023, when their valuations began to diverge. US Consumer Staples are now much more expensive than their European counterparts.

The similarity in the names isn’t a coincidence. That’s because, until 2000, the two Novos were one company. More than two decades after their corporate breakup, their headquarters, some labs, and production plants remain near one another (and both businesses continue to be controlled by a holding company for the Novo Nordisk Foundation).

“Novo” is Latin for new, and that’s what industrial enzymes were in the 1940s, when the original company introduced its first enzymatic products—one used to clean leather hides before they are tanned, and another for textile desizing, in which amylase breaks down starch agents to prepare fabrics for dyeing. The company was also a pioneer in synthetic biology, launching its first enzyme derived from genetically engineered microorganisms in 1987; lipase is still used today in detergents to help remove stains deposited by a greasy burger or pizza, and some of Novonesis’s biggest customers are Procter & Gamble and Unilever.

Enzymes are proteins that act as catalysts to speed up chemical reactions. For example, they are naturally found in the stomach and help break down food into tiny particles that can be converted into energy. In industrial settings, they are used as a substitute for harsh chemicals, which tend to require higher temperatures and pressure to carry out the necessary reactions. The use of enzymes also prevents unwanted reactions, as each type of enzyme binds only to specific molecules, thus leaving behind less waste than traditional chemicals that could give off hazardous byproducts. And industrial enzymes are a good business: While they comprise a small portion of a manufacturer’s overall cost of goods sold, the switching costs can be high, which gives enzyme suppliers pricing power over their customers. This is especially true for Novonesis, given that it is the dominant player in the oligopolistic niche market.

Another source of strength for Novonesis is its research-and-development strategy. The company has historically spent much more on R&D as a percentage of sales than competitors such as DuPont, DSM, and BASF, and that investment has produced a number of important products and thousands of patents over time. In 2024 alone, Novonesis introduced 45 new products, and 30% of its revenue comes from products launched in the past five years.

Novonesis recently acquired its Danish competitor, Chr. Hansen, which supplies bacteria cultures and probiotics used in products such as yogurts. (The US$12.3 billion deal closed last year.) There are product-level advantages to putting the companies together. For example, adding protein to yogurt changes the texture and taste, but Novonesis can now combine products to better address those issues. Management has said it sees similar synergistic opportunities around food preservation for baked goods.

Revenue growth had been bumpy for Novonesis over the past decade, but recently it has gained positive momentum. Pro-forma sales climbed 5% in 2024 (8% when excluding the negative effects of currencies and acquisitions), and the company projects organic sales growth of 5% to 8% this year. The long-term outlook also looks attractive because there remains a significant opportunity for enzymes to displace chemical additives in industrial production processes. The clearest example is detergents, as producers emphasize products that are more water efficient, enable washing machines to run at lower temperatures, and use fewer harsh chemicals. An expanding middle class in emerging markets could also increase the demand for better household-cleaning products.

It’s also at lower US tariff risk than some other European companies, given that Novonesis has R&D and production facilities in the US, and most of its demand there is fulfilled by local production.

It may not be one of the companies shaking up the splashy market for weight-loss solutions, but Novonesis happens to possess a lot of the traits that investors admire about its better-known sibling: cutting-edge research that allows it to succeed in high-growth markets. For Novonesis, that growth strategy is beginning to bear fruit.

Each of these risks have sunk banks in recent years. During the 2008 financial crisis, many banks failed because of credit risk when borrowers defaulted on their mortgages. In 2023, Silicon Valley Bank, Signature Bank, and then First Republic Bank all collapsed when duration risk fears sparked bank runs (to be clear, they were not the only banks with underwater assets, they were the only banks to suffer a run). And liquidity risks often come up when there are already other problems, such as the bank run at Washington Mutual that turned long-term issues into an immediate crisis and the largest bank failure in US history.

Regulators create rules to keep banks and their management teams from taking too much risk, but it is only a partial solution. No amount of regulation can force banks to make only good loans. So, one idea that’s been getting some attention recently is that maybe banks shouldn’t make loans at all. A “narrow bank” would take in deposits and provide payment services but wouldn’t make loans or take credit risk. Instead, it would hold all the cash it brought in as deposits at the central bank or buy short-term government bonds, meaning that there is basically no credit risk. There is almost no duration risk because the assets are short term or even overnight, like the deposits. And there is no liquidity risk because the assets are cash (or as liquid as non-cash assets can be).

To my knowledge, none of the tens of thousands of banks around the world operate this way. In part, that is because the regulators who are supposed to keep the current banking system safe don’t seem to trust the idea. In February 2024, for example, the Fed rejected the application of a bank called The Narrow Bank, which had been trying to secure a banking license for nearly a decade. Indeed, some have even argued that narrow banks actually make the system less secure. Because a narrow bank would be so secure, depositors, during a panic, might move their money away from conventional, risk-taking banks to narrow banks, exacerbating the crisis.

Today, the closest company to a narrow bank anywhere in the world isn’t even a bank. Wise is a financial-services firm with more than 11 million customers that started as an international money transfer service. Wise lets customers leave their money inside of the service as a pseudo deposit, similar to keeping money in Venmo or Cash App. Many customers who travelled frequently or did a lot of international business realized it was more convenient to leave their money with Wise than constantly shift it in and out of local banks. Today, Wise holds about £16 billion in deposits on behalf of its customers, investing the money in government bonds and other low-risk assets (see chart). And in fiscal 2024, it made £360 million in net interest income on those deposits, compared to £1 billion from its main business.

For large depositors, Wise could be safer than a traditional FDIC-insured bank even though it is not one itself. A small business in the US with US$5 million deposited at a bank is insured only up to US$250,000 by the FDIC.

Unlike banks, Wise does not lend out its customers’ money but instead holds it in cash or cash-like, safe assets.

Source: Wise PLC. and Harding Loevner analysis.

The investigation began after Chedraui, the third-largest retail chain in Mexico, accused Walmex of abusing its market power, using its size to coerce suppliers into giving it better prices and terms than they could to competitors, especially smaller ones. A Reuters story amplified the claims of pressuring suppliers, finding that some of those suppliers removed their products from Amazon as a result of Walmex’s pressure. Cofece’s investigation concluded that Walmex abused its position over the course of 13 years and broke anti-monopoly laws in the process.

The common assumption with big retailers such as Walmex is that their power and profits are a result of their scale and ability to lower prices on products that will attract and keep customers. And that is true and well understood. But what is not well understood is how its scale gives the company that power. Retailers don’t make their money on consumers. They make it on suppliers.

There is an intricate game between retailers, suppliers, and customers. Customers have bargaining power with retailers, because they will go wherever prices are the best. Therefore retailers have little bargaining power with their customers—but can have a lot of bargaining power with suppliers. Successful retailers become the conduit to customers and therefore gain an advantage over their suppliers. Retailers use that bargaining power to force terms from suppliers that advantage the retailers, and offset the retailers’ weak bargaining power against fickle buyers. What Cofece concluded was that Walmex was abusing that power.

The Cofece ruling imposed a ban against some of Walmex’s practices, such as retaliating against suppliers based on their contracts with other retailers. That should raise the bargaining power of suppliers against Walmex. The impact, though, is hard to predict. If the ruling stands, it would effectively reduce Walmex’s competitive advantages, which would hurt the bottom line. That won’t be an issue if it wins on appeal, though it will likely be several years for that to play out.

In the meantime, there are two wrinkles. For one thing, Cofece, in its oversight role, will determine whether the company is violating the ruling. For example, the ruling does not appear to ban volume-based discounts. But if Walmex demands a 50% discount from a supplier on, say, 10 million units of an item, will that constitute a violation? For now, only Cofece gets to answer that question. Moreover, the ruling applies specifically and only to Walmex. In effect, Cofece is raising the bargaining power of suppliers…against Walmex only.

That is the real reason Walmex is appealing the ruling rather than just paying the small fine and moving on. Because ultimately what makes a retailer successful is the leverage it holds over its suppliers, not its customers.

Although the techniques employed by DeepSeek are not entirely new, the company’s execution is considered extraordinary for how it significantly reduced training and inference costs. The company reportedly not only used fewer and less-powerful chips but also trained its model in a matter of weeks. There is considerable debate regarding the accuracy of the roughly US$6 million training cost figure that has been reported as well as speculation that DeepSeek may have utilized rival models such as Meta Platforms’ Llama, Alibaba’s Qwen, and OpenAI’s GPT-4 in a process known as distillation to create a student model. Therefore, it may be that the true training cost of DeepSeek’s model is understated.

There is the risk that more efficient AI models may reduce the growth rate of demand for computing power and, in turn, the pace of investment in AI infrastructure. But while investors seem to have equated improved efficiency with a diminished need for AI infrastructure, the history of technology shows that better performance and lower costs typically lead to wider adoption and faster growth over time. AI could follow the same trajectory.

Among the likely beneficiaries of cheaper, more efficient AI are the software providers building applications on top of these models. As more users discover the advantages of AI, increased demand for user-facing software also helps the cloud-services companies that provide the computing power and data storage. However, the commoditization of large language models may negatively affect creators of these models, particularly those that have eschewed open-source technology.

Also, greater computing efficiency may lead to higher volumes of cloud data and thus the need for more data centers and electrical power over time. This would benefit infrastructure providers on the condition that higher demand more than offsets price declines.

The field of AI is still evolving, and further advances in the technology and the methods for developing it are likely. Innovation is always disruptive, but on the whole, DeepSeek’s breakthrough would seem to be a good sign for the industry.

Chinese consumers have, through necessity, become very price conscious. Pingti, which translates literally to “horizontal replacement,” refers to a consumer buying a cheaper product that does the same thing as a more expensive one. Trading down, as we might say in the US. In the language of Porter forces that we use to analyze industry dynamics at Harding Loevner, it is new entrants matching the functionality of incumbents such as Adidas at better prices, leading to a more intense rivalry between companies.

And pingti is easy to do. There are websites, such as 1688.com (part of Alibaba) or Made-in-China.com, originally set up for manufacturers and exporters to do business with their wholesale buyers. Since most of the manufacturer supply chains are in China, it is therefore relatively easy for consumers to find cheaper versions of products from retailers such as Adidas, Li Ning, and others. All a consumer needs do is find an item they like in a store, look at the label to see who manufactured it, and go find the lower-priced, off-brand versions online.

