Baron Durable Advantage Fund | Q1 2026

Baron Durable Advantage Fund® (the Fund) declined 9.0% (Institutional Shares) during the first quarter, compared to the 4.3% decline for the S&P 500 Index (the Index), the Fund’s benchmark.

In some ways, this quarter reminds us of the first quarter last year. We were coming off of two consecutive years of 25% plus gains for the Index in 2023 and 2024. The Fed was in the midst of an easing cycle. Advancements in AI were offering new tantalizing opportunities. Valuations were not cheap, but in our view, not at all unreasonable. We characterized the U.S. large-cap investment landscape as generally favorable and, in some pockets, as downright attractive. But then in early February the market got a wind of the new tariff policy and President Trump declared that “trade wars are good, and easy to win” and the market went into a tailspin. The Index lost 4.3% for the first quarter of 2025, R1KG was down 10.0%, while the Fund declined 7.0% - rather similar outcomes. In that quarterly review we wrote: “While every correction, pullback, or bear market is different, at their core, they are always driven by fear, uncertainty, and doubt. It is easy and tempting to get lost in the details because they change every time, but fundamentally, markets depend on stability and predictability. Every time stability and predictability are threatened – markets pull back.”

Well… we started 2026 off of three consecutive years of strong market returns with the Fund gaining 115.7%, cumulatively, compared to 86.1% for the Index and 101.8% for the Morningstar Large Growth Category Average (the Peer Group), and were likely due for a breather anyway. The increased geopolitical tension and the subsequent war with Iran caused the price of oil to spike to as high as $150 per barrel (physical brent crude). Treasury yields went up, the probability of further rate cuts went down, the range of possible negative outcomes expanded significantly – and the markets sold off.

From a performance attribution perspective, approximately two-thirds of the Fund’s relative underperformance was due to sector allocation, with the other third coming from poor stock selection. We held no investments in Energy (+38.2%), Materials (+9.7%) or Utilities (+8.3%), and had an underweight to Consumer Staples (+7.7%), the four best performing sectors in the Index, which accounted for 214bps of the relative shortfall, while a sizable overweight to Financials detracted another 78bps. Strong stock selection in Information Technology (IT) (+152bps) was not enough to offset poor performance in Financials, Industrials, Communication Services, Real Estate and Health Care.

From an absolute return perspective, we simply did not have enough winners, which was not terribly surprising given the broader sell-off in the quarter in the areas that we tend to invest in. Monolithic Power Systems (MPS), Taiwan Semiconductor (TSMC), CME Group, Quanta Services, Costco, and Welltower were our winners contributing 201bps combined. Microsoft (-22.8%), Meta (-13.3%), Amazon (-9.8%), and Alphabet (-8.5%) were our largest detractors. Similar to the first quarter of last year, we are highly confident that we did not suffer any permanent loss of capital. In fact, as of the writing of this letter in the middle of April, the Fund’s entire drawdown has been recovered.

In News Reporting – Sensational Always Dominates Over Statistical

The current news cycle often has a disproportionate impact on stock prices. Entire investment strategies are built on analyzing daily news flow and executing trades with lightning speed (think micro-seconds). An army of technical analysts opine daily on the significance of “breaking moving averages” and formations of “head and shoulders” in various stock charts. The goal of these highly paid experts is to predict where stock prices will go over the next say 30 or 60 days. Most of our investors will agree with us that 30 or 60-day returns don’t matter, though they can easily make us lose sight of our long-term time horizon. We do not make investment decisions based on timing or predicting the outcomes of wars or the price of oil. Not only because macro-driven events are notoriously difficult to predict with any consistency, but more so because we believe they will work themselves out. In the 20^th century, the Dow Jones Industrials Average advanced from 66 to 11,497 – an increase of 17,391% (excluding dividends) despite four costly wars, a Great Depression, and countless recessions. Not to be cavalier about the increased geopolitical risks and their consequences but in an unlikely scenario we are wrong – beating an Index will be the least of our problems. So, with rationality and pragmatism prevailing as our default setting, we focus on separating the signal from the noise and identifying the statistically significant events that help us build conviction in the investment thesis for a long-term success of a business.

