Category: Chart of the Week

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.

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.

The New Face of Emerging Markets

The MSCI Emerging Markets Index has undergone a significant structural transformation in recent years. For much of the past decade, China dominated the benchmark, but Taiwan now represents the largest country in the index at roughly 27%, with South Korea close behind at around 23%. After reaching nearly 40% at the end of 2020, China’s weight in the index now sits below 20%. This shift has largely been driven by the strength of Taiwan and South Korea in the semiconductor space and the global AI infrastructure buildout. For example, Taiwan Semiconductor Manufacturing Company (TSMC), the world’s leading contract chip manufacturer and a critical supplier of the advanced semiconductors used in AI accelerators, has seen its revenues, margins, and market capitalization expand significantly in the last five years. TSMC now represents nearly 15% of the MSCI Emerging Markets Index. Additionally, South Korean companies Samsung and SK Hynix have become global leaders in memory semiconductors, particularly high-bandwidth memory chips, which are essential for training and operating large AI models. Samsung and SK Hynix constitute roughly 9% and 7% of the MSCI Emerging Markets Index, respectively.

This change in index leadership carries important implications for investors. Strong performance of a relatively small group of semiconductor companies has led to an uptick in concentration within passive emerging market funds and tied benchmark performance more closely to AI-related chip demand. The lower weighting of China in the index, meanwhile, reflects both weaker relative performance for Chinese companies and the broader investor preference for markets more directly connected to AI infrastructure spending. As a result of these trends, the MSCI Emerging Markets Index increasingly reflects advanced semiconductor leadership rather than the diversified growth of emerging economies, heightening both country- and company-specific risks. For instance, geopolitical tensions involving Taiwan, supply chain disruptions, or a meaningful slowdown in AI capital expenditures could materially alter recent performance trends. This dynamic reflects a broader shift in where value creation is occurring across emerging markets and is likely to persist as long as AI-related semiconductor demand remains strong.

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.

The “Magnificent One”

Over the last few years, equity markets have been defined by a group of stocks often referred to as the “Magnificent Seven” (Alphabet, Amazon, Apple, Meta, Microsoft, NVIDIA, and Tesla). These stocks represent roughly 34% of the S&P 500 Index, leading to meaningful concentration risk and an outsized influence on overall index returns. In fixed income, on the other hand, the Bloomberg U.S. Aggregate Bond Index could be referred to as the “Magnificent One” given the extent to which it serves as a bellwether for the broader asset class. The index is comprised of four sub-indices: Treasuries, Government-Related, Corporates, and Securitized. Like the S&P 500 Index, however, this benchmark is not immune to concentration risk, as issuers that borrow the most maintain the largest weights within the index. More than 80% of the securitized sector, for instance, is comprised of Fannie Mae and Freddie Mac mortgage-backed securities, while Ginnie Mae mortgage-backed securities represent an additional 10% of this sector.

Prior to 2008, securitized bonds were the largest component of the index, fueled by the growth of the mortgage market and the issuance of mortgage-backed securities by Fannie Mae and Freddie Mac. Following the Global Financial Crisis, the U.S. Treasury embarked on a borrowing bonanza, with Treasury issuance surging to $760 billion in the 2008 fiscal year. Net borrowing jumped again in 2018 after the passage of the 2017 Tax Cuts and Jobs Act and continued to rise through the COVID-19 pandemic. The U.S. budget deficit is now expected to widen to more than $3 trillion in the next 10 years, and these dynamics have impacted the constitution of the Bloomberg U.S. Aggregate Bond Index. While not all Treasuries are eligible for index inclusion, the overall weight of Treasuries in the benchmark has grown from roughly 25% to 46% over the last two decades and could climb higher in the years ahead. Treasuries are not the only source of U.S. government risk in the Bloomberg U.S. Aggregate Bond Index. As noted above, the securitized sector is heavily exposed to bonds issued by government-sponsored entities (e.g., Ginnie Mae, Fannie Mae, and Freddie Mac). Ginnie Mae mortgage-backed securities are supported by the full faith and credit of the U.S. government, while securities issued by Fannie Mae and Freddie Mac have an effective government guarantee since the entities were placed under conservatorship in the wake of the Global Financial Crisis. Taken together, securities issued or guaranteed in some way by the U.S. government currently exceed 70% of the Bloomberg U.S. Aggregate Bond Index. While a default by the U.S. government is highly unlikely, prices of government-related securities can move adversely in response to persistent deficits, rising debt levels, higher interest costs, inflationary pressures, and geopolitical developments.

Concentration risk within the fixed income space can be reduced via active management, as actively managed strategies have greater flexibility in terms of sector positioning and diversification. To that point, a common trade among bond managers with an active focus is to strategically underweight Treasuries and Agency mortgage-backed securities in favor of corporate and structured credit exposures. This approach reduces investor exposure to the U.S. government and increases yield due to higher spread risk relative to a passive portfolio. Additional sources of diversification that active strategies can provide include non-dollar exposures (e.g., developed and emerging markets) and below-investment-grade credit.