Is higher stock market concentration good or bad for Corporate America?

Is higher stock market concentration good or bad for Corporate America?

In recent years, S&P 500 stock market returns exhibit spectacular concentration in the top tech titans Meta ($META), Apple ($AAPL), Microsoft ($MSFT), Google ($GOOG), Amazon ($AMZN), Nvidia ($NVDA), and Tesla ($TSLA), also known as MAMGANT or Magnificent 7. In the past years from January 2022 to December 2024, the Magnificent 7 delivered a hefty stock market return of 41% (versus only 17% for the other 493 stocks in the S&P 500 index). As of early-March 2025, the S&P 500 index shows substantial stock market concentration. Specifically, the top 10 stocks account for more than 35% of S&P 500 market capitalization. Historically, the top 10 stocks represented more than 20% of S&P 500 market capitalization over the past few decades. Further, the market capitalization of the largest stock relative to the top quartile stock now shows the highest level of stock market concentration since 1932. Although there has been no clear relationship between stock market concentration and near-term return performance, some economists and institutional investors express their concern about increasingly higher stock market concentration in NYSE and Nasdaq. Solid sales and profits in Corporate America can help substantially boost the S&P 500 index, perhaps from 6,000 points to 6,500 points, in the next few years. In this positive light, we can expect S&P 500 stocks, specifically the Magnificent 7 tech titans, to out-perform with a hefty 9% average return per annum in the next few years. Our fundamental analysis combines our proprietary alpha stock signals with ESG scores to lend credence to some of the tech titans in S&P 500 and more broadly Corporate America, especially the top tech titans with significant AI-driven technological advancements.

 

Stock market investors need not worry about higher market concentration in the longer term. American history shows that high stock market concentration usually leads to lower average returns ceteris paribus over longer investment horizons. When we add market concentration as a distinct variable to the long-run stock market return model, the model forecasts average S&P 500 annual returns of 3%-5% in each decade. Although this subpar return performance falls short of the historical average return of 11% for S&P 500, this drag on long-run returns arises from the greater volatility of tech titan stock returns. In recent times, the current higher stock market valuations of the Magnificent 7 tech titans now appear to embed greater growth expectations in relation to the recent AI-led stock market rally. From Apple ($AAPL), Amazon ($AMZN), and Microsoft ($MSFT) to Meta ($META) and Google ($GOOG), these tech titans rely upon the steady flows of high-end semiconductor microchips, graphical processing units (GPU), and several other quantum advances to make iterative continuous improvements for their Generative AI large language models (Gen AI LLM). As of mid-March 2025, we believe the current Gen AI LLM bellwethers include: Google Gemini, Meta Llama, Microsoft-OpenAI ChatGPT, Anthropic Claude, Perplexity, Alibaba Qwen, DeepSeek, Amazon Nova, Mistral, and Twitter xAI Grok.

 

After all, stock market concentration per se should not be a major concern for U.S. investors. This concentration often turns out to be a mainstream mechanical result of winner-takes-all sales and profits in AI-driven markets such as Internet search, text, voice, vision, video, and some smart combinations of these common forms of content generation. Specifically, stock market concentration need not heighten the 2 key types of stock market risks: fundamental risks and disequilibrium risks. The former relate to unlikely structural declines in fundamental sales and profits for S&P 500 tech titans, and the latter relate to short-term deviations from fair market values. Although some of the S&P 500 tech stocks seem to reach a new steady state of stock market over-valuation, we believe the vast majority of S&P 500 tech titans can benefit substantially from the broader AI stock market rally to explore new niche markets for both institutional investors and retail investors. In a positive light, stock market concentration need not be a major concern for U.S. investors in a fundamental view. However, we believe U.S. investors should refrain from placing big bets on the recent extreme winners, because their substantially higher market valuations may or may not justify their fundamental forces in the broader context of medium-term competitive threats. At least some of the recent AI-driven winners cannot sustain their greater growth expectations and longer-term competitive advantages. It takes time for U.S. investors to better assess whether each of these AI-driven winners passes the baseline proof of concept for the optimal product-market fit.

