Long Weakened

The global bond market is facing renewed pressure as investors demand higher yields to hold long-dated government debt, pushing borrowing costs in several developed economies to extreme levels relative to recent history. For instance, the 30-year U.S. Treasury yield sits at nearly 5.3% as of this writing, near its highest level since 2007, after rising more than 40 basis points in the last two months. Additionally, 30-year borrowing costs in France recently reached their highest level since 2008, long-term yields in Germany have moved to levels not seen in more than 15 years, 30-year gilt yields have approached 6%, and comparable Japanese yields are near record highs.

While some country-specific factors are contributing to this sell-off, many of the drivers are global in nature. For instance, governments are running significant deficits at a time when interest rates remain well above the exceptionally low levels that prevailed for much of the past decade. In the U.S., interest expenses on the national debt have become an increasingly important contributor to the budget deficit, with fiscal-year-to-date interest costs now above $1.1 trillion as higher Treasury yields raise the government’s financing bill. It is important to note that the current environment also differs from previous periods of rising deficits. Historically, fiscal deterioration has often occurred alongside economic weakness, prompting central banks to cut interest rates and provide support to government bonds. Today, however, governments are adding to borrowing needs while monetary policy remains relatively restrictive. This dynamic could keep upward pressure on long-term yields even if central banks eventually begin lowering short-term rates.

Another important development is the changing composition of sovereign bond market investors. While government bonds have traditionally benefited from steady demand from institutions (e.g., pension funds and other liability-driven entities), demographic changes, pension reforms, and regulatory developments are impacting that demand. Consequently, governments are increasingly dependent on private investors, who are generally more sensitive to valuation and expected returns. This dynamic is particularly important at the long end of the curve, where the additional yield investors require to own longer-dated securities (i.e., the term premium) can have an outsized impact on borrowing costs. Government debt is also competing with a rapidly expanding supply of corporate bonds, as the capital requirements associated with artificial intelligence infrastructure have prompted technology-oriented companies to raise unprecedented amounts of debt (much of which is concentrated in longer maturities). As a result, bond investors now have more opportunities to deploy capital, and issuers must compete for that demand by offering attractive yields. Inflation is another reason investors have become less comfortable locking in yields for decades. The conflict in the Middle East has pushed energy prices higher, raising concerns about renewed inflationary pressures and the possibility that central banks could be forced to maintain restrictive monetary policy for longer than previously anticipated. That risk is particularly problematic for long-duration bonds, which have prices that are highly sensitive to changes in interest rates and inflation expectations. It should be noted, however, that the recent increase in long-term yields has not been driven entirely by rising inflation expectations, as long-dated inflation breakevens have remained largely contained across major markets. Instead, a significant portion of the increase has come from higher real yields (i.e., the inflation-adjusted compensation investors receive for owning bonds). That distinction is important because if real yields continue to rise because investors are demanding greater compensation for fiscal and economic uncertainty, long-term bonds could remain under pressure even without a major acceleration in expected inflation. The deterioration in long-term borrowing conditions is already influencing how governments approach debt issuance. For instance, the United Kingdom has reduced its planned issuance of longer-dated bonds and increased its reliance on shorter maturities. The problem with this approach is that shortening maturities does not eliminate underlying fiscal burdens but rather shifts more debt into the near-term refinancing pipeline. This leaves governments more exposed to future interest-rate movements. The U.S. Treasury is also taking steps to support liquidity in the long-end of the market, recently doubling the size of planned buybacks of longer-dated Treasuries to at least $4 billion per operation. While this initiative may provide some near-term support, its initial impact was short-lived, underscoring the challenge policymakers face in addressing the broader fiscal and supply-demand forces driving long-term yields higher.

