Author: cvernon

2026 Market Preview

This video is a recording of a live webinar held January 15 by Marquette’s research team analyzing 2025 across the economy and various asset classes as well as themes we’ll be monitoring in 2026.

 

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
Catherine Hillier, Senior 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
Chad Sheaffer, CFA, CAIA, Associate Director of Private Credit

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

Where Should Investors Land on the Aggregate Continuum?

Contrary to widespread belief, fixed income aggregate strategies offer a continuum of active risk and return profiles. While aggregate strategies broadly aim to provide income, diversification, and liquidity, varying degrees of excess return exist. Investors must choose what suits their active risk and return goals.

Fixed income mandates are described by their beta and benchmarked to a similarly named index. For example, long credit is benchmarked to the Bloomberg Long Credit Index and high yield is benchmarked versus the Bank of America High Yield Master II Index. Once a beta is selected, then an alpha objective is chosen for the mandate. Some mandates in the universe have an alpha target of benchmark plus 50 basis points (bps), while others target an excess return of 100bps or more.

However, this is not true for aggregate strategies. The beta and index are the Bloomberg Aggregate Index. Rather than having different objectives, aggregate mandates have different “asset classes.” The aggregate continuum should not be thought of as different asset classes, but rather different active risk and return profiles.

This white paper outlines considerations for investors when choosing a fixed income aggregate strategy, including an overview of the Bloomberg Aggregate Index, how investment managers can generate active risk, excess return targets, and the important distinction between risk and active risk.

I Drink Your Milkshake

The capture of Venezuelan president Nicolás Maduro is a watershed moment for a country whose natural resource economy has been managed by an interventionist, state-centric regime for nearly 30 years. Indeed, Maduro’s detention effectively ends the command-and-control model that had long governed Venezuela’s oil sector, in which the state-owned oil company PDVSA functioned largely as a political instrument rather than a commercial enterprise. Once a technically competent producer, PDVSA was hollowed out in the early 2000s as revenues were diverted to fund government spending, skilled workers were purged, and maintenance and reinvestment were neglected. As can be seen in this week’s chart, this led to a steep decline in Venezuelan production and export capacity. For global markets, the immediate significance of the ousting of Maduro lies less in the regime change itself than in the potential reopening of one of the world’s largest hydrocarbon endowments after years of sanctions and operational decay.

In the short run, Venezuelan oil exports are likely to increase modestly but unevenly. Although the nation’s output has already started to recover from its 2020 trough due to limited sanctions waivers and ad hoc deals, infrastructure constraints remain severe. Years of deferred maintenance have left pipelines, ports, and storage facilities in poor condition, while a shortage of skilled labor and reliable power continues to limit throughput. As a result, any additional barrels reaching export markets will likely come primarily via better utilization of existing fields rather than large-scale new investment, at least over the coming months. Deals that redirect crude toward the United States (particularly heavy oil suited for Gulf Coast refineries) could shift trade flows quickly, but they do not solve the deeper structural problems of the industry. Near-term export gains are therefore likely to be measured in hundreds of thousands of barrels per day rather than a return to Venezuela’s historical multi-million-barrel output.

Over a longer time horizon, the toppling of Maduro could reshape Venezuela’s oil sector more profoundly by altering its relationship with foreign capital and global commodities markets. International oil companies have long viewed Venezuela’s reserves as attractive but effectively uninvestable due to sanctions risk, opaque governance, a history of expropriation, and weak contract enforcement. A political realignment raises the possibility of a gradual normalization of commercial terms, including joint ventures, profit-sharing mechanisms, and clearer legal protections for market participants. However, analysts widely agree that rebuilding production capacity would be a long and risky process, likely requiring tens of billions of dollars and many years of stable policy. Further complicating matters is Venezuela’s exceptionally high methane intensity, which makes its crude oil among the most emissions-intensive in the world and increasingly problematic for buyers facing stricter environmental standards. Addressing these environmental liabilities would add both cost and time to any meaningful expansion of exports.

Beyond oil, Venezuela’s broader natural resource abundance adds an additional layer of significance to the recent change in leadership. Specifically, the country sits atop substantial reserves of gold and other strategic minerals, and renewed export capacity could feed into a broader bull market in commodities if supply constraints ease. It is important to remember, however, that recent events do not automatically translate into a clean political transition, and the near-term outlook for Venezuelan commodities exports remains shaped by institutional fragility, security risks and unresolved questions about who exercises authority over production, contracts, and revenues. Ultimately, Maduro’s capture creates an opening rather than a resolution, as it increases the probability that Venezuelan resources re-enter global markets at scale, but it does not eliminate the risks that have defined the country’s commodities sector for years.