 

Over the past 60 years, no more than 3% of S&P 500 companies were able to sustain 20%+ sales growth for 10 consecutive years. We can back up this empirical result with Jim Collins’s seminal research on what makes great companies tick in his strategic management books: Built to Last, Good to Great, Great by Choice, and Beyond Entrepreneurship 2.0. Therefore, it is hard for the recent AI-driven tech winners to sustain their stock market outperformance in the long run. For at least some of these recent growth stocks, the probable mean reversion of returns can result in future under-performance, especially when their future fundamental sales and profits dwindle, dry up, and then fail to allow these recent winners to dominate in the respective AI-driven markets and adjacent niche segments.

 

The U.S. regulators should step in when the AI-driven tech titans use their market power to stave off both their rivals and competitors with higher product prices. To the extent that stock market concentration may stifle subsequent disruptive innovations, the Securities Exchange Commission (SEC), Federal Trade Commission (FTC), and Department of Justice (DoJ) etc should introduce new antitrust rules and regulations to make American tech titans face fierce competitive pressure with no clear dominance in any particular AI-driven market. The classic examples include: Apple App Store and Google Play in the mobile software market; Amazon e-commerce in the retail market for consumer goods; Nvidia GPUs, microchips, and several other hardware advances in the semiconductor industry; and Tesla in the global market for electric vehicles (EV) and autonomous robotaxis (AR).

 

This current high stock market concentration serves as one of the mainstream reasons for U.S. investors to further diversify exposures across asset classes, regions, and strategies. The historically optimal portfolio mix of 60% stocks and 40% bonds remains empirically valid, relevant, profitable, and reasonable in a fundamental view. In light of the still-solid sales and profits in the AI-driven sections of Corporate America, we believe the optimal portfolio combo of 60% stocks and 40% bonds continues to serve as the mainstream economic engine for the global asset management industry, specifically BlackRock, State Street, and Vanguard. U.S. investors need to revisit their optimal choices of AI-driven stocks with new fundamental competitive moats, substantial safety margins, positive network effects, cost economies, and information cascades.

 

Some economists argue that higher U.S. stock market concentration can be a major concern for stock market over-valuations and lower subsequent average returns in the next few years.

Today, the top 10 tech titans in the S&P 500 index account for more than 35% of total stock market capitalization. This increasingly high stock market concentration compares to a long-term historical average of about 20% over the past 45 years. An alternative measure of stock market concentration, the market capitalization of the largest stock relative to the top quartile stock, shows that the current level of concentration has hit the highest threshold since 1932. For this reason, the S&P 500 index shows increasingly higher stock market concentration in global history. Some economists argue that this increasingly higher concentration can serve as a major concern for persistent stock market over-valuations and lower future returns over the next few years. Another useful and common alternative measure of market concentration, the Herfindahl-Hirschman Index (HHI), suggests that S&P 500 sales seem to concentrate in some sectors such as cloud media services, industrial conglomerates, pharmaceutical firms, telecoms, and tobacco companies.

 

Over the short run, both institutional investors and retail investors need not worry about high stock market concentration, because there is no clear and robust empirical relation between market concentration and S&P 500 return performance over the subsequent week, month, quarter, or year, especially when many fundamental factors, such as near-term profits, order flows, cash dividends, share repurchases, and so forth, help maintain the 9% annual return forecast for S&P 500 over the next 12 to 36 months. However, these investors should pay attention to increasingly higher stock market concentration over the longer run of at least 10 years to 25 years, because U.S. history shows that higher market concentration often leads to higher market valuations in the medium term. As a result, U.S. history further shows that these medium-term stock market over-valuations often lead to substantially lower S&P 500 annual returns over the longer investment horizons ceteris paribus.

 