One of the key takeaways here is that the long ends of yield curves across major economies are increasingly being shaped by forces that extend beyond traditional monetary policy expectations, with even the U.S. Treasury taking steps to support demand and liquidity in longer-dated bonds. Additionally, investors should note that rising long-term yields raise the discount rates applied to future corporate earnings, potentially creating a difficult backdrop for growth-oriented companies whose valuations depend heavily on cash flows expected many years in the future. On the positive side, the repricing in long-duration bonds could eventually create opportunities for investors with fresh capital, as higher real yields provide a more attractive starting point for long-term fixed income returns. The key question is whether yields are now high enough to compensate investors for the fiscal, inflationary, and supply-related risks currently embedded in the market.

2026 Halftime Market Insights

This video is a recording of a live webinar held July 23 by Marquette’s research team analyzing the first half of 2026 across the economy and various asset classes as well as themes we’ll be monitoring in the coming months.

 

Our quarterly Market Insights series examines the primary asset classes we cover for clients including the U.S. economy, fixed income, U.S. and non-U.S. equities, hedge funds, real assets, and private markets, with commentary by our research analysts and directors.

Featuring:
Greg Leonberger, FSA, EA, MAAA, FCA, Partner, Director of Research
Frank Valle, CFA, CAIA, Associate Director of Fixed Income
James Torgerson, Senior Research Analyst
Fred Huang, Research Analyst
David Hernandez, CFA, Director of Traditional Manager Search
Evan Frazier, CFA, CAIA, Senior Research Analyst
Dennis Yu, Research Analyst
Amy Miller, Associate Director of Private Equity
Hayley McCollum, Senior Research Analyst

Sign up for research alerts to be invited to future webinars and notified when we publish new videos.

Under the Radar for the Second Half

The usual midyear version of these letters has touched on year-to-date performance as well as the most influential macroeconomic and market-specific variables to monitor over the last six months of the year. This time, however, I enlisted the help of some colleagues — Frank Valle, Evan Frazier, Fred Huang, and Weston Whalen — to identify more subtle yet materially influential factors to watch across the economy and capital markets. Make no mistake: the headline topics of Fed policy, interest rates, geopolitics, earnings, and overall diversification remain paramount to long-term investment success, but the following metrics will likely determine if the positive performance of 2026 continues for the second half of the year.

Wagging the Dog

Our most recent Chart of the Week publication discussed how the AI investment opportunity has expanded beyond the large technology platforms to include critical suppliers throughout the semiconductor ecosystem and highlighted the strong performance of SK Hynix. As the AI investment theme continues to evolve, another important development has emerged: the growing influence of leveraged investment products on the trading dynamics of AI beneficiaries. Unlike traditional exchange-traded funds, single-stock leveraged ETFs seek to deliver a multiple of a stock’s daily return, allowing investors to express high-conviction views with magnified exposure. The SK Hynix Daily 2x Leveraged ETF, for example, attracted approximately $13 billion in assets after its October 2025 launch, and its success has prompted a wave of similar products. Indeed, following SK Hynix’s recent U.S. listing, issuers have begun launching leveraged ETFs tied to its U.S.-traded shares, broadening access to investors outside Asia.

The structure of leveraged ETFs creates a notable market dynamic. To maintain target leverage levels, these funds must rebalance their positions at the end of each trading day. When SK Hynix shares rise, the ETF generally needs to increase its exposure by purchasing additional derivatives or shares. Conversely, when the stock falls, the ETF typically must reduce its exposure. As assets in these funds have grown, these daily rebalancing trades have become large enough to represent a meaningful portion of SK Hynix’s trading volume. This creates the potential for feedback loops. During periods of strong momentum, ETF rebalancing can add incremental buying pressure that further supports the stock price. Conversely, market declines can trigger additional selling as the funds reduce exposure. Although company fundamentals continue to drive long-term value, these mechanical trading flows can increasingly influence short-term price movements and contribute to periods of heightened volatility.