“Customer mindsets have changed considerably in Mainland China in the post-COVID era,” Pan Ning, the chief executive of the Chinese division of Japan’s Uniqlo, said in July. “We are seeing a new set of consumer values centered on pingti.” The trend has been especially sharp among the younger generations, he said. Given its focus on low-priced goods, Uniqlo could also be seen as a beneficiary of the trend, which would help explain why its performance held up better in China than some other retailers.

Adidas has been adapting. The company has been expanding aggressively into lower-tier cities, where it is selling more-affordable versions of its products. It has also, as much as possible, tried to organize its Chinese operation as if it was a local company. The company has teams that are focused on discerning what local buyers want, and building products based on those insights. Once they come up with those ideas, the product designs are approved by the China team, not the home office back in Germany. The efforts appear to be yielding results. Its sales in China rose 9% in the third quarter of 2024, to about US$1 billion, its best quarter since the beginning of 2022.

While pingti was sparked by the economic downturn, it may outlast the eventual recovery. Chinese consumers have become more sophisticated. They no longer view price and brand as the sole markers of quality. Increasingly, they are seeing that lower-cost products can have the same essential quality. A good example of this is the Japanese brand Mont-bell, which has been opening new stores and expanding its presence in China. Mont-bell is a well-known replacement for Arc’teryx, the premium brand owned by Anta.

This dynamic doesn’t have a catchy name in the US, but pingti has been visible here: off-price retail stores operated by TJX such as TJ Maxx and Marshalls saw sales rise after the 2008 financial crisis. Even as the economy recovered after the crisis, those new customers stayed loyal and that outcome may hold in China, too. For that reason, manufacturers and retailers in China may have to account for the trend even after the economy eventually rebounds.

A related metric is the ratio of net property, plant, and equipment (PPE) to gross PPE. A high ratio indicates the outgoing CEO heavily invested in the company’s facilities and equipment. A declining ratio suggests that the outgoing CEO invested little to maintain or upgrade them—or as some might say, management was “sweating the assets.” The latter scenario constrains the next CEO’s ability to implement significant changes. Think of it as the difference between buying a well-maintained house and one needing extensive repairs: The same renovation budget would achieve far more in the well-maintained house, while at the fixer-upper the money would need to be used for necessary but less exciting projects.

Take Intel as an example. Once the leading chip designer and manufacturer, the US company has fallen behind rivals such as NVIDIA and TSMC. Its CEO was pushed out in December, and shareholders are hopeful that his replacement can restore Intel to its prominence. The challenge is that Intel is not easily changeable. Chipmaking is intricate and capital intensive, and the process relies on specialized tools, machinery, and facilities that last for many years. According to its filings, Intel’s manufacturing assets can remain in service for up to eight years, with some facilities lasting over two decades. Despite recent capital investments, the net-to-gross PPE ratio hasn’t dramatically improved, suggesting legacy infrastructure still defines the firm’s capabilities. A quick pivot is tough.

The other question to ask about an incoming CEO is whether change at the company would be a good or bad thing. Generally speaking, change is more welcome for a business that is in a position of weakness, such as Intel, than one that is in a position of strength, such as Schneider Electric. Schneider’s competitive edge in providing electrical solutions continues to be a source of sustained profitable growth, particularly as it sees heightened demand from data-center customers. While the industrials company replaced its CEO in November, investors are unlikely to want drastic changes. Fortunately, with Schneider’s long-lived assets providing operational consistency, the new CEO has limited room—or need—to meaningfully change things.

Consider the potentially very different implications of a new CEO for a company such as Intel compared with a company such as Schneider:

The concept behind autonomous vehicles is simple—cars that are controlled by onboard computers and sensors rather than a human driver—but the technologies behind making them work are far more complex. Autonomous vehicles replace the human driver with a highly advanced system of hardware and software. The most promising ones incorporate a system called LiDAR (Light Detection and Ranging). LiDAR systems flash a laser and record the time it takes that light to hit an object and return to measure distance and the shapes of objects (very similar to radar, which uses radio waves in the same way). A LiDAR system can measure data points down to the centimeter. An AV’s operating system takes the information provided by the LiDAR system to map out the car’s path and then control the steering, acceleration, and braking.

The concept of self-driving cars has been around for a long time. A man named Francis Houdina experimented with a radio-controlled car all the way back in 1925, driving it down New York’s Fifth Avenue. In the 1950s, a famous one-off concept car called the Golden Sahara utilized a rudimentary, LiDAR-like self-driving system. A team at Carnegie Mellon built its first autonomous vehicle, dubbed Navlab, in 1986. Much like humanoid robots, the problem wasn’t the technology but the cost; it was too expensive to be commercially feasible. Recent advances in hardware and software have driven the costs down and given these companies a real chance at making and selling AVs at scale and profitably.

They’re not there quite yet. Israeli company Mobileye has dominated the market for driver-assisted software, but has struggled to sell to auto makers more advanced systems that enable higher levels of autonomous driving. Tesla earlier this year delayed the initial launch of its robotaxis (the company dubbed them “cybercabs”) from July to October, and the October “launch” was just the reveal of a prototype. Production vehicles won’t be available for sale until the first half of 2025 at the earliest (and Elon Musk is notorious for his unmet timelines). Just getting the cars onto the road is not sign of success, either. A Cruise robotaxi hit and dragged a pedestrian in San Francisco last year; subsequently California regulators rescinded the test permit they’d given the company just months earlier. Stories like that highlight what could end up being a material obstacle: regulators who will need to be convinced these cars are safe before they approve any more of them for public roads, or suspend ones that have already been approved.

The AV competition splits pretty cleanly between two kinds of companies, auto and software companies, and in this competition, experience making cars is less important than experience making software. Because the key part of the vehicle is the autonomous operating system, companies such as Baidu and Alphabet are on equal footing with Tesla and GM.

The fact that software companies such as Alphabet and Baidu are already such prominent players in this market proves the point. The ”picks and shovels” of the AV industry won’t be the car makers, we think, it will be the software makers. Whoever builds the best operating system—which means one that can both be completely effective and pass muster with the regulators who will allow it on the roads—will be able to sell it to any auto maker. The car itself will almost become a commodity while the operating system will be the key differentiator. It will be analogous to mobile phones. There are really only two operating systems: Apple’s iOS and Alphabet’s Android. Autonomous vehicles are likely to repeat that development. We imagine the landscape for AV operating systems will end up looking like the landscape for mobile-phone operating systems. Which means this competition is virtually all or nothing, where only one or two companies will end up with the dominant system that everybody else is forced to use.

EV makers are beginning to highlight their use of CATL batteries as a way to differentiate their cars from the competition. Companies such as Zeekr have been advertising their use of CATL batteries, much like PC makers used to do with “Intel Inside” stickers to differentiate themselves in a crowded, intensely competitive market. Like Intel’s chips in the 1990s, CATL’s batteries have consistently pushed the envelope in technological advances, including industry-leading charging speed and density, which enable total ranges of more than 600 miles. These advanced batteries, called Shenxing and Qilin, now account for roughly a third of its EV battery shipments. Earlier this year, CATL started offering special service stations exclusively for owners of cars with the Shenxing batteries.

In August, CATL took that idea—that the battery in your car matters, more than you think—one step further. It opened a showroom in Chengdu, in Sichuan province, displaying nearly 100 models of EVs from 50 different car brands that use CATL batteries. The only major car maker not featured is BYD, a vertically integrated EV maker that has insisted on producing its own batteries, effectively becoming CATL’s main competitor.

As if to illustrate just how important an EV battery really can be, a Mercedes EV caught fire in Incheon, South Korea, just a week before CATL’s showroom launched. Thankfully no one was hurt, but the fire ended up damaging or destroying dozens of cars in an underground garage. After that, Korean regulators started requesting automakers disclose their battery suppliers.

The car in question had a battery from Farasis, a Chinese semi-captive supplier to Mercedes and one of a long tail of unprofitable, substandard rivals to CATL, which has the best safety record in the industry among major makers. CATL sets aside the most reserves for quality/warranty payouts (a conservative accounting approach), yet uses the least amount of those reserves in practice.

Batteries are not as commoditized as many think. These recent events could lead more consumers, and investors, to that conclusion.

Additionally, in September, Sony pulled its shooter game Concord off the market two weeks after it was released, saying the game “didn’t land the way we’d intended.” Like Ubisoft, the Japanese conglomerate issued refunds. There is also speculation that Grand Theft Auto VI, which has long been in development at Take-Two Interactive, may get delayed until 2026—13 years after the previous installment in the series was released.

News such as this tends to restart the debate over whether gaming is just a bad industry for investors. In fact, the industry structure seems challenging. The barriers to entry are somewhat low, and the number of substitutes and competitors—including new entrants in China and South Korea—are both high, factors that generally limit a company’s ability to generate sustainably high profits. But the charts above do not depict such a terrible situation. Rather, there may be some weak players, but there are clearly others that have managed to become more profitable and stable over time.

One way some publishers have done this is by building diversified franchises, which leaves them less prone to revenue lulls and limits the impact that a failed release has on the company’s overall finances. Electronic Arts, for example, has a number of successful franchises, including FIFA, Madden, Apex Legends, and The Sims. Activision Blizzard, in addition to Call of Duty, has World of Warcraft, Candy Crush, and Overwatch, among others—a collection Microsoft found so attractive that it acquired the company for about US$70 billion last year (Microsoft owns Xbox). Other diversified players include Tencent and NetEase, both based in China.

Another way that some in the industry have generated more consistent revenue and profits is through add-on digital content. Twenty years ago, video-game publishers were essentially consumer-goods companies. Their games were a physical product, and manufacturing, shipping, and selling these discs carried a significant cost. Playing them was also a one-off experience. Digital technology changed all this, with players increasingly downloading games rather than purchasing new or used discs. This has allowed game developers and publishers to boost the revenue generated by a game after it’s released by offering so-called expansion packs for online purchase, as well as virtual cosmetics to enhance a player’s avatar and virtual currencies. For example, Call of Duty: Black Ops 6 was released October 25, but you can almost guarantee that at some point, perhaps in six months or so, an expansion pack with additional content will become available. Extending the useful life of each game in this way relieves the pressure on developers to quickly crank out the next one. In the second quarter of 2023, Activision Blizzard’s last earnings report before its sale to Microsoft was completed, the company said that downloadable content and micro-transactions accounted for 63% of its net bookings.