Specifically, if we forecast long-run S&P 500 stock returns with several fundamental factors, such as Tobin’s q, gross margins, operating profit margins, interest rates, macro economic and financial variables, and stock market concentration, market concentration often serves as a distinct factor in support of greater long-term return forecast accuracy. For instance, we can gauge the 11% conventional annual return of S&P 500 over each decade over the past 100 years. In this century, each decade includes 5 quarters of economic output contraction on average. Over the past decade, there has been only 2 quarters of economic contraction, and the annual return of S&P 500 has been about 13.5%. By contrast, our proprietary alpha stock signals and personal finance tools result in 17 virtual stock market portfolio strategies in support of 19.3% to 21.2% annual returns from 2017 to 2025. Over the next decade, even if we assume only 4 quarters of economic output contraction, the long-run return model now forecasts S&P 500 annual returns between –3% and +9% (with average returns in the range of 3% to 5%). When we exclude stock market concentration from the long-run return model, the model would suggest annual returns between 3% and 11% (with average returns in the broader range of 4% to 9%). For this reason, stock market concentration alone helps explain almost 4 to 5 percentage points. With market concentration, this additional drag on S&P 500 annual returns goes above and beyond several fundamental factors such as Tobin’s q, gross margins, profit margins, interest rates, and macro variables. If the historical patterns persist, high stock market concentration today portends substantially lower S&P 500 annual returns in the next decade (than S&P 500 annual returns that would have been in an alternative U.S. macro environment with significantly lower stock market concentration).

 

What is the main economic intuition behind this additional drag of stock market concentration on subsequent S&P 500 return performance? This economic intuition arises from at least 2 major sources. First, higher stock market concentration suggests that forward return volatility is likely to be greater given the comparably narrow group of tech titans in the S&P 500 index. Any stock portfolio with a smaller number of constituents subject to greater idiosyncratic risk attracts substantially more volatile annual returns (in stark contrast to a broadly diverse stock portfolio). More importantly, the higher market valuations of many top tech titans in S&P 500 now drive this higher stock market concentration. In a risk-return framework, many investors cannot receive sufficient compensation for larger idiosyncratic risk in relation to higher stock market concentration. In recent times, the current market valuations of the top tech titans in S&P 500 are relatively high: their P/E ratios are in the broad range of 31x to 35x. When we take the reciprocal values of these P/E ratios, we get annual returns in the range of only 2% to 3.5%. By an order of magnitude, these annual returns are lower than the 10-year Treasury yields of 4.2% to 4.5%. In this negative light, these top tech titans in S&P 500 now seem to trade at extremely high stock market valuations. In effect, these current over-valuations are not commensurate with the larger idiosyncratic risk that many U.S. investors face by buying these tech titan stocks at relatively high P/E ratios. As the top tech titan stocks have already generated 41% annual returns in recent years (more than half of the annual returns of S&P 500), their idiosyncratic risk looms large.

 

Second, greater growth expectations seem to support these exceptionally high stock market valuations. These growth expectations shine fresh light on 20%+ growth rates for sales and profits with persistently high gross margins and profit margins. Throughout American history, however, only 3% of S&P 500 companies can consistently deliver-and-sustain 20%+ growth rates for sales and profits over 10 consecutive years. Also, almost no companies can remain great with 20%+ growth rates for both sales and profits well beyond 15 years (cf. Jim Collins’s recent research on what makes great companies tick: Built to Last, Good to Great, Great by Choice, and Beyond Entrepreneurship 2.0). The current return performance of S&P 500 tech titans is likely to disappoint current euphoric market valuations and growth expectations in the longer run.

 

For non-taxable institutional investors such as sovereign wealth funds and pension funds, we believe long-term fundamental factors favor the ultimate persistent winners in Generative AI technology. Although our forecasts suggest subpar 9% annual returns for S&P 500 stocks over the next decade, these non-taxable institutional investors should overweight some of the Gen AI bellwethers. From Apple ($AAPL), Amazon ($AMZN), and Microsoft ($MSFT) to Meta ($META) and Google ($GOOG), these tech titans rely on the steady flows of high-end semiconductor microchips, graphical processing units (GPU), and other quantum advances to make iterative continuous improvements for their cutting-edge, state-of-the-art Generative AI large language models (LLM). As of mid-March 2025, we believe the current Gen AI LLM bellwethers include: Microsoft-OpenAI ChatGPT and Copilot, Anthropic Claude, Perplexity, Google Gemini, Meta Llama, Alibaba Qwen, DeepSeek, Amazon Nova, Mistral, and Twitter xAI Grok.

 

Both institutional investors and retail investors need not worry about increasingly high stock market concentration in America, but the pervasive U.S. stock market over-valuation seems to be a more problematic modern feature of American tech titans.