Recent events provide a clear example of this dynamic. After an extraordinary rally fueled by optimism surrounding AI infrastructure spending and SK Hynix’s successful U.S. market debut, sentiment reversed sharply. The largest leveraged ETF tied to the company has lost roughly 45% since its debut, while SK Hynix experienced one of its steepest single-day declines in years. The rapid reversal prompted South Korean regulators to publicly question whether single-stock leveraged ETFs had been approved too quickly, highlighting growing concerns that these products can exacerbate market swings during periods of market stress. The implications of this dynamic extend beyond SK Hynix itself, as the company now represents one of the largest constituents of South Korean equity benchmarks and has become an increasingly important holding within the broader MSCI Emerging Markets Index. As a result, pronounced swings in SK Hynix shares can ripple through passive investment vehicles, affecting a much broader universe of global investors. The company’s recent U.S. listing and the expansion of leveraged products tied to both its Korean- and U.S.-listed shares further increase the number of investors participating in these technical trading flows. What began as a niche investment vehicle tied to a single stock has the potential to influence market performance across international equity portfolios.

While the long-term investment case for companies enabling AI infrastructure remains compelling, the rapid growth of leveraged products serves as a reminder that market structure can influence prices alongside fundamentals. The recent reversal in SK Hynix illustrates that leverage is inherently two-sided: the same mechanisms that can accelerate gains during periods of optimism can also amplify losses when sentiment shifts. For long-term investors, distinguishing between short-term technical factors and underlying business fundamentals will remain increasingly important as the AI investment theme continues to mature.

The Modern Gold Rush

One of the enduring lessons of the California Gold Rush is that the greatest fortunes were often made not by the prospectors themselves, but by the businesses that supplied them with the essential “picks and shovels” needed in their pursuit of gold. As companies such as OpenAI, Anthropic, Alphabet, and others compete to develop increasingly sophisticated large language models, demand for the memory chips and semiconductors that power these technologies has surged, providing a significant tailwind for hardware manufacturers. The surge in demand for AI infrastructure has propelled memory chip manufacturers to record valuations. In 2026, SK Hynix, Samsung, and U.S.-based Micron each surpassed a $1 trillion market capitalization as memory has become one of the industry’s most valuable and sought-after commodities. Collectively, these three companies are now worth more than Saudi Aramco, Exxon Mobil, and Chevron (the world’s three largest oil companies), highlighting the extraordinary value investors are placing on the AI supply chain.

Microsoft, Meta, Amazon, and Alphabet are expected to spend more than $670 billion on AI-related capital expenditures in 2026, up from a combined $410 billion in 2025. This surge in investment has fueled unprecedented demand for memory chips, prompting Samsung and SK Hynix to commit more than $500 billion to expand semiconductor manufacturing capacity in South Korea. As investors continue to assess the winners and losers of the AI race, memory chip and semiconductor manufacturers have emerged as some of the market’s strongest performers.

Centers of Attention

The rapid buildout of artificial intelligence infrastructure is reshaping the U.S. investment landscape. According to recent Census Bureau data, spending on data center construction surpassed $50 billion in April for the first time, rising more than 28% from a year earlier and reaching a level that now exceeds public spending on transportation-related initiatives. The scale of this growth is striking, as monthly spending on data center construction is roughly sixteen times higher than it was a decade ago and has nearly tripled since the emergence of generative AI in late 2022. What began as a niche segment of the commercial real estate space has evolved into one of the largest and fastest-growing categories of nonresidential construction, driven by hyperscale cloud providers and technology companies racing to expand computing capacity for AI workloads.

The implications of this trend extend far beyond the technology sector. Data center development is becoming a significant source of demand for construction labor, electrical equipment, power generation, semiconductors, cooling systems, and industrial commodities such as copper. At the same time, the unprecedented power requirements of AI infrastructure are creating new constraints around electricity generation, transmission capacity, and permitting. These dynamics have prompted policymakers and utility services companies to rethink long-term infrastructure planning. While some projects face delays due to power availability and construction bottlenecks, broader trends suggest that AI-related capital expenditures will remain a powerful driver of economic activity for years to come. For investors, the beneficiaries of these developments are likely to extend well beyond the large technology firms, encompassing a wide range of “picks-and-shovels” providers across the industrials, energy, and digital infrastructure sectors.