“AI has moved from being a novelty to becoming something that is really useful! Inferencing is exploding and we are standing smack in the middle of this tornado.”
– Andrew Feldman, CEO of Cerebras⁴

One of the main investor concerns over the last six months has been that the mammoth increases in capex and capacity buildouts were not accompanied by the clear evidence of revenue generation. This is no longer the case. The most significant development in the quarter, in our opinion, was the dramatic acceleration in AI adoption and usage. Witness the curious case of Anthropic, the maker of Claude Code and Claude Cowork, which reported annualized recurring revenues (ARR) of $9 billion at the end of 2025, projecting to reach $30 billion in ARR exiting 2026. The company then proceeded to add $4 billion in ARR in January, $6 billion in February, and a mind-boggling $11 billion in five weeks through the first week of April⁵ , surpassing the $30 billion target for 2026. Anthropic added over $21 billion in net new ARR in just over one quarter. Think about that for a minute… Dario Amodei, the company’s CEO disclosed a few months ago that majority of the revenues is coming from enterprise customers with over 1,000 companies paying over $1 million in ARR. These are the most coveted customers in the world that every business dreams of getting. When will AI revenue finally show up? Well… it just did!

While clearly the most impressive, Anthropic is not alone. OpenAI’s ARR surpassed $25 billion⁶ from $20 billion at the end of 2025. As of the writing of this letter, no public company has reported its first quarter results, but we did get a glimpse from Amazon⁷ . Amazon AI is now at a $15 billion revenue run rate (260x larger than original Amazon Web Services (AWS) at the same point), their combined custom chips business (Graviton, Trainium, and Nitro) is now at a $20 billion ARR, growing triple-digit percentages year-over-year, implying approximately 13% of total AWS revenues. And that number is understated since they are monetizing the chips themselves. If it was a standalone business selling to third parties, their ARR would be $50 billion. AWS continues to be capacity constrained – growth would be higher if they could serve it. At 7.0% of net assets, Amazon is the Fund’s third largest holding – we would own more if we could.
 

Culture, Structural Moats, Adaptability to Change, & What’s Not Going to Change

“I very frequently get the question: 'What's going to change in the next 10 years?' And that is a very interesting question; it's a very common one. I almost never get the question: 'What's not going to change in the next 10 years?' And I submit to you that that second question is actually the more important of the two — because you can build a business strategy around the things that are stable in time."
– Jeff Bezos⁸

We have often used this quote when analyzing and thinking deeply about the companies we invest in. What attributes of successful businesses will not change in the world of AI?

• Solving real problems for customers.
• Doing it in a way that is unique – with competitive advantages that are durable.
• Being adaptable to change – see our 4Q2025 letter for an in-depth discussion.
• Management that thinks and acts like owners of the business, optimizing for the long term.
• Management that is willing to make big bets when inflection points (a disruption) become clear.

Here too, Amazon’s shareholder letter is instructive – addressing all these points. Jassy begins with what won't change: "We believe that customers will always care deeply about massive selection, low prices, very fast delivery, ease of use, and how they're treated." We own businesses that solve real problems for customers that are not going away in the world of AI. The buildout of data centers will require grid modernization solutions provided by Quanta Services. The rising amounts of debt needed to finance this buildout would still require to be rated by Moody’s and S&P Global. Businesses would still need insurance offered by Arch. The aging population and retirees will continue to need investment solutions offered by LPL, Brookfield, Blackstone, and Apollo, and the shift in demographics with the rising number of people over 80 will continue to benefit senior living provider Welltower, and so on.

Jassy then describes what adaptable culture looks like in practice – when Amazon's Bedrock team realized it needed an entirely new inference engine, rather than patching the existing one, it spun out a group of six engineers who rebuilt the architecture from scratch in 76 days using Amazon's own AI coding tool, Kiro. The result – an engine called Mantle – became the backbone of Bedrock, which nearly doubled month-over-month in March and processed more tokens in Q1 2026 than in all prior years combined. We see the same willingness to go back to the drawing board at Meta, where Founder & CEO Mark Zuckerberg last summer recruited Scale AI founder Alexandr Wang to rebuild Meta's AI program from the ground up, restructured the entire organization around a new Meta Compute initiative, and is now flattening teams as AI makes it possible for "projects that used to require big teams" to be "accomplished by a single, very talented person." ⁹ On April 8, much earlier than expected, Meta released its new AI model, “Muse Spark” that seems to have taken a massive step forward in capabilities.