We can re-consider some special cases, and then U.S. stock market concentration becomes significantly less problematic in the deeper context of these special cases. In the mid-1950s, the top 3 American tech titans, IBM, AT&T, and GM accounted for almost 30% of total U.S. stock market capitalization. In 1960, a single public company, AT&T, represented more than 13% of U.S. stock market capitalization. In this context, the increasingly higher stock market concentration continues to be within historical norms for America. In Europe, some countries such as France and Switzerland show much higher stock market concentration than NYSE and Nasdaq. In several East Asian countries, the single largest public company, specifically TSMC in Taiwan and Samsung in South Korea, now accounts for far more than 20% of total stock market capitalization there. For these reasons, both historically and globally, the U.S. stock market demonstrates increasingly, but not alarmingly, higher market concentration in some of the top tech titans today.

 

For sure, U.S. stock market concentration has risen substantially over the past 15 years; but this higher market concentration arises as a mainstream mechanical result of 2 mega trends. First, the largest tech titans attract and absorb greater sales and profits in AI-driven winner-takes-all markets such as Internet search, cloud connectivity, mobile software, e-commerce, and so forth. With both positive network effects and scale economies, many of these markets help enhance human productivity with Gen AI LLMs such as ChatGPT, Gemini, and Qwen. Hence, increasingly higher U.S. stock market concentration reflects the higher concentration of fundamental sales and profits in these AI-driven markets. Second, the top tech titans now attract more favorable stock market valuations (in stark contrast to their modest stock market valuations about 10 to 15 years ago). Because these top tech titans have outperformed their traditional peers with smarter, stronger, and better fundamental sales, profits, strengths, and competitive advantages over the past 15 years, these fundamental strengths mechanically heighten stock market concentration in America. Investors need not worry about increasingly higher market concentration across NYSE and Nasdaq, but the pervasive U.S. stock market over-valuation seems to be a more problematic modern feature of American tech titans.

 

With increasingly higher stock market concentration, the U.S. stock market is not necessarily riskier in a fundamental view. For example, the U.S. stock market used to show much higher market concentration back in the 1950s, but the U.S. stock market was arguably safer, more stable, and much less volatile than the U.S. stock market today. In the 1950s, the American real economy experienced steady economic output growth, employment, and relative price stability even though one mega phone company (AT&T), 3 large automobile manufacturers (GM, Ford, and Chrysler), and several large oil refiners (Exxon, Mobil, Chevron, and so forth) dominated the U.S. stock market.

 

There are 2 distinct types of stock market risks: fundamental risks and disequilibrium risks. The former relate to unlikely structural declines in fundamental sales and profits for S&P 500 tech titans, and the latter relate to short-term deviations from fair market values. Neither one of these risks necessarily increases when the stock market concentration rises in due course. In the 1980s, the Department of Justice (DoJ) forced AT&T to split into several independent subsidiaries due to antitrust concerns, lawsuits, and regulations. As a result, American stock market concentration declined substantially overnight as AT&T was the second largest stock at the time. One monopolistic phone company, AT&T (Ma Bell), was arguably less risky for U.S. stock market investors than 7 competitive Baby Bells. In 1984, the ultimate breakup of AT&T would not completely alter the fundamental prospects of American public corporations across the whole stock market.

 

We need to better appreciate the fact that individual companies can be diverse in their own niche market segments. The Magnificent 7 tech titans garner a vast array of business lines from Internet search, e-commerce, and smartphone mobile connectivity to electric vehicles (EV), autonomous robotaxis (AR), and cloud storage and video-streaming services etc. It is not problematic for the top tech titans to put a wide variety of highly successful and profitable AI-driven businesses into one diverse constituent group as part of the S&P 500 index. There is no clear and robust empirical nexus between stock market concentration and subsequent return performance in global economic history.

 

In global economic history, Schumpeter describes and characterizes creative destruction as a series of smart disruptive innovations in the rare unique process of industrial mutation that incessantly revolutionizes a new economic structure, destroys the old one, and then repeats the same process in the distant and infinite future. Creative destruction is an inevitable part of the American enterprise. The biggest companies that were important to the U.S. economy 30 years ago are not the now important Magnificent 7 tech titans and other companies today. In the best likelihood of success, the mega tech titans that will become important to the U.S. economy 30 years from today may turn out to create completely new jobs, sales, and profits in support of their dominance in the U.S. stock market then.