The industry’s earnings consistency also has to do with the other types of companies involved in gaming: console makers, such as Microsoft and Sony, as well as businesses that sell tools and services to developers and publishers. One example is Keywords Studios, a provider of game-ready art and quality-assurance testing. Gaming platforms and toolmakers capture a portion of the industry’s revenues, which means they benefit from the overall growth without taking on the risk of any single game.

The recent challenges at Ubisoft and other companies reflect two industry trends that are worth watching. One is that game development has slowed. It’s unclear whether this is due to increased remote work, developers missing deadlines because they’re trying pack more interactive features into a game, pushback against the industry’s overtime habits, or perhaps all the above. In any case, these would seem to be temporary challenges.

Another is that some gamers seem to be spending less money on the hobby, which describes a change in user habits that could be more permanent. However, there’s not enough data to know if that’s the case. Instead, what we can gather from 30 years of financial data is that some gaming companies are built to ride out the rough patches, and so it would be a mistake for investors to write off the whole industry.

The government is focused on a “new development model” agenda that aims for a cumulative annual growth rate in income-per-capita of 6% through 2035. It plans to spend about US$100 billion between now and 2030 on infrastructure, covering everything from improving irrigation to reducing carbon emissions to rebuilding housing after last year’s earthquake.

Over the past two decades, Morocco has achieved remarkable macroeconomic stability compared to other frontier markets, a result of prudent monetary and fiscal policies. The country has more than 1,100 miles of highways, one of the largest container ports in Africa, Tanger Med, and the first high-speed trains in Africa. The kingdom spends 5.5% of GDP on education, and is turning out 24,000 engineers annually from its nearly 200 technology-focused universities and institutes. The country also offers investment incentives to industries such as autos and pharmaceuticals, and has established free-trade agreements with more than 50 partners.

Morocco has been consciously trying to shift its economy away from more volatile sectors such as agriculture via a deliberate industrialization strategy that’s resulted in a more diversified economy. Sectors such as automotive and aeronautics have been growing at a faster rate than traditional sectors. As a result, the contribution of those traditional sectors to total exports has fallen from 44% in 2010 to 25% in 2023.

By the time the soccer World Cup arrives in 2030—the country is co-hosting alongside Spain and Portugal—Morocco expects to show off a vibrant, growing country that will attract both tourists and foreign investors and can be a lasting bridge between Africa and Europe.

Markets recovered quickly, though, and Japan ended the quarter as the second-best performing region for small-cap stocks. As the chart above shows, the yen also topped currency returns.

For several quarters, Japan has been a particularly challenging market for investors in quality growth small companies, as stocks of cheaper, low-quality businesses tended to outperform. However, another market development in Japan in the third quarter was that style patterns reversed, with stocks of faster-growing, more expensive companies leading returns. The charts below depict the spread between returns for the fastest- and slowest-growing, highest- and lowest-quality, and least and most expensive small caps by region for both the third quarter and trailing 12 months, based on Harding Loevner’s proprietary growth, quality, and value quintiles.

Of course, there are cases when stock price momentum is linked to company fundamentals. Apple is an example where a profound and structural change is harnessed by a company over a long period, leading to sustained profit growth and extended share price appreciation. Such dynamics are possibly at play in the recent fever for companies linked to the development of artificial intelligence or weight-loss drugs. But such cases are rare and most of the time investors tend to overestimate the number of transformative changes that will actually materialize.

Momentum in the markets is often driven less by fundamentals and more by the fear of missing out (FOMO). In our experience, the FOMO response is most acute when it’s most dangerous—near the peak of market trends, or worse, an investment bubble. Investors who hold the winning stocks are happy to hold on, while those who don’t quickly feel the pressure of “missing out,” amplified by the constant media coverage that acts as free advertising for these market leaders. Passive investors inadvertently pour more capital into these heavyweight stocks in ever-increasing percentages, further amplifying their impact. As a result, the momentum behind these stocks grows ever stronger, and they come to dominate index returns. All (human) investors who measure themselves against a benchmark index feel drawn to jump on the bandwagon. We suspect that FOMO has been a significant element contributing to some of the most damaging drawdowns in the performance record of momentum investing, and we expect it will likely feature in some doozies to come.

We are well aware of the behavioral pitfalls in investing and use a variety of tools to promote objectivity in decision-making. But we can be just as susceptible as other investors to the temptations of momentum. To stiffen our resolve, we’ve made pre-commitments in the form of absolute limits in our risk guidelines, which are primarily aimed at enforcing diversification in our portfolios, but secondarily act as brakes to curb our enthusiasm.

For international quality growth investors, the hope, of course, was that resurgent performance for US growth stocks would herald a similar trend elsewhere. Although this has yet to be the case, the variability in the performance of growth stocks in recent months may suggest a reversal in style trends is approaching. For example, the return spread between international value stocks and international growth stocks does appear to be flattening.

There is also reason to question the underpinnings of a rally characterized by companies with weak profits. In many cases, the catalysts for the rise in their shares have been speculative or one-off developments, such as the announcement of share buybacks, a short-lived valuation opportunity, or takeover chatter. A clear example is the broad rotation toward stocks of low-quality, cyclical companies in Japan on anticipation that a flurry of reforms may, eventually, improve corporate governance and shareholder returns in the country.

The idea that highly profitable, growing companies outside the US will continue to perform the way they have over the last three and a half years isn’t supported by their earnings outlook. Therefore, a rotation back into growth may not be far off in the future.

Daifuku, based in Japan, is a leading provider of cleanroom-automation solutions such as the monorail described above, which TSMC, Samsung, Intel, and others depend on to keep chip production on track. Each monorail extends 10 kilometers (6.2 miles) and is equipped with about 1,000 autonomous vehicles, called front opening unified pods (FOUPs). Typically, multiple cleanrooms operate together, with several monorail systems connected to one another. Each FOUP can travel 200 meters (656 feet) per minute. This speed is important because the photoresist light-sensitive polymers will degrade if the process takes too long. Dynamic routing, or the ability of the FOUPs to find the best path depending on the wafer’s condition while avoiding collision with other vehicles, is one of Daifuku’s key competitive strengths.

Because the company has only one significant rival, Murata Machinery, Daifuku enjoys strong bargaining power over buyers. (Samsung has a subsidiary that also does some of this work, but exclusively for its parent company.) And although the broader cleanroom-automation market is largely split between Daifuku and Murata, fabrication facilities, or fabs, working on the most cutting-edge technology—chips with features two and three nanometers small that are highly sensitive to contamination and degradation and require more precision—primarily turn to Daifuku. To create smaller transistors and other components, fabs not only must limit airborne and aerosol particles but also minimize machine vibrations and have other critical environmental controls. Daifuku is distinguished by its ability to engineer large, sophisticated projects such as these. Rather than focus on manufacturing all the disparate parts that go into an automation system, the company’s core competency is designing ways for various solutions to work together to address each customer’s increasingly complex needs.

Cleanroom automation isn’t Daifuku’s only business, although it may soon be its biggest. For much of the company’s 87-year history, its largest source of revenue has been factory and warehouse conveyor systems, including those used today by Amazon.com, Home Depot, and Walmart to swiftly transport boxes around facilities that can span several football fields. Its elevator-like systems of storage racks can also organize and retrieve crates stacked multiple stories high (a common setup in Asia, where land is limited, and warehouses tend to be tall rather than wide). Daifuku’s systems are also used in automotive plants to hoist cars through assembly lines, and in airports to move baggage.

Given the strength of its main businesses, and the increasing interest among companies, consumers, and regulators for more recycled material in products, TOMRA seemed primed for profitable growth as the go-to equipment supplier in this “circular economy.” From 2017 through 2021, the company compounded its earnings at a 13% rate. At a capital markets day in 2022 it promised more of the same—to boost revenues 15% per year while expanding margins.

But since that capital markets day, which coincided with turnover in the executive team, the company’s execution has faltered. Earnings this year are expected to be lower than they were three years ago. TOMRA was hurt by inflation, as existing contracts prevented the company from increasing prices to offset rising costs. The company was also the victim of a severe cyberattack, which cost US$20 million to remediate. In the food division, the company had to undergo a drastic restructuring after a series of acquisitions led to a disjointed operation.

World-class industrial businesses often have an ethos that focuses their work force and strategy on what’s most important—think Danaher’s famous Danaher Business System, Parker Hannifin’s Win Strategy, or Honeywell’s Accelerator program. The companies attribute their historical success to these systems because they focus decision makers on organic growth, profitability, and return on invested capital. We’d like to see TOMRA’s management take a similar approach and pay more attention to concrete financial metrics as opposed to buzzwords like “circular economy” or “food security.” Talking about cash-flow return on investment and other hard numbers with investors often encourages a more dedicated focus on them.

In the first quarter of this year, two of TOMRA’s three divisions lost money, yet on its earnings call with investors, the management team hardly referenced the dismal results. In fact, in the opening 30 minutes of the one-hour call, the CEO made scant reference to TOMRA’s lackluster financial results. The second-quarter results showed some promise; revenue for its reverse-vending machines rose 15%, an encouraging sign. Earnings, however, for the first six months fell from 2023’s levels.

While TOMRA has endured a challenging period, it still has a dominant position in a growing market, and some mid- to long-term drivers of growth are still intact. Jurisdictions from Quebec to Tasmania are planning to launch deposit programs this year and next, albeit others are rethinking plans; France for instance cancelled a planned bottle-recycling program. But Austria, Poland, Hungary, and Romania have also emerged as new markets. Additionally, the technology the company has developed for sorting recyclables can be leveraged for other uses; the company expanded into metal recycling in 2006 and mining in 2008 as well as food sorting.

The company says its machines collect more than 46 billion used beverage containers every year, and that collection rates in markets with deposit programs are higher than those with curbside-collection plans. TOMRA has managed to boost revenues steadily over the past decade, which points to a degree of stability. The new management’s missteps combined with the changing interest-rate environment and countries altering recycling plans have sown doubt. There is still a business and environmental case to be made for TOMRA. What we’re looking for are signs that the new management team is balancing those two things more effectively.

Another significant difference, particularly in soccer, is that the frequency with which players are traded is much greater than that in most American sports. Trading of players (technically, of their contracts) takes place in two transfer windows, a long one that starts before the season begins and stays open until the season is a month old, and a short one in the middle of the season—the month of January.

Players are, of course, any club’s biggest asset, and once assets start being traded, any investment person will wonder what determines the price of those assets and how that market price relates to “true” value of the asset.

