Author: cvernon

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

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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.

To CV or Not to CV?

Since traditional exit routes have remained constrained in recent years due to higher interest rates, valuation gaps, and a subdued IPO market, continuation vehicles (“CVs”) have become an increasingly important liquidity tool for private equity investors. At a high level, CVs are investment structures in which a sponsor transfers one or more portfolio companies from an existing fund into a newly formed fund, allowing existing investors to either cash out or roll their investment while providing the manager with additional time to create value. While CVs do help to mitigate a challenging exit environment, they are also raising several considerations for fund investors. For instance, many are concerned about potential conflicts related to valuation, governance, and asset selection given the fund manager’s direct involvement in both the sale and acquisition process. These concerns often call for active discussions about asset valuation if third-party sales are considered. The economics of CVs have also been called into question by some, as the transfer of assets into a new vehicle can reset management fees and performance incentives for fund managers. Moreover, some CV structures include performance-related tiered carried interest arrangements, which may eventually result in a higher-than-industry-average fee paid by fund investors. Additionally, limited partners are closely examining the quality of assets being transferred since CVs can potentially reduce the impact of underperforming portfolio companies on a primary fund’s track record. CVs also offer less visibility into a fund manager’s ability to achieve traditional third-party exits, which remains an important measure of execution and realization capabilities.

More recently, the emergence of “CV-squared” transactions (in which assets move from one CV into another) has led to even more discussion around the ultimate path to liquidity and the alignment of incentives between fund managers and investors. While the rise of CVs is clearly a response to a market with constrained traditional exits, it is important to note that these structures are creating a more circular liquidity ecosystem that may make it harder for investors to evaluate portfolio company quality and exit opportunities. Ultimately, while continuation vehicles can provide valuable flexibility in a difficult exit environment, investors should carefully evaluate each transaction to ensure that governance, valuation, and incentive structures remain aligned with their long-term interests.

Balancing Growth and Income in Infrastructure

This week’s chart highlights the varying return profiles across key infrastructure sectors by illustrating the split between income and capital appreciation. Digital infrastructure stands out given the extent to which total returns are driven primarily by capital gains with minimal contributions from current income. This reflects strong investor demand for data center platforms, where development pipelines continue to expand rapidly alongside accelerating AI adoption, cloud computing growth, and increasing data consumption. However, elevated entry valuations and ambitious growth assumptions are leading to a wider range of potential investment outcomes for this space as capital markets test the sustainability of current expectations.

In contrast, energy transition sectors, renewables, utilities, and transportation assets exhibit a more balanced profile, with a larger portion of returns generated via recurring cash flows and contracted revenues. As the buildout of data center capacity intensifies, significant investment will also be required in the infrastructure needed to power these facilities. This dynamic is creating attractive opportunities in adjacent sectors including renewable generation, battery energy storage, and grid modernization. While these investments may not offer the same headline return potential as digital infrastructure, they often benefit from long-term contracted cash flows, multiple pathways to value creation, and return characteristics that may be more suitable for core and core-plus infrastructure investors seeking durable income and downside protection.

Commodities: An Overview of the Asset Class

Commodities represent a unique asset class within global financial markets. Like equities and bonds, commodity prices are influenced by the macroeconomic environment, geopolitical events, and technological developments. However, because commodities are tangible assets, their prices are also directly affected by physical supply-and-demand dynamics, weather patterns, and other factors unique to underlying resource markets. Recent structural trends, including rising demand for metals within the technology and renewable energy sectors, have created secular tailwinds for certain commodities that potentially complement the asset class’s traditionally cyclical characteristics. Additionally, evolving energy market dynamics may provide further structural support. Years of underinvestment in conventional energy production coupled with recent geopolitical conflicts and damage to critical infrastructure in the Middle East have increased concerns about the long-term resilience of global energy supply chains, potentially supporting elevated energy prices relative to historical norms. Simultaneously, global inflationary pressures and conflicts across the world have renewed interest in commodity allocations as a hedge against macroeconomic uncertainty and geopolitical strife. This paper examines the viability of commodities in institutional portfolios by exploring the dynamics of commodity cycles and demand drivers, analyzing the historical performance of the asset class, and outlining risk management considerations. By reviewing both opportunities and challenges, the paper aims to provide a balanced and educational assessment for institutional investors seeking to understand the role of commodities in modern portfolios.