 

Given that many U.S. tech titans seem to attract near-term stock market over-valuations, we believe these public companies are expensive by any reasonable stock market benchmarks. In global economic history, expensive stocks deliver subpar subsequent returns on average. For this reason, we believe the mega tech titans in S&P 500 may or may not offer sufficiently high annual returns to prove their net worth in the new couple of decades. Today, U.S. stock market concentration per se need not be a major concern for both institutional investors and retail investors. However, the increasingly higher stock market valuations of American tech titans may result in substantially lower annual returns in the next few years ceteris paribus. High stock market concentration demonstrates the triumph of the American capitalist society; whereas, increasingly high stock market valuation may ultimately deliver subpar subsequent return performance.

 

The U.S. government is likely to introduce new and stringent antitrust rules and regulations for better merger control, data oversight, and consumer protection against some American tech titans.

In America, the Federal Trade Commission (FTC) and the Department of Justice (DoJ) are responsible for antitrust enforcement, and their current jurisdictions seem to overlap in the common terrain of U.S. tech titans. Both government agencies bring tech titan conduct and merger cases, and these lawsuits usually involve some forms of anti-competitive behaviors. However, there are some important differences between the FTC and the DoJ. In relation to U.S. merger cases, the DoJ brings cases to block mergers in federal court, especially when the DoJ believes these mergers distort the level playing field for tech titans in some specific industry; whereas, the FTC brings 2 merger cases, one in federal court and the other in its in-house administrative court, with the federal case to enjoin the merger (sometimes with an injunction) so that the FTC can resolve the case in its administrative court. The FTC and the DoJ further differ in their structures. At the DoJ, the assistant attorney general for Antitrust Division leads antitrust efforts on behalf of the agency. At the FTC, 5 commissioners run the agency, and one of these 5 commissioners serves as the chair and directs the staff.

 

The FTC and the DoJ further differ in their respective enforcements of U.S. antitrust statutes. The DoJ enforces the Sherman Antitrust Act of 1890 and the Clayton Antitrust Act of 1914, Section 7 of which is the federal merger statute. The FTC enforces the Clayton Act as well but also Section 5 of the FTC Act, the latter of which prohibits unfair methods of competition. Section 5 of the FTC Act seems broader in scope than the Sherman Act, although how much broader in scope has been a matter of debate for over 100 years. Over time, the DoJ focuses on media, energy transmission and production, and technology; whereas, the FTC focuses on pharmaceutical companies, oil and natural gas refiners, and tech titans. In addition to the above statutes, both the FTC and DoJ garner greater power for merger control and antitrust enforcement under the Hart-Scott-Rodino Antitrust Improvements Act of 1976.

 

Through a presidential executive order, the U.S. government adopts a whole-of-government approach to American antitrust competition with the new White House Competition Council and a special assistant for antitrust competition. The executive order purports to dramatically shift American antitrust enforcement to a more interventionist and aggressive policy stance relative to prior decades in response to new and recurrent economic populist concerns about the anticompetitive business conduct, market pricing power, and stock market concentration of several tech titans: Meta ($META), Apple ($AAPL), Microsoft ($MSFT), Google ($GOOG), Amazon ($AMZN), Nvidia ($NVDA), and Tesla ($TSLA) (MAMGANT or the Magnificent 7). As a practical matter, the biggest change with merger control involves the U.S. government’s aversion to legal remedies, or particular agreement deals for tech titans to address pervasive concerns about antitrust competition in America. The DoJ’s current public position suggests that the agency refrains from reaching legal remedies with tech titans. By contrast, the FTC reiterates that the agency would reach legal remedies only if the surviving tech titan agreed to seek prior approval before they closed any future deals. As a result, the U.S. government would no longer have to challenge these deals to block them. Specifically, the FTC and the DoJ both delve into the recent killer acquisitions by Meta, or formerly Facebook, of Instagram and WhatsApp in a clever and cost-effective manner for the social media tech titan to retain more than 2 billion active users worldwide. As a pragmatic matter of stricter merger control, both agencies may require Meta to break up its various online platforms in response to anti-competitive conduct concerns.