In investing, practitioners have a model that claims the value of an asset is the value of the cash flows it generates in the future, discounted back to a present value using a discount rate that is the sum of a risk-free interest rate and an equity risk premium. We all accept that the model is imperfect, but investors such as us believe that prices are more volatile than values and that they converge on value over some indeterminate time frame. Over short periods prices are set by the preponderance of buyers and sellers, but eventually, underlying values dominate prices. As Ben Graham observed, “In the short run, the market is a voting machine but in the long run, it is a weighing machine.”

There is no such model that underlies prices in the market for soccer players (and I apologize to all players for considering them only as tradeable assets in this piece. They are, of course, human beings and, unlike stocks that are indifferent to ownership, have preferences about where and for whom they play). The result is that prices for soccer players are driven by the quantity of money available in the industry and often appear to have little basis in the value that is created by that player on the field (or pitch). Buyers have been attracted to rising prices for soccer clubs and more money has entered the industry in recent years, leading to a rapid increase in the price for an average player.

Prices for clubs similarly appear unrelated to their value. The discounted present value of cash flows generated by clubs in the division in which my club plays is strongly negative, with the average club losing over £25 million a year, sometimes on revenues that are less than the losses. Owners should pay to have these liabilities taken off their hands. (I hasten to add that my club operates on a cash flow breakeven basis, but still doesn’t generate cash flows that could accrue to its shareholders).

Instead, prices of clubs and players are determined, as is often the case in the real estate market, by “comparables”—buyers and sellers look at prices of similar assets and negotiate based on that. In an industry where money has been available in increasing amounts, but the numbers of clubs and players roughly fixed, that has led, unsurprisingly, to price inflation.

At my club Plymouth Argyle, we have embarked on a strategy to try to generate returns from player trading. We allocated some funds last year to buy players with the intention that they would increase in price and then be sold, generating profits to be reinvested or used to pay higher wages for more skillful players—establishing a portfolio of players, if you will. As part of that effort, we have thought about a model to determine value in the absence of associated cash flows. We could, for example, say that promotion to a higher division would increase the club’s revenues by £x million, and that an individual player could increase the probability of capturing those revenues by y%. That is possible, if not easy, and enables us to put an expected value on an individual player. The trouble is that the resulting number bears little relation to the actual market prices for players, coming up with a value that’s significantly less than actual market prices! We could also accept that the market for clubs is what it is, and that prices for clubs rise as they ascend the league’s divisions so base the expected value for a player on the contribution he makes to the probability of promotion and the value of that promotion, or to avoiding relegation. Again, this is not a true anchor in value, simply in prices for clubs.

This is, of course, quite different from investing in stocks, where, as I’ve pointed out, prices, in the long run, are determined by underlying value.

But how firm is that underpinning? Is it really so much more objective and calculable than the trading of sports stars? Investment professionals, and finance academics, like to talk about the “intrinsic value” of a stock, once the analysis has been done, the forecasts made, and the discount rate applied.

But is there really an intrinsic value that is separate from the preferences of the valuer? As my colleague Andrew West has written, “Valuation is always an estimate, and valuation always requires a valuer.”

The forecasts that analysts make of cash flows far into the future reflect subjective views about that future—not just about management’s ability to control costs, impose higher prices, gain market share or invest retained earnings successfully, but also about competitive positions in the industry in which the company operates and the industry’s competitive structure and growth rates. And all that occurs before the analyst considers the economic environment in which the company operates.

The choice of discount rates presents further opportunities for subjectivity. The risk-free rate is observable in the US Treasury market (though which Treasury should be used to approximate rates in the future is debatable) but the equity risk premium is highly contentious and perhaps is best described in terms of individual risk and return preferences and needs. In my career I’ve heard perfectly sensible people argue that the equity risk premium should be zero, and others argue that it should be 600 basis points.

Value is in the eye of the beholder and an estimate of true value is closer to an estimate of what the market is prepared to pay than fundamental investors such as us like to admit. In thinking about stock portfolios, as in thinking about the value of a squad of footballers, we cannot ignore what the market is prepared to pay when thinking about portfolio construction and even about long-term returns.

Markets such as Egypt and Nigeria have indeed faced challenges with repatriation due to unsustainable currency pegs, which both countries abandoned earlier this year. Since then, Nigeria was eliminated from the benchmark by index provider MSCI in February. Also, Egypt has attracted US$35 billion from a consortium led by Abu Dhabi’s ADQ investment company and an additional US$5 billion from the IMF, easing liquidity pressure there.

We also note that BlackRock shuttered its fund as the FEM Index has actually become more balanced. From 2023 through the first half of 2024, MSCI added about 125 stocks to the MSCI FEM Index, resulting in lower country concentration for the benchmark. The Philippines, once the largest market with more than 30% weight, is now 20%.

This is underscored when we look at the valuation across sectors. Current valuations are at the extreme point of the five-year range in all sectors, with the sole exception of Financials.

Outside of Japan, there didn’t appear to be strongly defined style patterns. The heatmap above shows that there weren’t consistent headwinds or tailwinds when examining performance by measures of quality, growth, and value. There did, however, appear to be a style divergence between regions.

In the Eurozone, the fastest-growing stocks performed in line with the slowest-growing stocks. In emerging markets, the concentration effect of heavyweight stocks, including TSMC and Tencent, flattered the returns of the highest-quality, fastest-growing cohorts, even while cheaper stocks outperformed. In Asian markets excluding Japan, the most expensive stocks only modestly outperformed the least expensive this past quarter.

Perhaps because consumers in the US and elsewhere are accustomed to seeing “made in China” tags on their clothing, there is a misconception that China was always the domain of fast fashion—cheap, rapidly produced apparel that mimics catwalk trends. Traditionally, though, production and shipping lead times were longer in China, making it a more suitable supplier for brands such as Nike than retailers trying to quickly recreate viral looks. Leading fast-fashion retailers such as Inditex, the Spanish parent of Zara, and the British e-ecommerce site ASOS source only about 30% to 40% of their merchandise from China and often turn to countries such as Spain, Portugal, Morocco, and Turkey for styles requiring a quicker turnaround.

Shein and Temu, however, mostly rely on Chinese suppliers, and they’re able to offer low prices in part because of the method they use to get their products from those suppliers to shoppers. By shipping individual orders directly to customers, they avoid US import duties, which are waived if a shipment’s value is less than US$800. US lawmakers have called this an unfair advantage over American retailers, many of which do pay import duties to bring in inventory made overseas. Duties, particularly in countries with high duties, can be a meaningful component of costs, although their avoidance isn’t the only reason Shein and Temu can offer low prices. Another is the efficiency of their supply chains and logistics operations.

But while these relative newcomers have been popular with some consumers, there doesn’t appear to be much risk to high-quality retail companies. One reason is that the retail market pie is so large, which means the rivalry dynamics are such that many different strategies can succeed at the same time. For example, even after getting off to a gangbuster start in the US, Temu’s gross merchandise value represents just 1% of the US e-commerce market, putting it significantly behind Amazon at 38% and even Walmart at 6%. Its customer retention rate is also lower, suggesting that some shoppers may be drawn to the novelty of scoring a deal but aren’t becoming repeat customers. The Sensor Tower data below shows the proportion of Apple iPhone users who open the Temu app at least once a month after downloading and how that compares to other retail apps; the large drop-off in Temu visitors is true among Android users as well:

Tinubu had success turning around the economy in Lagos as its governor, and he wasted no time in tackling the country’s sclerotic economy. On the day of his inauguration, he abruptly ended a decades-old subsidy paid to oil companies to keep fuel prices low that cost the government US$10 billion a year, more than it spent on education or health care. He reorganized the county’s foreign-exchange system and abandoned the naira’s currency peg—it has fallen about 70% against the dollar since—and took other steps geared toward improving the economy and boosting tax revenue.

Since ending the subsidy, the price of oil (which is a strong source of revenue in Nigeria) has stabilized and credit-quality issues that plagued the energy sector have improved. Credit trends, for now at least, are stable. Two currency devaluations have removed a lot of the concerns about the previous monetary regime. So far, the reforms seem to be well received by outside observers. In early May, the ratings agency Fitch upgraded the country’s outlook to positive from stable, based on the initial success of Tinubu’s reform package.

There is good reason for investors to pay attention. Nigeria’s demographics are compelling: it has the sixth-largest global population, one that is young and fast-growing. Demographic tailwinds can be powerful over longer periods of time as penetration of banking and insurance services naturally expand as countries develop. Even amid the travails of recent years the country’s high-quality banks have fared well. Zenith and Guaranty Trust consistently post a return on assets north of 3%, compared to the more typical 1-2% earned by most banks around the globe.

Recent earnings might seem to indicate the hoped-for inflection point has arrived, and investors may also be enticed by the fact that Zenith and Guaranty Trust trade well below book value. But the earnings are somewhat misleading since both banks posted large and unsustainable hedging gains due to the naira devaluation. Nevertheless, their operating performance demonstrates their relative stability amid the volatility induced by the reform package.

A larger argument against the idea that an inflection point’s been reached is the reality that unwinding the mistakes of the past 8 to 10 years is going to be extremely difficult. Tinubu’s reforms, while necessary, have caused lots of pain and economic hardship. The currency devaluation feeds straight into inflation, which is running north of 30%. That, combined with the removal of the fuel subsidy and later an electricity subsidy as well, was too hard a pill for the majority of the mostly poor population to swallow. It seems likely that the next couple of years will be rocky and there may be credit-quality issues for the banks since credit stresses typically lag economic shocks.

Whatever the short-term pain, though, we do believe that the long-term picture is still positive, which is why we remain resolutely interested in Nigerian companies, not just the banks. The policy changes this new government has made will hopefully put the economy on a better growth trajectory and make the society more prosperous. In fact, we’d go so far as to say that Nigeria is lucky to have elected President Tinubu at this critical time. He appears to be the right man to have taken over the country given its precarious economic state. After his success in Lagos, it’s reasonable to have hope for his administration’s ability to turn the country around. But the path to better days ahead will likely be turbulent.

Fast fashion has become a roughly US$120 billion industry and is projected to grow to US$185 billion by 2027. Shein, H&M, Temu, Zara, and others have built worldwide businesses by creating cheap clothing in bulk as quickly as possible to respond to changing fashion trends, especially for a growing global middle class with more disposable income. The crux of the problem is that fast fashion tends to encourage what many consider an excessive amount of consumption. Traditional clothing companies might release new lines four times a year; fast-fashion companies do so weekly or even daily. The clothes are designed to be relatively cheap and worn for a short period of time before being discarded, sometimes after only seven or eight wears. Consumers are then expected to buy the next hot thing. The result? People are buying more clothes, an estimated 60% more, but keeping them only half as long as they would a more durable, higher-quality piece of clothing.