Brains Over Brawn?

The development of artificial intelligence is advancing along two largely distinct paths. The first centers on generative AI powered by large language models, with the long-term objective of creating systems that can reason across domains at levels superior to those of human beings. The second focuses on embodied intelligence (i.e., robotics). In this space, the objective is not abstract reasoning but rather the deployment of capable machines that can operate effectively in the physical world. Over the last five years, capital and attention have overwhelmingly gravitated toward companies involved in generative AI, with the Bloomberg Artificial Intelligence Index up a staggering 276% in that time. Robotics, by comparison, has been widely viewed as a longer-dated theme, with the Bloomberg Robotics Index up only 77% over that same period (even less than the S&P 500 Index return of 134%). These dynamics can be observed in this week’s chart.

Going forward, there are reasons to believe that this performance trend may shift in the years ahead. For instance, human-level general intelligence could be far more distant than markets currently assume, and language models may not prove sufficient to reach it. At the same time, practical robots (e.g., warehouse automation, humanoid assistants, etc.) appear closer to commercial reality than previously believed, particularly in aging societies facing persistent labor shortages. One possible accelerant for robotics companies in the years ahead is the use of advanced simulation. By training in virtual environments, robots can acquire motor skills and coordination far more rapidly than through physical trial and error alone, potentially pulling forward adoption timelines relative to current investor expectations. Importantly, transformative impact does not require robots to achieve artificial general intelligence but rather functional capability (i.e., the ability to move objects, operate safely, and sustain useful work with sufficient battery life). Commercial momentum in robotics is already building. In 2024, for example, Agility Robotics opened a manufacturing facility in Oregon with capacity to produce up to 10,000 humanoid units annually, and Amazon has now begun testing Agility’s robots in its warehouses. Additionally, companies like Tesla are showcasing humanoid prototypes performing increasingly fluid physical tasks, and BYD has signaled interest in future household robotics. While price points remain prohibitive for mass adoption today, several structural forces are converging to improve the economics of robotics. Manufacturing costs are declining as scaling drives down prices for components like sensors and actuators, while improvements in AI models are enhancing robotic perception and control. Taken in tandem with the fact that generative AI leaders are currently investing heavily in costly, power-hungry data centers, it is fair to say that a once slower-moving, less glamorous segment of the AI ecosystem may now benefit from relative capital efficiency.

Despite these developments, markets continue to assign a significant valuation premium to generative AI over robotics, which can also be observed in the chart above. Factor analysis helps explain part of the gap, as AI-heavy indexes skew toward momentum and growth while robotics-oriented benchmarks exhibit greater exposure to value, quality, and, in some cases, even dividend income. Further, the generative AI complex is dominated by large technology platforms including Alphabet, Microsoft, and NVIDIA, whereas robotics companies tend to be more industrial in nature (e.g., automation specialists, automakers, and emerging consumer-robotics firms). This valuation disconnect suggests that investors may be overemphasizing long-term breakthroughs in cognition while underappreciating near-term progress in physical automation, especially as physical robots transition from research environments into factories, homes, and hospitals. Indeed, while much of today’s excitement centers on artificial brains, it may ultimately be robotic brawn that drives the next leg of growth within the technology sector.

Glass Half Empty

While the holiday season was once marked by bustling bars, readers may notice that nightlife isn’t what it used to be. Indeed, alcohol-oriented companies, long considered stable components of the Consumer Staples sector thanks to recession-proof attributes, are struggling to regain momentum after a post-pandemic boom. As can be seen in this week’s chart, the Bloomberg Global Alcohol Index, which tracks over 50 of the world’s top listed beer, wine and spirits producers, has exhibited a roughly 46% decline since the summer of 2021. Shares of European giants such as Diageo, Pernod Ricard, and Remy Cointreau now hover near multi-year lows, with many global peers notching similar declines.

There are likely many factors contributing to these performance headwinds for alcohol-oriented businesses, including rising costs, post-pandemic societal shifts (i.e., higher levels of solitude), and healthier lifestyle choices being pursued by consumers. Interestingly, a recent Gallup survey indicates that alcohol consumption by U.S. adults sits at a staggering 90-year low, with members of the Millennial and Gen-Z cohorts increasingly viewing drinking as less fashionable. This change in behavior is compounded by the rise of GLP-1 drug use for weight loss, as early indicators suggest that these medications are catalyzing behavioral changes that have led to a greater emphasis on health and well-being. Additionally, the options for partygoers outside of alcohol have rapidly expanded in recent years, with global consumers increasingly turning to non-alcoholic beverages and cannabis to fuel their holiday cheer. While demand for alcohol is unlikely to disappear completely, alcohol-oriented businesses will surely need to innovate and diversify to meet changing consumer preferences based on the trends described above.