 

In light of the increasingly higher stock market concentration of Magnificent 7 tech titans, the FTC and the DoJ may seek to break up some tech titans, specifically, Meta, Amazon, Nvidia, and Alphabet into their respective tech-savvy subsidiaries. Alternatively, both agencies need to decide whether they drop, settle, or continue to prosecute their respective cases. At the DoJ, the fate of each case depends on what the new assistant attorney general for Antitrust Division seeks to accomplish in due course. At the FTC, if a majority of the 5 commissioners cannot come to an agreement on each case, the case should continue. The FTC chair has the authority to steer much of antitrust staff involvement in each case. In this unique fashion, the FTC litigates each antitrust case on behalf of the U.S. government. In the next couple of decades, the future administrations are likely to remain aggressive in the pursuit of antitrust prosecutions against further mergers and acquisitions in high technology and beyond.

 

Under the Trump administration, a former FTC commissioner, Andrew Ferguson, serves as the new chair of the FTC, and Gail Slater serves as the DoJ assistant attorney general for Antitrust Division. These antitrust leaders continue to bring an America First, pro-innovation approach to antitrust enforcement. Also, these 2 antitrust leaders are likely to file new cases against mergers and acquisitions by some tech titans such as Meta, Amazon, and Alphabet. Specifically, Ferguson and Slater urge antitrust investigations into any unlawful key collusion between online platforms, because this collusion may impose limits and constraints on free speech and consumer privacy protection. With respect to Gen AI LLMs, the FTC has issued subpoenas to 5 major tech companies, Alphabet, Amazon, Anthropic, Microsoft, and OpenAI to seek information in relation to the mainstream rationale behind their Gen AI investments. This investigation should shine fresh light on the competitive impact of Gen AI investments by these 5 major tech companies. Additional issues revolve around the competition for Gen AI developmental resources such as data, energy, and human expert capital.

 

In accordance with the prior FTC rejection of Environmental, Social, and Governance (ESG) exemptions to the antitrust laws, Ferguson has criticized the use of antitrust statutes for the FTC, and even the DoJ, to achieve policy goals other than antitrust competition. In the same spirit, Slater suggests that DoJ antitrust enforcement should promote fair market competition alone. Some U.S. government agencies other than the FTC and the DoJ help address ESG themes, concerns, and several other issues in association with environmental conservation and sustainable economic development. These government agencies include the Securities Exchange Commission (SEC), Environmental Protection Agency (EPA), and Department of Labor (DoL). The new Trump administration is likely to look upon ESG defenses to antitrust competition issues with even greater disdain.

 

While higher stock market concentration is not always harmful, the rise of bad concentration has hurt U.S. consumers, some sectors, and the broader economy.

Higher stock market concentration can be good or bad. After Apple launched the iPhone, its smartphone market share rose significantly. As a result, the global market for smart phones and other mobile devices showed substantially higher stock market concentration with some oligopolistic manufacturers: Apple, Google, Samsung, Xiaomi, Huawei, Vivo, Oppo, Lenovo, Sony, and so forth. However, the smartphone invention was a positive development in the past couple of decades. In the 1990s, Walmart became a dominant player in the American supermarket sector for a good reason: Walmart provided higher-quality consumer goods at lower prices given its more efficient global supply chain. Good market concentration further arises from greater global trade. For instance, the European car industry is quite competitive, but the number of automakers has dramatically declined over recent decades because some auto companies have merged to enhance their lean production of electric vehicles (EV) and autonomous robotaxis (AR) in response to both global competition and the recent green and clean energy transition.

 

By contrast, bad stock market concentration occurs when the incumbent tech titans attempt to protect their niche pricing power and market dominance by building market entry barriers against potential rivals and competitors. Also, bad stock market concentration occurs when the incumbent tech titans merge, acquire smaller lean startups, and then leverage their niche market power to raise prices at the expense of consumers. Good stock market concentration happens in many markets such as America, Europe, China, Japan, and Malaysia. But bad stock market concentration is more of an America-specific phenomenon.