The Best and Worst of Times

The classic novel A Tale of Two Cities by Charles Dickens begins with the line “It was the best of times, it was the worst of times…” While Dickens was describing the extreme contradictions of the late 18th century leading up to the French Revolution (i.e., comfort for the aristocracy and hardship for the poor), this line could just as easily apply to the current economic environment in the United States, which is marked by a stark divergence between consumer confidence and investor behavior. Specifically, recent University of Michigan consumer sentiment readings have fallen to some of the weakest levels in decades, reflecting persistent frustration on the part of many Americans over inflation, elevated interest rates, high gasoline prices, and job security. Consumers remain particularly sensitive to the cumulative impact of several years of higher prices, even as headline inflation has moderated from its post-pandemic peaks. Surveys from both the University of Michigan and the Conference Board suggest U.S. households are increasingly worried about future economic conditions and weakness in the labor market. At the same time, equity markets have largely shaken off these concerns given enthusiasm surrounding artificial intelligence and expectations for longer-term productivity gains. Indeed, the S&P 500 Index has notched gains of more than 17% in each of the last three full calendar years and has advanced more than 9% in 2026 as of this writing. This strong performance has led to higher equity market valuations. As can be seen in this week’s chart, the Shiller Cyclically Adjusted Price-to-Earnings (CAPE) Ratio for the S&P 500 Index, which compares prices to average inflation-adjusted earnings over the prior 10 years to smooth out short-term volatility, sits at roughly 42. This figure is well above historical average levels and signals that investors continue to pay a significant premium for future earnings growth despite weaker consumer sentiment. Many have described this dynamic as a “tale of two markets,” as investors reward companies with outsized earnings potential and the ability to generate technological disruption even as households cut back on discretionary spending and grow more cautious about the economy.

A major driver of the divergence described above is the way in which financial asset ownership is distributed in the United States. A recent estimate from the Federal Reserve indicates that the top 10% of American households own roughly 90% of all U.S. corporate equities and mutual fund shares, meaning recent market gains have created a wealth effect that continues to support spending among affluent consumers, even as lower- and middle-income households face significant pressures. This divergence also highlights the forward-looking nature of financial markets, as equity investors are often pricing in anticipated earnings growth and future monetary policy as opposed to current economic conditions. Most consumers, on the other hand, respond more directly to present-day realities such as grocery bills, gasoline prices, and the perceived stability of the labor market. Whether this sentiment gap ultimately closes due to consumer confidence that is recalled to life or equity valuations that face the guillotine of market repricing remains one of the key questions facing investors in the near term.

This Too Shall Reconstitute

Rooted in medieval Persian Sufi thought, the adage “this too shall pass” speaks to the fleeting and impermanent nature of the human condition. For investors, this aphorism can serve as a useful framework for understanding the constantly evolving composition of the upper end of the U.S. equity market. As this week’s chart shows, the top 10 constituents of the S&P 500 Index have changed dramatically over the last 40 years, with each new decade seeing both additions to and subtractions from this basket of companies.

In 1985, the top of the S&P 500 Index was heavily weighted toward industrial conglomerates, energy producers, and legacy financial and telecommunications firms such as IBM, Exxon, AT&T, and General Electric. This composition reflected an economy still anchored in manufacturing, physical infrastructure, and regulated industries with durable but relatively slow-moving competitive dynamics. Capital intensity, domestic scale, and regulatory barriers to entry helped entrench incumbents, allowing a small set of diversified conglomerates and commodity-linked businesses to dominate equity indices. As can be observed in this week’s chart, the top 10 constituents represented roughly 21% of the S&P 500 Index in 1985. In contrast, the top 10 constituents at the end of last year represented more than 40% of the benchmark, with technology-oriented companies like NVIDIA, Apple, Microsoft, Alphabet, Amazon, and Meta topping the benchmark and accounting for an outsized share of index earnings and returns in recent years.