The Secondary Option

Private equity is known for being an illiquid asset class, with investments typically locked up for several years and limited options to access cash before a fund winds down. Investors have largely accepted these restrictions in exchange for the potential of higher returns, but this lack of liquidity has become a challenge more recently. For instance, DPI (distributions to paid-in capital) as a percentage of net asset value for 2024 was 12%, significantly lower than the 25-year average of 21%. As a result of these dynamics, there has been rapid growth in the private equity secondary market, which allows investors to sell their existing stakes in ongoing private equity funds. Indeed, what was once a niche option for distressed sellers is now a mainstream tool for managing portfolios, with global secondary market transactions on pace to exceed $200 billion in 2025. This figure would constitute a record high. Interestingly, more than 50% of secondary transactions in the first half of this year came in the form of Limited Partner (“LP”)-led secondaries, which occur when existing LPs sell fund interests to other investors.

The rise of LP-led secondaries is about more than investors simply “cashing out.” Specifically, LPs may tap the secondary market to rebalance portfolios when private equity exposure becomes too high, move away from underperforming funds, or free up capital to invest in new opportunities. Institutions of all types are embracing this strategy. For instance, the University of Illinois Foundation recently announced the sale of roughly $245 million of net asset value of private market assets, aiming to reduce exposure to high-risk, illiquid positions and reposition its endowment for greater long-term stability. Additionally, CalPERS announced a potential $3 billion secondary transaction earlier this year, and Yale University is currently in talks for its first-ever secondaries sale to convert older private equity holdings into liquid assets for reinvestment. These developments reflect a broader trend among institutional investors seeking flexibility and liquidity amid a challenging private equity environment. Indeed, as private equity funds continue to hold assets for longer and exit activity remains slow, the secondary market may become a standard part of portfolio management for both large institutions and smaller investors in the years ahead.

Big “Issues” for Big Tech

While technology-oriented firms have made their presence known in equity markets for several years, these companies have made waves in the fixed income space recently as well. Companies such as Alphabet, Meta, and Oracle, which in the past have funded initiatives via balance sheet cash, have increasingly turned to the bond market to finance the buildout of AI-related infrastructure. Specifically, a total of nearly $240 billion worth of investment-grade bonds have been sold by technology giants on a year-to-date basis through the end of November. Some notable deals in 2025 include Meta’s $30 billion bond sale, the largest in the U.S. high-grade market this year, Oracle’s $18 billion issuance in September, and Alphabet’s deal that raised $17.5 billion in the U.S. and another €6.5 billion (roughly $7.5 billion) in Europe.

This surge in supply carries meaningful implications for the broader investment-grade corporate market, which is one of the most heavily traded areas of fixed income. For instance, the sheer volume of new issuance from technology companies can put upward pressure on corporate spreads as investors demand slightly higher yields (despite the strong balance sheets and generally low leverage of these firms). There is also the question of the potential return on AI-related spending (or lack thereof). Indeed, a recent MIT study found that around 95% of companies have yet to see any meaningful payoff from their generative AI efforts. At the same time, investors and creditors are growing more cautious, increasing their use of derivatives designed to pay out if specific technology firms fail to meet their debt obligations. That said, investment in AI-related infrastructure seems likely to continue at full speed in the years ahead, meaning technology firms may continue to tap the investment-grade market for financing.

Small Caps: Unprofitables Lead, Active Managers Lag, But Can it Last?

At the start of 2025, very few could have predicted the wild ride that awaited equity markets. After a volatile period that culminated on April 8, U.S. equities achieved several new all-time highs, with small-cap equities reaching a first all-time high since November 2021. Absolute returns have been substantial, as the Russell 2000 rose nearly 42% off the market bottom through October 31. Despite renewed volatility in November as expectations for another Federal Reserve rate cut fluctuated, small-cap equities have led large-cap equities since April 8. As is expected in the first six months of a bull market, low quality, including residual volatility, short interest, non-earners, and beta, propelled the small-cap market. Conversely, active managers favor high quality companies, typically characterized by high returns on equity, strong balance sheets, and low leverage. As a result, this factor backdrop is a known headwind for many active managers across the small-cap universe, and this bull market is no different.