 

We can attribute bad U.S. stock market concentration to high market entry barriers in some sectors and hostile takeovers, mergers, and killer acquisitions in technology. The American wireless market is a good example of both. New firms find it difficult to enter the U.S. wireless market because cellphone plans must cover a significant fraction of the domestic population. This broader coverage can be prohibitively costly for new entrants. American regulators can help facilitate market entry by requiring new firms to rent part of an extant wireless network, as these new firms gradually build up capacity to offer their own wireless services one day. In the U.S. wireless market, high stock market concentration is bad because high cellphone bills and expensive high-speed Internet bills continue to harm U.S. household budgets. The U.S. wireless market could have remained competitive with as few as 4 to 6 major telecoms. Many decades of mergers have left only AT&T, Verizon, and T-Mobile as the major wireless service providers in America.

 

It is plausible for high stock market concentration to spur further capital investments as new firms should be able to enjoy reasonably high profit margins in order to recoup their upfront sunk costs. In response to fierce competition from the incumbent tech titans, new firms need to further invest in lean innovations for survival. However, market entry barriers often reduce and deter these capital investments and innovations. When market competition rises, these new firms usually take a hit on profit margins and maybe cut their cash dividends, but these new firms cannot slash their capital expenditures. Instead, these new firms tend to increase their capital investments in response to increasingly intense competition from the incumbent tech titans. For this reason, bad stock market concentration is harmful to not only consumers, but also some sectors and the broader real economy.

 

Although the Magnificent 7 tech titans have surely earned their moniker, these top tech titans are not large by historical standards. Superstar firms earned their success through disruptive innovations, scale economies, positive network effects, and information cascades. This logic applies to Apple, Amazon, Google, Meta, and so on. After all, these tech titans are not new under the sun and hence should not be able to receive preferential treatment. We welcome their success, but we should not allow the top tech titans to flout the rules with higher prices (despite their niche market dominance).

 

Perhaps we can fix the problem of bad market concentration by the market or by government intervention. In the past case of Walmart, Amazon took the plunge and entered the American retail market with brand-new e-commerce technology in the late-1990s and the early-2000s. In effect, Amazon’s online platform disrupted significantly Walmart’s past dominance in the American retail market. Today, the U.S. supermarket sector comprises several large efficient companies, Amazon, Walmart, Target, Costco, and so on. These retail companies compete fiercely to provide high-quality products at lower retail prices to U.S. consumers.

 

When the market cannot fix the problem of bad market concentration, the regulators should step in. Unfortunately, American history shows that the government remedies tend to come too late. By the time the U.S. government stepped in the Internet browser market to rein in Microsoft in the late-1990s, its browser archrival, Netscape, already vanished from existence. In the new cases of Meta and Alphabet, the U.S. government may find it necessary to break up these quasi-monopolies to ensure healthy and intense competition in the respective U.S. markets for social media and online search. This government intervention helps restore the new dynamism in the digital markets. However, government intervention should not be the only fundamental factor in support of new disruptive innovations for U.S. consumers. Silicon Valley, top universities, and a broader ecosystem between research institutions and private R&D venture capital funds, allow many lean startups to scale up smarter, faster, and better online platforms and digital markets worldwide. For this reason, the U.S. is home to so many world-class champions and superstar firms across some sectors, regions, and asset classes. From the benevolent social planner’s viewpoint, it is vital for the American regulators to strike a delicate balance between crafting the right antitrust enforcement policy and promoting the creation of new technological advancements and innovations for U.S. consumers.

 

The next wave of AI technological breakthroughs may not arise from feeding more data into Gen AI large language models (LLM). This status quo seems to favor only the long prevalent incumbent tech titans due to the large sunk costs of training Gen AI LLMs. Instead, the next wave of AI technological advancements should arise when the top tech titans apply smarter, faster, and better machine-learning algorithms to challenge the previous Gen AI LLMs such as Microsoft-OpenAI ChatGPT, Google Gemini, Meta Llama, and Anthropic Claude. Some recent developments from DeepSeek and Alibaba Qwen seem to promote positive progress in this new direction. As of mid-March 2025, we believe the current Gen AI LLM bellwethers include: Microsoft-OpenAI ChatGPT and Copilot, Anthropic Claude, Meta Llama, Perplexity, Google Gemini, Alibaba Qwen, DeepSeek, Amazon Nova, Mistral, and Twitter xAI Grok.

 

Why is American exceptionalism good for global stock market investors?