The transition between these two regimes did not occur abruptly but rather through decades of structural changes, including the rise of the digital economy, the decline in manufacturing’s share of GDP, and the increasing importance of intangible assets such as software, data, and intellectual property. Indeed, the 1990s and early 2000s saw the rise and consolidation of the internet economy, which led to the reshaping of information, communication, and commerce. The years following the Global Financial Crisis further accelerated the dominance of scalable, asset-light business models, while low interest rates and abundant liquidity disproportionately benefited high-growth technology firms. At the same time, several former index leaders either stagnated, were disrupted, or lost relative economic relevance, leading to a gradual but persistent turnover at the top of the index.

Against this backdrop, the current composition of the S&P 500 Index should not be viewed as fixed, but rather as a snapshot of a specific moment in time. If history is any indication, the next decade will likely bring another reshuffling of top index constituents as new technologies, industries, and business models emerge. For investors, this suggests that maintaining broadly diversified equity exposure while remaining disciplined around rebalancing is prudent, as market leadership, however dominant it appears at a given time, has historically been transient rather than permanent.

1Q 2026 Market Insights Webinar

This video is a recording of a live webinar held April 16 by Marquette’s research team analyzing the first quarter across the economy and various asset classes as well as themes we’ll be monitoring in the coming months.

Our quarterly Market Insights series examines the primary asset classes we cover for clients including the U.S. economy, fixed income, U.S. and non-U.S. equities, hedge funds, real assets, and private markets, with commentary by our research analysts and directors.

Featuring:
Greg Leonberger, FSA, EA, MAAA, FCA, Partner, Director of Research
James Torgerson, Senior Research Analyst
Fred Huang, Research Analyst
David Hernandez, CFA, Director of Traditional Manager Search
Evan Frazier, CFA, CAIA, Senior Research Analyst
Dennis Yu, Research Analyst
Hayley McCollum, Senior Research Analyst

Sign up for research alerts to be invited to future webinars and notified when we publish new videos.

If you have any questions, please send our team an email.

 

A Bug in the Software

Recent market dynamics in the software sector reflect a sharp shift in investor sentiment driven primarily by concerns that advances in artificial intelligence could fundamentally disrupt traditional software business models. Public software-linked equities have sold off broadly (even as many companies continue to deliver solid earnings) because investors are increasingly focused on long-term structural risks rather than near-term financial performance. Indeed, estimates for longer-term earnings growth for these businesses have started to decline despite stable or improving near-term outlooks, highlighting growing skepticism around the durability of pricing power, competitive moats, and growth trajectories in an AI-enabled environment. Since the end of October, the S&P North American Technology Software Index has fallen by roughly 30%. These concerns have now spread beyond equities into credit markets, where leveraged loan investors are rapidly reducing exposure to software-related borrowers. Many software loans that entered 2026 priced at or near par have since declined as investors reassess the sector’s credit risk profile, reflecting fears that AI-driven disruption could weaken cash flows and increase default risk for highly leveraged issuers. Specifically, the Morningstar LSTA U.S. Leveraged Loan Index has dropped by around 6% since the start of 2026.

This repricing across equity and credit markets underscores a key shift in sentiment. Software, long viewed as one of the most predictable and resilient sectors of the economy due to recurring revenue models and high margins, is now facing simultaneous multiple compression in equities and widening spreads in credit. While fundamentals remain relatively intact today, markets are increasingly discounting a wider range of potential outcomes for software-linked businesses, creating heightened volatility and a more selective environment in which investors are demanding clear evidence of AI resilience and sustainable competitive differentiation.