Those dynamics exacerbate the environmental impacts of an industry that is inherently polluting to begin with. Conventional textile mills generate about one-fifth of the world’s industrial water pollution. About 20-35% of all the microplastics in the world’s oceans come from microfibers shed by clothes as they are washed. The industry also produces veritable mountains of unsold clothing, which get burned or thrown into landfills strewn around the Global South. (Shein, for one, has argued that its business model better matches supply with demand and produces less unsold clothing).

Among factors, perhaps the biggest puzzle, however, is what lies behind the excess returns that have accrued to companies with strong balance sheets, consistent profitability, and operational excellence, typically referred to as the quality factor. Investors should be willing to pay up for such enviable characteristics, and they do, but not as much as they should and therein lies the puzzle. Narratives about risk can shed light on the performance of value stocks, and the idea of slow-spreading information can account for momentum, but what exactly is behind the outperformance of high-quality stocks remains elusive.

For behavioralists, often mistakenly criticized as viewing every market inefficiency as proof of human imperfection, the quality factor is a reflection of rational, yet imperfect, heuristics that sometimes lead to less-than-optimal outcomes. For strictly orthodox economists who hold fast to the notion of a perfectly rational human agent, every excess return must be a manifestation of some as yet unrecognized risk. And a more unconventional viewpoint turns the traditional understanding of the quality factor on its head, suggesting instead that what we’re observing is not a premium for high quality so much as discount applied to everything else.

Costco’s results for the quarter were healthy, but they also contained signs that industry dynamics are beginning to shift. For example, given that overall inflation was flat across the retailer’s product categories, growth in same-store sales was dependent on increased customer traffic.

At Harding Loevner, we believe that whether a business thrives largely depends on the competitive structure of its industry, which we evaluate using Michael Porter’s Five Forces framework. NVIDIA has an estimated 95% share of the market for AI chips. Its graphics processing units (GPUs), which were originally used to power video games, have been adapted to become the key engine of AI computation. The customer base for these chips is highly concentrated and primarily consists of “hyperscalers”—companies such as Alphabet, Amazon.com, Meta, and Microsoft that operate large networks of data centers with immense computing power and storage needs. More than half of NVIDIA’s data-center revenue for its fiscal quarter that ended in January came from large cloud-services providers, and one company alone accounted for 19% of last year’s total company revenue.

From the Porter perspective, a key factor in the bargaining power of buyers is their ability to backward integrate. All of the aforementioned customers have this capability, which threatens to diminish their reliance on NVIDIA. In our view, it’s only a matter of time before this manifests. In fact, Amazon, Google, and Microsoft each have unveiled custom data-center chips as potential substitutes for NVIDIA’s general-purpose GPUs. Because each server in a data center performs only a few specific functions that are repeated over and over, these custom chips, called application-specific integrated circuits (ASICs), are tailored to just the tasks the companies need them to perform.

Industry rivalry is also likely to increase. As the frenzied pace of spending on AI infrastructure eventually eases, companies will begin to look for less expensive options from new suppliers, which may include NVIDIA’s own customers.

NVIDIA is a high-quality company led by skillful managers. Its revenue more than doubled over the past fiscal year, and net profit rose fivefold. But the high potential for increased rivalry and backward integration among key customers suggest that it is unlikely NVIDIA can continue growing at these rates with these margins while maintaining its grip on 95% of the AI-chip market. The fragility of its competitive structure limits our valuation tolerance, which is why we exited the stock in the first quarter after holding it for more than five years.

While it is possible that NVIDIA will continue to exceed increasingly aggressive consensus earnings forecasts for some time, we own other more attractively priced businesses that allow us to invest in AI’s potential. For example, Microsoft and other providers of software and services have the advantage of being able to monetize generative-AI technology without regard for whose GPUs or ASICs are used in the future. Microsoft’s customers also don’t appear to have the ability or interest to try to backward integrate; in fact, AI functionality such as its Copilot chatbot are helping to lock in users. In general, as the applications for AI evolve, value is likely to shift from hardware, such as NVIDIA’s GPUs, to the software and services built upon this infrastructure.

Read more about our software and services holdings in the first quarter Global Equity report.

While US chip designer NVIDIA gets most of the AI press, TSMC manufactures virtually all of the high-performance AI chips designed by NVIDIA. The Taiwan-based company uses some of its most sophisticated manufacturing technologies for these chips, enabling them to be at the forefront of transistor density, speed, and energy efficiency. AI chip customers also increasingly depend on TSMC’s innovative capabilities in integrating and packaging the logic, memory, and input/output components involved. TSMC’s CEO recently projected that in four years about 20% of this company’s total revenue would come from AI-specific chips.

Samsung Electronics has received less attention from investors but is also carving out a niche for itself in AI-related semiconductor manufacturing. Samsung anticipates a rebound in their memory chip prices in 2024, in part due to the expected proliferation of on-device AI, a memory-hungry implementation, and is investing for longer term in the next generation of high-bandwidth memory chips integral to AI applications, promising to leapfrog competitors in performance. Samsung Electronics is also positioning itself to compete with TSMC in manufacturing advanced logic chips, using its capability of designing and manufacturing memory, logic, and chip packaging to unlock new opportunities for its foundry business.

Infineon, widely recognized for its strength in automotive and power semiconductors, is less directly exposed to AI themes but does have products supporting growth data centers and AI computing whose high-power demands is a good match for Infineon’s switched mode power supplies and voltage regulator designs that power high performance systems.

During 2023, Amazon overhauled the sprawling US logistics network that supports its online-retail operations, switching from a national system for filling and routing orders to a regional setup. The core change was to partition the US into eight main regions, assigning each region dedicated fulfillment warehouses, sorting centers, last-mile delivery hubs, and vehicles. By limiting the area each facility serves, the company doesn’t need as many connecting points along its distribution routes, and trucks are filled closer to their capacity and travel shorter distances. This helps Amazon save money on fuel, fleet upkeep, labor, and other overhead, as well as potentially reduce its environmental impact.

Amazon’s latest financial report in February revealed that fulfillment costs, which had soared to 16.4% of net sales in 2022, shrank to 15.8% of net sales in 2023 as the new system was implemented. As the chart below shows, it was only the second time in 14 years that this metric’s long ascension was interrupted. This time, we view it as an inflection point, and so the downward trend should continue.

Given the opaque relationship between the Chinese government and private companies, the exact terms of the exchange are unknown; Baidu’s move could result in the US putting the company on the restricted list that blocks US investments in companies that could be supporting China’s military. However, there is a plausible market-based reason for the donation: the quantum computer was expensive to build and maintain and the effort wasn’t profitable.

At a meeting with analysts in January, Baidu’s chief financial officer, Rong Luo, explained that the kind of “moonshot research” the quantum computer represented was too expensive and didn’t add to the company’s bottom line. Donating it helped cut costs and foster goodwill with the government. It was the kind of pragmatic move that the company had gotten away from in recent years.

Like their global peers, Chinese internet companies enjoyed years of growth and strong cash flows. That allowed them to expand beyond their core operations to invest in new business formats and technologies, such as Alibaba in offline retail and Tencent in fintech. They usually focused on creating scale even if the business itself was initially unprofitable. That goal depressed margins in the sector. But as growth has slowed, Baidu, Alibaba, Tencent, Netease, and other Chinese tech companies have been refocusing their operations on turning a profit.

At Baidu, this included bringing in Luo, who has a PhD in management science from Peking University and had been the CFO at TAL Education Group. During his tenure there, Luo played an important role in TAL’s transformation from operation-driven to data- and technology-driven, and from offline to online.

When Luo arrived at Baidu two years ago, some senior management didn’t recognize the importance of return-focused performance metrics. That has changed. Expenses have been cut. Research and development spending as a percentage of sales, which had been about 20% (and more than its peers), has been reduced. The company was making investments in innovative technologies, such as quantum computing, but there wasn’t likely to be a return on these investments in the foreseeable future. The effectiveness of projects is now measured on the return on investment and efficiency. Thus, the decision to give away the computer.

Now the company is focused on the parts of its business that are or can be profitable: its core ad business, cloud computing, and AI. In the highly competitive business of search, Baidu released an AI-based advertising platform called QingGe. The new platform essentially examines a users’ interactions with a chatbot and generates a new ad specifically tailored to them. The goal is to create a better advertising platform, with the goal of improving the click-through rate by 10x. Hitting that goal would add several billion in incremental RMB in 2024, the company said.

That’s one example of how management is employing AI, a crucial test. In 2017, Baidu was the leader among its peers in AI. It had Andrew Ng, the former head of Google Brain, as its chief scientist and signaled its intentions with its slogan “All in AI.” But Ng left the company in 2017.

Despite his departure, Baidu was the first among Chinese companies to launch a chatbot in 2019, shortly after OpenAI released ChatGPT. That chatbot, called Ernie, is not as advanced as ChatGPT 4.0 but is more advanced than its Chinese peers and many Chinese companies are using it to train their own more specialized models. In December, Baidu reported Ernie had more than 100 million users.

Even with a technological lead over its peers, Baidu hasn’t yet shown it can make AI a profit center the way some US-based companies have. It is testing monetization models, such as a subscription service, and fusing it into its search business, but neither investors nor Baidu itself can be certain how the AI efforts will affect the company’s profits (the company does not provide revenue projections for its AI business). What investors do know is that the company’s criteria for the success of that effort and everything else it does will be measured on the bottom line.

The charts below illustrate how variable those characteristics are. The bubbles represent the roughly 2,700 stocks that were in the MSCI All Country World Index (ACWI) at the end of 2018. In the tab for 2018, they’re split down the middle such that the top half of stocks (the orange portion) were considered high quality, based on their Harding Loevner quality scores at the time. But over the next five years, the characteristics of the companies changed. Now click the tab for 2023. It shows that only 25% of index members were also above the threshold that was set in 2018.

• 2018
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One might expect that a decrease in the number of babies would be a major problem for a company like Unicharm, which dominates the Japanese market for disposable diapers. But by taking advantage of other demographic trends that have opened new markets for the company, Unicharm has seen its overall business grow, even as its core market shrinks.

Unicharm was founded in 1961 as an insulation and building materials supplier and later began manufacturing feminine sanitary pads. In the following decades, Unicharm relied on its expertise in processing non-woven fabrics and absorbent materials made from petroleum-based polymers to expand into other markets beyond feminine care, especially diapers.