In the broader context of global economic history, the concept of U.S. exceptionalism refers to the fact that the American stock market has historically outperformed those stock markets of other countries due to the rare and unique fundamental factors and competitive forces in the U.S. real economy and financial system. Over the past 60 years, U.S. stocks have often delivered higher returns, in the common forms of dividends, share repurchases, and capital gains, in comparison to global counterparts. This historical outperformance strengthens the broad and pervasive perception of American stock market superiority. The U.S. promotes a rare and unique culture of discipline in both innovation and entrepreneurship, especially in Gen AI technology. In America, this core culture of discipline helps drive smarter, faster, and better economic growth, employment, and price stability over long time horizons. In addition, the U.S. provides both deep and liquid capital markets to new business ventures. Hence, it is relatively easy and straight-forward for co-founders and entrepreneurs to raise capital with tradable stocks and bonds. Also, the U.S. regulatory framework is generally quite supportive of new business ventures, investments, and strategic alliances. In global trade, finance, and technology, the greenback remains the world’s reserve currency, ensures financial stability, and facilitates cross-border transactions, payments, wire transfers, and other money orders. The U.S. real economy and its liquid stock market continue to promote a broader variety of diverse investment opportunities for institutional investors and retail investors worldwide.

 

Although such historical trends are significant, some economists continue to debate whether perpetual U.S. exceptionalism is still an open controversy and passes the test of time. Global economic shifts, trade disputes, technological advancements in several other countries such as China and Russia, and massive changes in U.S. investor sentiment etc can all influence future stock market performance. Today, U.S. national debt, fiscal deficits, and geopolitical risks start to challenge continual American exceptionalism. In essence, U.S. exceptionalism often suggests that the U.S. stock market offers a rare unique favorable macro environment for investors worldwide, even though past performance should not be taken as a rock-solid guarantee of future performance.

 

The current high stock market concentration serves as one of the mainstream reasons for U.S. investors to further diversify exposures across asset classes, regions, and strategies. The historically optimal portfolio mix of 60% stocks and 40% bonds remains empirically valid, relevant, profitable, and reasonable in a fundamental view. In light of the still-solid sales and profits in the AI-driven sections of Corporate America, we believe the optimal portfolio combo of 60% stocks and 40% bonds continues to serve as the mainstream economic engine for the global asset management industry, specifically BlackRock, State Street, and Vanguard. U.S. investors need to revisit their optimal choices of AI-driven stocks with new fundamental competitive moats, substantial safety margins, positive network effects, cost economies, and information cascades. From Apple ($AAPL), Amazon ($AMZN), and Microsoft ($MSFT) to Meta ($META) and Google ($GOOG), these tech titans rely on the steady flows of high-end semiconductor microchips, graphical processing units (GPU), and other quantum advances to make iterative continuous improvements for their Gen AI large language models (Gen AI LLM). As of March 2025, we believe the current Gen AI LLM bellwethers include: Microsoft-OpenAI ChatGPT, Google Gemini, Meta Llama, Anthropic Claude, Perplexity, Alibaba Qwen, DeepSeek, Amazon Nova, Mistral, and Twitter xAI Grok.

 

This analytic essay cannot constitute any form of financial advice, analyst opinion, recommendation, or endorsement. We refrain from engaging in financial advisory services, and we seek to offer our analytic insights into the latest economic trends, stock market topics, investment memes, personal finance tools, and other self-help inspirations. Our proprietary alpha investment algorithmic system helps enrich our AYA fintech network platform as a new social community for stock market investors: https://ayafintech.network.

We share and circulate these informative posts and essays with hyperlinks through our blogs, podcasts, emails, social media channels, and patent specifications. Our goal is to help promote better financial literacy, inclusion, and freedom of the global general public. While we make a conscious effort to optimize our global reach, this optimization retains our current focus on the American stock market.

This free ebook, AYA Analytica, shares new economic insights, investment memes, and stock portfolio strategies through both blog posts and patent specifications on our AYA fintech network platform. AYA fintech network platform is every investor's social toolkit for profitable investment management. We can help empower stock market investors through technology, education, and social integration.

We hope you enjoy the substantive content of this essay! AYA!

 

Andy Yeh

Co-Chair

Brass Ring International Density Enterprise (BRIDE) © 

 

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