An “Imbalancing” Act

Germany is on pace for a record-breaking trade deficit with China this year, with Chinese exports originally intended for the United States now flooding European markets. Specifically, Germany currently exhibits a trade balance with China of roughly -1.7% of German GDP, which is close to a multi-year low. Germany’s increasingly negative trade balance with China can be observed in this week’s chart. While trade imbalances are not necessarily cause for concern, this growing deficit is part of a long-term structural shift in the trade relationship between Germany and China. Despite ideological differences, the two countries have been economic allies since establishing a trade partnership in the early 2000s, which led to the exporting of German cars, machinery, and specialty chemicals to China. This, in turn, fueled economic growth in China, and the relationship benefited both countries for years (though not without growing concerns around potential economic dependence of Germany on China). This dynamic changed in 2020 given pandemic-induced supply chain shocks and China’s alignment with Russia at the outset of its invasion of Ukraine. These headwinds reaffirmed Germany’s commitment to diversifying its economic relationships, and last year the United States overtook China as Germany’s number one trading partner for the first time in nearly a decade. While China has reclaimed the top spot this year, trade between the two countries is not what it once was. For instance, many Chinese households now prefer the latest car model from BYD (a multinational manufacturing company domiciled in China) as opposed to the once coveted German Volkswagen. Chinese officials have also threatened to limit exports of certain rare earth minerals and semiconductor chips, which are crucial inputs for goods manufactured in Germany.

The future of this once vibrant and amicable economic partnership remains unclear. German manufacturers now face stiff competition from what was previously significant end-markets, and the country seems to be adopting the more cautious stance on China exhibited by the rest of Europe. Indeed, while some German firms are deepening their relationship with China to stay connected with technological innovation, the nature of aggregate German manufacturing may be changing, especially as the country’s economic output becomes increasingly tied to services rather than goods. Eventually, China and Germany will reach a trade equilibrium, though current trends suggest it will look vastly different from their prior decades of collaboration.

The Asymmetry of Unemployment

A fundamental characteristic of U.S. labor markets is the pronounced asymmetry in unemployment dynamics, as joblessness rises anywhere from three to five times faster during recessions than it falls during recoveries. This “sawblade” pattern has important implications for economic forecasting, monetary policy, and investment portfolio positioning. Amid recessionary conditions in the early 1980s, unemployment surged from 7.0% to 10.8% in just 16 months (an average increase of more than 0.2% per month). The subsequent recovery took 54 months, with unemployment declining at a rate of less than 0.1% each month on average. The Global Financial Crisis of 2008 exemplifies this pattern even more dramatically, as unemployment jumped from 5.0% to 10.0% in 22 months and normalized over a period of more than six years, during which time millions of workers faced extended joblessness. Most striking was the COVID-19 pandemic of 2020, when unemployment exploded from 3.5% to 14.7% in just two months (the sharpest spike in modern American history). While the initial recovery was faster than historical norms due to unprecedented fiscal and monetary stimulus, the unemployment rate still took 33 months to return to pre-pandemic levels. This illustrates that even with extraordinary policy support, labor market normalization remains gradual. The pattern described above reflects fundamental labor market frictions. On one hand, companies can execute mass layoffs within weeks when facing existential threats or demand shocks. At the same time, hiring is usually carried out with caution, as firms slowly restaff as confidence improves, workers require time to locate appropriate positions, and many require retraining for structural shifts in demand. Indeed, this friction is not a policy bug but rather a feature of how the labor market functions.

Understanding unemployment asymmetry is critical for investors today as the Federal Reserve navigates an increasingly complex challenge related to its dual mandate of stable prices and maximum employment. Specifically, the Fed faces an unprecedented data vacuum due to the recent government shutdown, and traditional labor market indicators are sending mixed signals. For instance, payroll growth has moderated but remains positive, initial jobless claims are elevated but have not reached recessionary levels, and the unemployment rate has risen yet remains relatively low. Some have also linked the rise of artificial intelligence to recent hiring trends, though it remains unclear whether these trends represent a meaningful secular shift in labor demand. Complications are intensified by inflation that remains stubbornly above the Fed’s 2% target. In short, looser monetary policy could lead to even higher price levels, while restrictive policy could trigger higher unemployment if actual labor market conditions are worse than available data points suggest.

Going forward, the Fed will likely be forced to prioritize one side of its dual mandate over the other, as interest rate policy is too blunt an instrument to fine-tune both price and employment levels simultaneously. The current environment represents precisely the knife-edge scenario in which an understanding of asymmetric labor dynamics becomes essential for economic forecasting.