Unicharm grew to dominate the market for baby diapers in Japan, with an estimated 41% retail market share in 2023. But the product segment has become a challenging, low-margin business, partly because consumers have not been swayed to pay a premium for baby diapers with special features, and the decreasing number of babies being born has meant that Unicharm is fighting for its portion of a shrinking pie. Meanwhile in neighboring China, once a key market for the company’s baby diapers, stiff competition from local manufacturers has driven down retail prices.

While Unicharm says it will continue to make baby diapers, because of the positive and happy associations consumers attach to baby products, the company has increasingly focused on market segments that offer higher margins (if not the same positive feelings) such as adult incontinence products.

Japan now has the highest proportion of elderly citizens of any country in the world. About 29% of Japanese are over age 65, while more than 10% are 80 or older. As the population has gotten older, Unicharm’s adult products have become a larger part of its business. Adult diapers constitute about 33% of the company’s net sales in Japan today, up from an estimated 25% in 2018. Overall, the company derived one-third of its sales and 40% of its profits from Japan last year.

Adult incontinence products are a high-margin business because consumers are willing to pay a premium for products with special features, such as improved fit to prevent leakage. Furthermore, the company’s marketing campaigns have been successful at creating demand for its light and mini-incontinence pads by associating them with an active lifestyle.

The sort of quality companies that we look to invest in have, among other characteristics, strong management teams who can respond to changing market and industry dynamics. Unicharm’s ability to leverage its core competency in absorbent materials in different markets is an example of how managing change can help a business thrive over time. And Unicharm might even find a way to help address Japan’s aging demographics—it’s recently introduced a new feminine hygiene product that monitors ovulation to help women plan their pregnancies.

It’s an expansive deal, beginning in January 2025 and running for ten years. Netflix will air Raw in the US and internationally, and will have the rights to all WWE shows outside the US. It also may be a harbinger of what’s to come in the world of streaming services and sports. Over the next several years, the contracts for broadcast rights to the NBA, NFL, NHL, and MLB in the US will come up for renewal, as well as the domestic and US rights to top soccer leagues such as the Premier League (UK), La Liga (Spain), Seria A (Italy) and Bundesliga (Germany). The streaming services will be serious contenders in the bidding for all of them.

Netflix has previously declined to jump into sports. “We’re not anti-sports, we’re pro-profits,” co-CEO Ted Sarandos said last year. Making a major foray into sports, even if it’s a scripted one, may be a signal that Netflix is seeing—or at least planning for—a ceiling in terms of how many new subscribers it can attract without sports.

The biggest problem with sports programming is that while it does the things a broadcaster wants it to—steadily bring in dedicated viewers—over time the rights can become addictive for companies. If a sport increases in popularity, that improves profitability and hopefully leads to good returns on the investment for the rights holder. However, those attractive returns also lead to a higher renewal contract, which resets profitability at a lower level even when competitive dynamics are benign.

The problem for Netflix is that the sports-rights competition is not benign. Netflix will be competing with Paramount, Peacock, and Disney, as well as big-tech companies that have completely different strategic goals. For tech companies like Amazon and Apple, for example, “success” in terms of sports programming is more about e-commerce or hardware sales than subscriber profitability.

Netflix has spent roughly US$17 billion a year on content since 2021, a level it plans to maintain for the foreseeable future. The company said that the WWE deal would not add to its content budget, meaning it expects to spend less elsewhere. On one level, then, this is not an expensive bet. WWE already has a fanatical global audience and NBC is paying nearly US$300 million annually just for the US rights. Maybe US$500 million a year for global rights is a bargain.

Given Netflix doesn’t have any legacy networks to protect like some of its competitors do, it sidesteps a lot of the messy problems in the industry. But Netflix has its own set of pressures with which to contend. In 2023, Netflix’s subscriber base rose to 260 million, which was a record. Its growth rate, however, is slowing. In the past two years, the subscriber base is up 17%. In the two years prior to that, it rose 33%. Netflix used to be valued and treated like a tech stock. These days it is valued and treated more like a media company.

But one Japanese company in the Information Technology (IT) sector has taken an unusual approach to reinvigorating the labor market. SHIFT, which provides software-testing services, is poaching and re-training workers from other industries, turning them into IT pros. As Prime Minister Fumio Kishida advocates for the reskilling of workers and for companies to increase wages, SHIFT’s system is an example of how companies could help put a dent in Japan’s entrenched model of lifetime employment, helping the country dig out of a decades-long deflationary environment.

Among its labor-market challenges, Japan faces a major shortage of IT engineers. Of the 75 million people in the country’s working population, only about one million are IT professionals. That’s a lower proportion than in other developed countries such as the US and Germany. But SHIFT estimates that 10% of Japan’s non-IT workers aspire to join the space.

Software testing is also one of the most labor-intensive processes in software development, as it entails the time-consuming work of manually looking for bugs within code and making sure an application works as intended. For firms that struggle to find experienced programmers to begin with, having those expensive programmers do testing doesn’t make sense. Some of SHIFT’s biggest customers are consulting firms that would rather have their own high-paid employees focus on their main business of consulting while outsourcing something like software testing to save money. For example, the average salary at Nomura Research Institute (NRI), an IT-consulting firm, is double the average at SHIFT:

In many areas of our lives, we can, in fact, learn from our experiences. Over time we start to see patterns in events and that pattern recognition enables subjective judgment, or what is often called intuition. But those patterns need to be recurrent, in environments where there is a clear and stable relationship between cause and effect, so that history really does repeat itself.

In his book Range, David Epstein described that sort of learning environment as “kind”—patterns repeat, feedback is immediate, and experience can lead to expertise. As he writes, “In golf or chess, a ball or piece is moved according to rules and within defined boundaries, a consequence is quickly apparent, and similar challenges occur repeatedly…. the player observes what happened, attempts to correct the error, tries again, and repeats for years.”

In contrast, in the sorts of learning environments that Epstein describes as “wicked” there are few (or no) clear rules and feedback is limited at best. In these kinds of environments, experience teaches you little. Indeed, it can be dangerous. Experience can lead us to over-interpret, to see patterns where there are none, and to become entrenched in our ideas.

Once we have an idea, it is extremely hard to change our minds. Confirmation bias means that we see evidence that confirms our views and ignore that which challenges them. When facts change, we should change our minds, but we rarely do. And cognitive entrenchment means that the more experience we have, the more difficult we find it to adapt to changing circumstances. With greater experience comes rigidity.

The fact that more experience can lead to these behavioral pitfalls is a good reminder that it’s important to pay attention to smart, inexperienced people. Often in organizations, seniority can lead to one’s views being accorded more weight, while more inexperienced colleagues’ views are often dismissed as lacking sufficient wisdom.

Investing, obviously, takes place in a wicked learning environment. The relationship between cause and effect on market prices is highly obscure. Few patterns repeat and, once identified, are arbitraged away and do not persist. There is no evidence, for example, that market participants can forecast the direction of markets, let alone macroeconomic or political variables.

Furthermore, for long-term investors such as us, it is hard to identify the right feedback to our decision-making. Our goal is to construct portfolios that outperform the broad markets on a risk-adjusted basis over extended periods. But returns are very time dependent, and short-term price movements are a poor guide to long-term returns, offering us poor feedback on our decisions. We must look at our investment theses and create our own feedback loops so that we can test whether the fundamental insights we are relying on to forecast outperformance of the stock of a particular company remain valid. And to overcome cognitive entrenchment, we must be prepared to update our beliefs—our forecasts—if the facts change.

This sort of learning environment is why when it comes to investing, experience doesn’t lead to expertise. It leads, simply, to experience—more opportunities to learn, more chances to understand the boundaries of our knowledge. But those chances are very, very valuable.

One of our basic beliefs about equity markets is that they are efficient, but not entirely so. There are inefficiencies that result from the biases of market participants, and to overcome our own biases and exploit those of others, we have structure and process—or rules—that govern how we do research and provide the background to the judgment required about when to buy and sell stocks.

But are there any permanent rules in investing? Rules are important for controlling cognitive biases, but they are not unchanging dogma. We should be prepared to change our rules when the environment changes or when they do not work. In an investment firm, humility about our ability to forecast accurately is important, and so is an open-mindedness about rules. More experience gives us the ability to look at our own behavior, to observe the errors that we make—usually because of our own biases—and to implement structures and processes that help mitigate the all-too-human tendency to make decisions where the results do not contribute to achieving our goals.

I know less now than I thought I did when I was new to the investment business 45 years ago. What experience has taught me is the importance of being aware of market history but not relying on it to make forecasts. It has taught me that how we behave is more important than what we know. And most importantly, experience has given me more chances to test ideas in the marketplace, receive feedback, and use that feedback for continuous improvement.

Perhaps most intriguingly, NVIDIA is a leading company in the biggest tech-driven trend to come along in years, artificial intelligence. It makes the chips that power AI-based computer systems, and it sells the software and services companies need to operate their own AI programs. And NVIDIA was a big company before AI took off.

As if to emphasize the point, this week the company posted third-quarter revenue of US$18.1 billion—tripling from a year ago and setting a company record. Earnings were also a record at US$10 billion.

NVIDIA meets all our core criteria for a quality growth company: It has a sustainable business and a competitive advantage, solid management, and financial strength. Over the last six years, its revenue has grown from nearly US$7 billion in fiscal 2017 to just under US$27 billion in fiscal 2022.

But as NVIDIA reaches dizzying valuations—it currently trades at 118 times earnings—we can’t help thinking of another good technology company whose stock once commanded nose-bleed premiums: Cisco Systems.

Cisco makes the networking equipment that enables much of the internet. As the World Wide Web was taking off in the mid-1990s, Cisco Chief Executive John Chambers was telling people a new era of computing was coming, and the company’s hardware played a big part in making that new era real. Between 1995 and 2000, its revenue surged 850%, from about US$2 billion to US$19 billion.

Cisco stock did even better, growing an incredible 3,800%, from US$2 in January 1995 to US$79 in March 2000. The title of its 1999 annual report exhorted investors to “Capture the Momentum.” Many took that advice. In March 2000, at the height of the dot-com bubble, Cisco became the most valuable company in the world, with a market capitalization of more than US$500 billion.