The right culture and organizational structure are preconditions for this kind of adaptability. According to Jassy, "You need to move fast, have teammates that act like true owners, and be scrappy. At Amazon, we talk a lot about operating like the world's biggest startup. It's the primary reason we've worked to flatten our organization last year." Arch is a great example of a company and a culture built on its ability to adapt to change. While operating in a highly cyclical industry, Arch’s strategy has been to act anti-cyclically, providing capital and increasing underwriting when conditions are tight, prices are attractive, and competitors are retrenching. When capital is widely available, and prices do not adequately represent the risks, Arch would pull back and allow its market share to fall rather than underwrite questionable or unprofitable business. By zigging when others zag, Arch has built an incredible track record of capital allocation and has proven itself to be a great steward of shareholder capital.

Many of our most successful investments share one attribute: founder-led management that thinks and acts like long-term owners. Jensen Huang has led NVIDIA for 33 years since founding it in a Denny's in 1993. Mark Zuckerberg has run Meta since founding it at age 19. As Jeff Bezos wrote in his original 1997 shareholder letter – which Amazon still appends to every annual report as a statement of enduring values – "We will continue to focus on hiring and retaining versatile and talented employees... each of whom must think like, and therefore must actually be, an owner."

And when the inflection is big enough, Jassy argues, you must bet disproportionately. Amazon guided 2026 capex to $200 billion. "If you believe you've found one of these disproportionate shifts, you want to invest as aggressively as you responsibly can. This will create investment spikes that will invite scrutiny, but the game-changers don't typically accommodate smoother investment horizons… Inflections aren't usually smooth or calm. They favor the bold and adaptable." This is exactly what Alphabet did with its custom AI accelerators, the TPUs, early version of which was unveiled in 2016, long before the ChatGPT moment, or when it started the autonomous driving project in 2009. Just like Amazon’s chips above, Alphabet’s TPUs are a huge driver of Google Cloud Platform’s growth and Waymo was recently valued at $126 billion.

What does AI mean for the durability of competitive moats?

AI changes the nature of competition, increasing the importance of structural competitive moats while reducing the durability of simple, product/feature/workflow-based moats. Some of the structural competitive moats that in our view remain durable include the following:

• Platform businesses with network effects – Amazon is the poster child for network effects where a high number of loyal consumers (repeat buyers) attracts the highest numbers of merchants who offer the widest variety of products at very competitive prices, which attracts more loyal consumers and so on. Meta offers over 3.5 billion active users with consistently high engagement and some of the best returns on ads spent, that made it indispensable to advertisers. CME Group is the world's largest derivatives exchange. The wide availability of contracts and healthy volumes create liquidity which attracts more traders to the platform, which creates more contracts and liquidity, which benefits the traders. Every attempt to create a competitive exchange has failed. Visa and Mastercard are the equivalents of digital railroads with massive networks effects. Their payment networks connect millions of businesses with billions of consumers globally, enabling seamless commerce.
• Proprietary data moats – In the age of AI, continuously generated proprietary data that enables ongoing product improvement is an important moat. It cannot be replicated from public sources by foundation models. S&P Global generates over 95% of its revenue from proprietary benchmarks, differentiated data, and critical workflow tools. Moody's has built one of the deepest proprietary datasets in finance over 115 years, spanning credit ratings on trillions of dollars of outstanding debt across more than 33,000 organizations. In each case, the data is continuously generated as a byproduct of serving customers and cannot be replicated by a foundation model trained on public sources. Similarly, MSCI has vast amounts of proprietary data and analytics, and nearly everything MSCI sells to customers is proprietary in nature. From MSCI and S&P Global, the index business is further insulated by their benchmark status – serving as a trusted common language for industry participants. All three companies should benefit from AI through increased efficiencies in data collection, enabling them to both increase margins and invest more into new product development. CME Group generates proprietary data from every trade executed on its platform – derivatives pricing, volume, and open interest across interest rates, equities, energy, and agriculture. This data is indispensable for risk management and is licensed to financial institutions globally.
• Economies of scale – Amazon is a great example of how scale creates a self-reinforcing cycle. Greater volume drives lower shipping costs per package, enabling the company to offer faster shipping to its customers that competitors cannot match without the density Amazon has built over time. Faster delivery speeds drive higher purchase frequency, expand the addressable market to lower-cost everyday items, and attract more buyers and sellers, which further improves logistics density, reducing unit shipping costs and so on. Amazon’s scale has also been a key pillar in jump starting large businesses over time. AWS was conceived of and underwritten by the scale of its retail business which became AWS’ first customer. As AWS scaled they were able to open it up to external customers, which justified further investments, which attracted more customers. Similar dynamics have powered its logistics business and are now powering its massive investments into AI.
• Manufacturing complexity and accumulated knowhow – TSMC manufactures approximately 90% of the world’s leading-edge semiconductors. Its moat is structural: building a cutting-edge fabrication facility costs over $20 billion and takes many years, but the real barrier is yield – the percentage of functional chips per wafer. TSMC has spent decades perfecting yields at each successive process node through continued manufacturing iterations, accumulating institutional knowledge over time that is proprietary and can NOT be replicated by AI models. Acceptable (i.e. high) yield is becoming increasingly more important and harder to achieve as chip complexity and prices increase over time. While Samsung and Intel also spend large amounts of capital building advanced fabs, they serve a fraction of TSMC’s customer base, which means they cannot amortize fixed costs as efficiently and cannot accumulate yield-learning data as quickly. This creates a self-reinforcing cycle: higher yields attract more customers for TSMC, which enables it to earn higher cross-cycle returns on its investment (while the diversity of its customers also reduces the overall cyclicality of the business), which funds more R&D, which enables TSMC to reach the next node quicker and with higher yields than competitors, which widens the lead further. Advanced nodes (7 nanometers (nm) and below) now generate 74% of TSMC’s wafer revenue. Broadcom has spent years building the co-design relationships, custom silicon and networking capabilities that make it the only scaled player helping hyperscalers and large AI labs to design their AI accelerators, which has now become a significant businesses for the company with AI growth accelerating at scale to 106% year-on-year growth in the last quarter, reaching $8.4 billion. It is expected to exceed $100 billion in 2027.
• Regulatory moats and switching costs – rising chip complexity increases the switching costs for customers of TSMC such as Apple, NVIDIA, Advanced Micro Devices (AMD), and Broadcom, as changing suppliers would take years, add major costs, and risk product delays which could negatively impact their competitive positioning. HEICO and TransDigm sell after-market aerospace parts that are critical to their customers even though they represent a small fraction of the overall cost. Additionally, they undergo a rigorous approval process by regulators – this drives pricing power and high switching costs. It’s not about whether a customer can switch, but about whether it is in their best interest to do so.

We have decades of experience in identifying and investing in businesses that are beneficiaries of disruptive change. While the AI disruption feels like the most significant and challenging disruption of our careers (and frankly, our lives), we have built internal processes that we believe have prepared us well for navigating it. We have learned to think probabilistically (expected value = every possible outcome multiplied by the probability of each outcome happening) and believe there is an advantage in allocating capital against the entire range of outcomes rather than the best, the worst or even the most likely outcome. We guard against behavioral biases and systematically seek out disconfirming evidence to stress-test and re-underwrite the key assumptions that form an investment thesis for every company that we own. The goal is to reduce investments in businesses where our conviction level has lessened and increase investments where our conviction level has increased.

We analyzed the current valuation multiples for our companies and compared them to the average valuation multiples over the last five years.¹⁰ The weighted average multiple for the portfolio at the end of the quarter was 12.9% below its average over the last five years. We believe that the current geopolitical tension, combined with apprehension and uncertainty created by the AI disruption have created an attractive buying opportunity for U.S. large cap stocks. The Fund’s 9.0% correction experienced in the first quarter was driven entirely by multiple contraction, which bodes well for the Fund’s prospective returns.