The VC Convergence Era

When Benchmark, one of Silicon Valley’s most renowned early-stage venture capital firms, closed $2 billion across two new funds this month (including its first-ever dedicated growth vehicle at roughly $1.3 billion), headlines were made. For nearly two decades, Benchmark was one of the industry’s most disciplined organizations, with funds capped at around $500 million and a conviction that backing the right companies at the right prices was preferable to deploying capital at scale. That thesis ultimately produced one of the strongest track records in venture capital.

Benchmark’s more recent moves are indicative of broader market dynamics. Indeed, VC-backed businesses are staying private for longer, an increasing share of enterprise value is being created after the traditional venture stage, and the capital required to participate in the initial phases of a company’s growth is now greater than what early-stage funds were built to provide. According to PitchBook, the median time to exit for unicorn companies was 9.2 years as of the end of last year. For an early-stage investor, that figure represents nearly a decade during which ownership stakes are tested via various financing rounds. For instance, a $400 million fund with pro-rata rights can participate in early rounds, but maintaining meaningful ownership across 10 years of financing requires capital that traditional venture funds were not designed to deploy. This means that the investor who backed the right company at the seed stage but lacked the capital to hold the position through subsequent financing rounds effectively did the difficult work of selection for someone else’s benefit.

In recent time, leading firms including Founders Fund, a16z, Thrive Capital, and Sequoia have launched dedicated growth vehicles, aiming to build out the capacity required to support portfolio companies across full lifecycles and avoid handing them off at the growth stage. It is important to point out, however, that growth investing is not simply venture investing with larger check sizes. Specifically, entry valuations are higher at this stage, requiring investors to underwrite not just a company’s potential but the return achievable at a given price. To that point, outcomes depend more heavily on public market conditions and exit timing, which are factors that no investor can fully control. In conclusion, venture capital is entering an era of convergence in which the most competitive firms are defined not by the stage at which they invest, but by their ability to support exceptional companies across a full lifecycle, meaning growth capabilities are increasingly becoming table stakes for venture firms seeking to build enduring franchises.

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.

How to Launder Your Volatility

Hi, James Torgerson here! Volatility can be an unsightly blemish on portfolios and lead to inferior risk-adjusted returns. Private credit is just the thing investors need to launder away the pesky volatility that drags down Sharpe ratios! Those looking for an easy way to remove the stains of volatility from their portfolios should look no further! Call the number at the bottom of your screen now! Smoother portfolio returns await!

While the above may sound like a cheesy infomercial, an allocation to private credit can indeed provide numerous benefits, including an income premium, stricter covenants, and attractive long-term returns. Additionally, the frequency with which private credit portfolios are marked (primarily monthly or quarterly) can lead to smoother headline volatility and higher risk-adjusted returns when compared to public credit.

While there is no publicly traded private credit index, listed Business Development Companies (BDCs) can be used as a proxy for the asset class. Listed BDCs are exchange-traded investment vehicles that hold private loans to small-to-mid-sized companies and can offer insights into the differences between the stated volatility of public and private credit portfolios. The chart above shows the cumulative returns for both the publicly listed MVIS US BDC (which is valued on a daily basis) and the Cliffwater Direct Lending (which is valued on a quarterly basis) indices. Additionally, the chart shows the Sharpe ratios (i.e., risk-adjusted returns) for these indices, as well as that of bank loans, which are often used as another proxy for direct lending. While the cumulative returns for the BDC and direct lending indices are directionally similar, the publicly traded BDC index exhibits significantly more volatility than the private index (even though the underlying assets are relatively similar in terms of credit risk). Further, when measured from the beginning of 2010 through the end of March, the Sharpe ratio of the direct lending index is 3.3, while the publicly traded BDC and leveraged loan indices show Sharpe ratios of 0.4 and 0.8, respectively, for that time period. Clearly, by listing privately and employing a valuation lag, private credit is able to launder away a significant percentage of a portfolio’s volatility.

To be clear, private credit likely has a place in many institutional portfolios, and it is important to remember that the asset class is comprised of much more than just direct lending. However, as the asset class continues to grow and retail investor participation increases, readers should be aware that lower private credit fund-level volatility does not necessarily mean lower volatility of underlying assets.