Then the dot-com bubble burst. Cisco shares fell 88%, dropping from US$79 to a low of US$9.50 two years later. That drop wasn’t the result of any large change in the company’s performance. Revenue was nearly US$19 billion in fiscal 2000, US$22 billion in 2001, and about US$19 billion in 2002. But the premium that investors were willing to pay for the company disappeared as the hype around the web faded.

Over the next two decades, Cisco kept growing. Its sales in 2022 were nearly US$52 billion, more than double the US$19 billion it hit in 2000. Yet its stock has never traded as high as it did on March 1, 2000. Today it’s at roughly US$53. On a total return basis, it took 20 years for Cisco stock to recover from the dot-com crash.

So, are there lessons we can learn from Cisco as we look at NVIDIA? Just as Chambers argued 25 years ago that a new era of computing was at hand, Huang has been talking up AI. Just this month he said “In the last 40 years, nothing has been this big. It’s bigger than PC, it’s bigger than mobile, and it’s gonna be bigger than the internet, by far.” The enthusiasm for AI’s future has led to very high valuation multiples for NVIDIA, although not as high as Cisco reached in 2000.

The possibilities are mind-blowing. The DRC, with a population of 112 million and situated almost precisely in the middle of the continent, is the second-largest country in Africa by landmass and the 11th largest in the world. The Congo River, which winds through the country and is the second largest in the world by discharge volume, has the potential to produce 100 gigawatts of clean electricity, of which less than 3% is currently being harnessed.

With the river and its tributaries coursing through the countryside, the DRC has an estimated 80 million hectares of arable land, enough to produce food for two billion people. The DRC also has abundant mineral resources. A recent UN study estimated its untapped mineral reserves were worth US$24 trillion. The DRC holds 46% of the world’s cobalt reserves, 23% of the world’s lithium reserves, and 4% of the world’s copper reserves. These are all commodities essential in the effort to enable the global transition to green energy.

Property Deleveraging

Disney and Charter clashed over a new cable agreement. Charter complained about the high fees it paid for ESPN, FX, and other Disney channels while Disney was funneling premium content to its own Disney+ streaming service. Eventually, Disney’s channels disappeared from Charter’s Spectrum TV service, and Spectrum stood firm: it was prepared to give up Disney’s networks, seemingly forever.

It didn’t come to that, though, and the terms of the agreement don’t sound monumental: Disney+ will now be an option for Charter subscribers for an additional fee. Disney gets new eyeballs, but hands over a chunk of its fees to Charter, which had faced a seemingly inevitable revenue decline from its cable business due to the rise of streaming. The agreement offers a reprieve from that.

However, the terms of the resolution show that Disney as a supplier had far less bargaining power with its customer than it had assumed. It was forced to make material concessions that will affect its transition to a full-streaming model. Make no mistake, Disney backed down, and that loss is going to hurt its bottom line in the long run. Moreover, if the world’s largest entertainment company couldn’t use its muscle to get what it wants, then all the other networks are going to face the same dilemma when their carriage agreements come up for renewal. Disney’s capitulation could signal a major shift in the entertainment industry.

For decades, “content is king” was the mantra of the media industry. While cable companies were the primary distributor of content made by studios, the ultimate pricing power was always in the hands of the studios, especially studios like Disney that owned must-see kids, sports, and movie content. A cable provider could not attract subscribers without these must-have channels. As a result, even though there would be heated negotiations over fees, ultimately cable providers would yield to the studios’ demands.

The studios’ leverage has been weakened by the very thing they are focused on: streaming. Streaming subscribers often cherry pick services, signing up for a short time if there’s a must-see program and then canceling. For Disney and the others, there is a fundamental mismatch between costs and revenue duration. Streaming platforms need a constant flow of new programming to limit subscriber churn, but that pushes operating costs up into the billions. Not all of them can afford it.

It’s possible Charter perceived this, or just felt like it had nothing to lose. It was willing to take a loss of subscribers upfront by terminating its Disney arrangement rather than bleed subscribers over a number of years if it didn’t challenge Disney, given either course would likely lead to the same terminal point, just in different time frames. Charter’s hard stand showed the flaw in the Disney plan.

The content king may not be dead but it definitely seems like he holds less power.

Ozempic being used as a substitute for a different medical treatment goes beyond Novo Nordisk selling the same drug under different names. Ozempic could also serve as a replacement for people contemplating bariatric surgery, since it stands to reason that anybody considering surgery would likely be willing to try a less-invasive treatment. Recently, Intuitive Surgical noted a slowdown in the growth of bariatric surgical procedures because of the increasing use of drugs such as Ozempic. “Some customers have indicated that they are seeing increased patient interest in weight-loss drugs,” Intuitive chief financial officer Jamie Samath said in July.

Given that obesity is the most important reversible factor contributing to sleep apnea, there’s a chance Ozempic and similar drugs could become a treatment for that, too. Eli Lilly, for instance, is running a study of its type 2 diabetes medication Mounjaro, which is in the same drug class as Ozempic/Wegovy, as a possible treatment for sleep apnea. Results are due in March 2024.

That could be a problem for a company like ResMed, which makes sleep-apnea treatments with its CPAP (continuous positive airway pressure) therapy. These are machines that force air through the patient’s nasal passages, enabling better sleep. For patients, the issue may go beyond just which treatment is more effective.

Cost will be a big factor. Medicare and private insurers cover Ozempic for its commercially approved use, diabetes, but not for weight loss or other off-label uses. That could be important because the cost of Ozempic can be considerable (without insurance, it can cost about $1,000 a month). For sleep apnea patients, ResMed products may end up delivering the same or better results at a much lower price.

ResMed CEO Michael Ferrell in fact seems to welcome the new attention, since sleep apnea tends to be an underdiagnosed condition. Ozempic and similar drugs could bring potential patients “into the funnel,” he said on a conference call, while issues like cost and side effects will limit any hit to sales caused by the drugs. “That’s good for us, too,” he said.

The big-picture view suggests that Meta is building a hub for user-generated content (UGC) discovery and distribution that aims to go head-to-head with the likes of YouTube and TikTok. In the world of unlimited content, the power shifts from creators to distributors and curators. In this scenario, the ultimate constraint on demand for content is the totality of leisure man-hours; Meta’s goal is to optimize how to fill those hours with the most compelling content.

Generative AI could also help transform Meta’s main money-maker, its advertising business. The digital-ad market comprises roughly 70% of the overall advertising market, and is dominated by two firms, Meta and Alphabet. Finding a way to expand its market share has been a stumbling block for Meta. However, with these new AI tools, Meta may have found a way around that constraint. It may not be able to take much more share of the advertising market, but it could start taking share of the advertising-creation market. On the call, Zuckerberg specifically mentioned the strides made by its Advantage+ generative AI tools that allows advertisers to supply just an image, from which the AI will then develop an entire ad campaign. For small companies that can’t afford to hire an advertising agency, this could be a powerful alternative and a lucrative market for Meta. Its Advantage+ ad program has the potential to take share from creatives and even advertising agencies by customizing, altering, or outright creating content for advertising, rather than just targeting or measuring it.

ChatGPT, the chatbot that helped spark the market’s AI enthusiasm, is an important innovation because it can digest large amounts of text (hence the term large language model), communicate in natural (human) language, and generate sophisticated responses. Based on the Transformer architecture, a technique first introduced by Google in 2017, ChatGPT demonstrates the advances that have been made in AI that open the door to a wider set of business uses. But while natural language models recently produced epiphanies among lay chief executives and investors regarding AI, some tech companies were already investing in such capabilities and are being rewarded for that foresight. NVIDIA has been the biggest beneficiary this year in terms of its stock run and projected revenue gains; however, our other holdings, such as Adobe, Microsoft, Salesforce, ServiceNow, Synopsys, and TSMC, also appear among the possible beneficiaries. More companies—including, perhaps, some not yet in existence—will certainly join the ranks over time.

While it is still early, it’s evident that these companies see generative AI as transformative to their businesses and something upon which they can build new revenue models. Additionally, they are turning to AI to boost internal productivity, enhance existing customer offerings, and improve the quality and efficiency of customer interactions.

Most notably, Microsoft was able to gain an immediate leadership position in generative AI by making a US$10 billion investment in OpenAI, the company behind ChatGPT, earlier this year. Microsoft’s Bing search engine has since introduced ChatGPT into its web index data—a collection so large that it is rivaled by the dataset of only one other business in the world, Alphabet’s Google. Data are the feedstock of AI models, and an AI-enhanced search engine trained on so much data may attract more users to Bing, allowing Microsoft to sell more ads on the service. Microsoft is also adding generative AI to other products, including the Azure cloud service, enabling business customers who use Azure to easily integrate OpenAI models to glean more insights from their data and automate functions such as certain IT tasks. These added capabilities should motivate more businesses to migrate their data to the cloud and make Azure more competitive with Amazon.com’s AWS and Google Cloud.

The beneficiaries of demand for generative AI aren’t limited to traditional IT-sector companies. Data centers used to train AI models require up to ten times more power than typical data centers, thus requiring more-powerful equipment and backup power. Given the amount of heat they generate, new liquid-cooling solutions will be needed as well. This creates an opportunity for Schneider Electric, which has been developing innovative data-center equipment solutions for many years.

In the meantime, NVIDIA has emerged as the unrivaled global leader in providing the technologies at the center of the AI arms race. Due to an explosion of demand related to generative AI and LLMs from across its customer base, NVIDIA projects that data-center revenue for its fiscal second quarter ending in July will surge to US$11 billion. Not only is that more than double last quarter’s total, but the forecast also shattered the average analyst estimate that called for about US$7 billion.

Our investments in NVIDIA and Schneider are reflective of how we are thinking through the many unknowns and approaching portfolio structure in this environment. Through our fundamental framework, we can appreciate the broad excitement for AI, but we also remain conscious of valuations and thoughtful about diversification, recognizing that it’s unlikely anyone can predict today the biggest long-term winners.

In the first three months of 2023, P&G raised prices a whopping 10% year over year, following a series of large price hikes implemented throughout 2022:

Even if the US features most of the world’s biggest companies, it’s hardly the exclusive repository of the best ones. Using cash flow return on investment, rather than market value, as our measurement reveals that the majority of the most profitable and capital efficient businesses in just about every sector are located outside the US. The only exceptions are two areas where US companies are clearly dominant—Information Technology and Health Care.

By “not doing macro,” he means that we try not to allow our judgments about macroeconomic variables—GDP growth, inflation, and real interest rates—or geopolitical events to dictate our views on individual companies. By “macro does us,” he means that when the market’s risk tolerance and underlying assumptions change because of unexpected shifts in the macroeconomic environment, the consequential price movements can dominate a portfolio’s periodic absolute and relative returns. Although the injury may be only temporary, it is hard to avoid getting swept up in the general fervor. That’s a problem if it leads to reflexive and hasty reactions. It is precisely to avoid getting whipsawed in this way that we devote much of our efforts to restraining our inherent behavioral biases. But even with the sturdiest of behavioral guardrails designed to curb our responsiveness, the sudden jump in portfolio volatility and tracking error feels no less jarring.

Our investment approach centers on analysis of the prospects for specific companies and the industries in which they operate. As a result, the portfolios we construct are a mosaic of company-centric views, with the final picture coming into focus only after all of the pieces are assembled. Sometimes our bottom-up investment process leads us to sidestep systemic issues. In the years before the global financial crisis, for instance, we became disenchanted with the traditional banking industry. We didn’t like how the increased price transparency that came with the migration of services online diminished banks’ bargaining power over their borrowers and depositors, or how rising levels of consumer debt portended that growth could be weaker, and rivalry and risk-taking fiercer. That was enough to lead us largely to steer clear of banking stocks. Although in hindsight our portfolio positioning appeared to anticipate the subsequent dislocations, in fact we had no overarching view on systemic financial stability.

There is no question it would be nice to have clear foresight on GDP, inflation, and real rates. Like it or not, economic growth is the lifeblood of industrial economies, and, despite its ever-shifting relationship to equity returns, is closely associated with aggregate earnings. Similarly, inflation and real rates are both barometers and agents of economic transformation that always could and frequently do alter the path of economic growth. And there is strong reason to believe that macro-level dislocations are likely to be an order of magnitude greater than the mispricings that occur at the security level. Given the periodic importance of such dislocations, this raises the question: Why don’t we attempt to shape our portfolios more explicitly by directly forecasting economic variables or geopolitical events? The question is particularly vexing given the current importance of the inflation outlook for equities.

Tetlock’s conclusion was that expert predictions about geopolitical crises were no better than guesses. The only contribution that expertise seemed consistently to confer was a perverse boost in confidence regarding one’s (ineffective) forecasts.

The standard response typically trotted out is that forecasting is exceptionally hard, or as the Danish physicist Niels Bohr is alleged to have quipped, “Prediction is very difficult, especially about the future.” Nowhere is this more true than with geopolitical events, which by all accounts appear to defy anyone’s ability to anticipate them with anything approaching consistency. The political scientist Philip Tetlock tackled this issue head-on in a multidecade study described in his 2015 book, Superforecasting: The Art and Science of Prediction. Tetlock’s conclusion was that expert predictions about geopolitical crises were no better than guesses. What’s more, the only contribution that expertise seemed consistently to confer was a perverse boost in confidence regarding one’s (ineffective) forecasts.

The record for macroeconomic forecasting is not quite as wretched; at least there are frameworks and models on which to hang one’s thinking. But it’s still one of those endeavors where you’re doing very well if you’re right a little more often than you’re wrong. Even so, it is not as though the ground-level forecasting of cashflows, business prospects, and competitive forces is easy. So perhaps the real question is why we consider the latter sensible but the former a fool’s errand, at least for fundamental equity investors such as us.

The answer in large part comes down to the size of the opportunity set, or the number of times you get to apply your investing edge. Even the most skilled forecasters, whatever their forecasting game, have but the tiniest of edges and so the surest way to increase their chances of success is to apply that minute edge as many times as possible. In a global investment universe, there are roughly 8,000 equity securities, each operating in its own industry and geography with their own sets of return drivers, compared with a relative handful of forecastable macroeconomic variables. Given equal forecasting skill, you are going to have a far higher likelihood of some overall success by applying that skill across many securities rather than over a few economic statistics. Even allowing for the fact that not every security’s return is entirely idiosyncratic, there are still far more independent and durable drivers of individual security returns than there are of macroeconomic trends, which may allow you to get the micro right without so much as taking a swing at the macro.

Even if you were one of the few hyper-skilled and hyper-accurate macro forecasters, a portfolio of stocks would be a poor way to capitalize on views about inflation or economic growth. Although there’s a relationship between the macroeconomy and stock returns, that relationship is neither simple nor determinate. In practical terms, stocks are a terribly inefficient way to express a view on macroeconomic variables. Better to bet on currencies, yields curves, and commodity prices directly, all of which are far more closely tethered to the outlook for growth, inflation, and real rates.

It’s not just that there are better, more precise, and more levered ways to express macroeconomic views. It’s also that trying to do so with stocks risks erasing the hard-won company-level insights that are the linchpin of our portfolios.

And it’s not just that there are better, more precise, and more levered ways to express such views. It’s also that trying to do so with stocks risks erasing the hard-won company-level insights that are the linchpin of our portfolios. All the companies in which we invest have track records of successfully generating cash and reinvesting it wisely. In many cases these companies have survived wars, recessions, pandemics, inflation, deflation, and geopolitical shocks. Sacrificing those financially valuable fundamental attributes in a most likely vain attempt to time a particular economic cycle not only presupposes a preternatural ability to tie economic outcomes to individual security returns but also risks the long-term health of the portfolio.

We don’t do macro, so by default we allow macro to do us. There are, though, ways in which we can protect against developments that result in sudden changes in risk aversion. One is to diversify—events that damage the outlook in one industry or part of the world may have no impact, or even a beneficial one, on stock prices elsewhere. That said, diversification cannot work during times of systemic crisis, when correlations between geographies, industries, sectors, and individual securities converge. That’s where our reliance on a company’s strength comes in. Two hallmarks of a company’s quality are the ability of its management to prepare for a wide range of outcomes and whether it has the financial strength to survive the worst possible operating conditions.

Although we can’t estimate the probability of market-moving events, we can think about the magnitude and range of potential outcomes so we may more fully understand our exposures and ensure we are sufficiently diversified to protect against them. For example, before Russia’s invasion of Ukraine, many people thought about a range of outcomes that included war versus no war or disruption to energy supplies. But, given prior Western responses, few considered the potential for sanctions that would freeze all Russian assets and render them worthless, at least for the time being. Now, as we think about the financial market implications if China were to invade Taiwan, we must consider the possibility that Chinese assets could be similarly impaired.

So, what do we do about it? We certainly aren’t going to try to parse Chinese troop movements or overturn our investment theses on the dozens of companies, not only in China but also throughout the global supply chain, that could be impacted by what at this point must still be considered a very low-probability event. On the other hand, thinking long and hard about the potential risks to supply lines, revenues, or the corporate structures of portfolio companies and what further levels of diversification might be in order is very much in our wheelhouse.

Financial markets, among other things, act as a type of sieve that screens investments. Ideally, the riskiest tradable assets pass through to the strongest balance sheets. In practice, they often end up on the balance sheets of the most accommodating investors, owned not by those most capable of bearing risks, but rather those most willing to. A well-functioning market will tend to filter out those excesses, eliminating investors who exceed their risk-bearing capacity, while helping to ensure that those who take on too little risk see their returns shrink and their share of the capital base dwindle. On balance, this sifting mechanism helps to steer capital to its most productive uses.

In extended bull markets, however, this process tends to break down, as rewards flow disproportionally to the most aggressive, over-confident, and complacent investors. This creates a powerful feedback loop, as unbridled risk-taking is rewarded with outperformance which in turn draws more capital. Once the process gets going, it is self-reinforcing as the newly attracted capital is plowed back into the same group of assets. In so doing, fragilities increase, and the longer it persists the more distorted capital allocation becomes.

By central bankers’ own admission, their goal was to spur a positive wealth effect on spending, by pushing safety-minded investors into taking more risks, thus driving up valuations. Now we will see just how difficult the unwinding will be as the wealth effect goes into reverse.

The implosion over the last six months (at least in terms of their asset prices) of profitless growth stocks, crypto assets, and other speculative creatures of the markets is emblematic of the reckoning that can occur once excessive risk taking continues for too long. In this case, it has been slowly building for over a decade. Fears of outright deflation following the global financial crisis encouraged central banks to keep pushing interest rates lower to allow over-extended borrowers to heal, and to reduce the cost of capital for new investment in the hopes of kick-starting growth. At the same time, the total absence of inflationary pressures seduced central bankers to set aside worries about the dangers of money printing and unrestrained liquidity. By their own admission, the goal of their zero-interest monetary policy was to spur a positive wealth effect on spending, by pushing fearful, safety-minded investors into taking more risks, thus driving up valuations.¹

Primary beneficiaries of this process were growth stocks, particularly the most speculative growth stocks of companies with untried business models; their multiples steadily increased, inversely with submerging interest rates. This coincided with a surge in indexation and so-called “smart beta” and factor investing, which channeled vast amounts of capital to the same group of stocks. Remarkably, for an extended period, some of these stocks were simultaneously defensive, fast growing, and relatively involatile, guaranteeing them an outsized weighting across a plethora of indices designed to track those very characteristics. Many active managers, faced with the prospect of having to beat a steadily narrowing benchmark, also piled in, overweighting these same stocks in the case of mutual funds, or owning them with leverage in the case of hedge funds. The prolonged success of these strategies encouraged yet more risk-taking, with new rafts of venture-backed startups and IPOs lacking anywhere near the prodigious free cash flows of the established tech companies. Moreover, the initial phases of the pandemic led to a late kick for tech stocks seemingly insulated from pandemic-induced disruptions to traditional commerce, which further turbocharged their valuations. The result was levitating valuations justified on the back of negative real interest rates.

The whole process was vulnerable to any shift in the macroeconomic backdrop that could prompt central banks to reverse course. The coils of that shift were arguably set by the pandemic and then sprung by the vaccine clinical trial results and rollouts which together upended consumption patterns, snarled supply chains, and reconfigured labor markets. According to the Bank for International Settlements, global growth, after cratering in 2020, accelerated to the fastest pace in almost five decades the following year.² The subsequent conflict in Ukraine exposed the fragility of an energy supply that had been undermined by a decade of underinvestment and climate-related antipathy, applying an energy supply shock to a combustible mix.

Now we will see just how difficult unwinding the unprecedented asset purchase programs and zero interest rate policies will be as central bank balance sheets shrink, interest rates rise, and the wealth effect goes into reverse. Policymakers embarked on their former policies with a clear-eyed view of the clear and present danger of deflation while the uncertain contingent costs inhabited a distant and abstract future. As that future arrives, the true costs are being revealed.