Monolithic Power Systems, Inc. (MPS) designs chips that deliver precise, safe, and efficient power to processors, memory, and sensors in electronic systems. With deep system-level expertise and highly integrated solutions, MPS has established a strong leadership position in power management. Shares rose 21.0% during the quarter following continued robust quarterly results, closing 2025 with full year revenues of $2.8 billion, up 26% year-on-year, while guiding Q1 2026 meaningfully above expectations with revenues of $780 million (at the mid-point) compared to consensus estimates of $738 million. The company is poised to benefit from two major secular trends: AI-driven data center redesigns and automotive electrification. AI is fueling exponential growth in data center power needs, forcing a fundamental rethink in how power is distributed. While server shipments are experiencing unprecedented growth, power content per system is also rising, creating a durable multi-year tailwind. At the same time, vehicles are shifting to centralized computing and higher-voltage architectures, significantly increasing the need for advanced power management content per vehicle. MPS’ leadership positions it to directly benefit from both the AI infrastructure buildout and long-term automotive electrification trend.

Semiconductor giant Taiwan Semiconductor Manufacturing Company Limited (TSMC) shares rose 11.5% during the first quarter, as revenue growth of 20.5% (25.5% in USD) exceeded expectations due to surging demand for AI chips. TSMC dominates the advanced semiconductor foundry market, controlling over 90% share of cutting-edge sub-7 nm nodes that power AI servers, flagship smartphones, and autonomous vehicles. The company benefits from a virtuous cycle in which its massive scale and profitability generate the capital necessary to fund industry-leading R&D and capex, in turn widening its technological moat and reinforcing its pricing power. As the ultimate picks-and-shovels provider of the AI era, TSMC remains insulated from the competitive dynamics of the AI chip design ecosystem. Whether hyperscalers develop custom accelerators or deploy merchant GPUs from companies like NVIDIA and AMD, nearly all advanced AI accelerators are manufactured exclusively at TSMC’s 3nm and 5nm nodes. We believe TSMC will deliver 20% earnings growth over the next several years, supported by secular AI-driven demand for leading-edge manufacturing capacity.

CME Group, Inc. operates the world’s largest and most diversified derivatives marketplace. Shares rose 10.8% due to higher trading volumes during a period of elevated market volatility. Average daily trading volume rose at a robust 22% pace during the first quarter, reflecting concerns over higher energy prices from the Iran war, persistent inflation, and an uncertain outlook for interest rates. We continue to own the stock because we believe that CME enjoys significant competitive advantages and should benefit from increasing adoption of exchange-traded derivatives and episodic volatility spikes.

Software leader Microsoft Corporation detracted from performance with shares down 22.8% despite reporting slightly better-than-expected revenue, margins, and earnings per share in the quarter, with cloud revenue up 24% year-over-year in constant currency and commercial bookings up 228%, driven by commitments from OpenAI and Anthropic. Two factors pressured shares. First, Azure growth of 38% year-over-year in constant currency was slightly below expectations, reflecting slightly greater capacity allocation to first-party applications over renting out GPUs to external customers in the quarter. Management continues to emphasize that Microsoft remains capacity-constrained and is optimizing usage for long-term value, prioritizing applications such as Microsoft 365 Copilot to support future adoption. Second, investors are focused on the company’s reliance on first-party models from OpenAI and Anthropic, which plan to expand into the broader enterprise software market and account for a meaningful portion of remaining performance obligations (with OpenAI representing roughly 45%). We believe Microsoft is well positioned over the medium to long term, though we see a need for continued improvement in the pace of innovation in Microsoft 365 Copilot and in advancing model capabilities.

Shares of Meta Platforms, Inc., the world’s largest social network, declined 13.3% in the first quarter. While Meta reported strong quarterly results with 24% year-on-year revenue growth and 41% operating margins, and issued a solid Q1 revenue guidance of 29% year-on-year growth rate at the high end (in constant currency), management guided to full-year 2026 operating expenses above Street expectations, implying a 40% increase year-on-year, and raising concerns that it may be overspending on AI for less clear returns relative to competitors. Near the end of the quarter, Meta also lost a jury verdict finding that its design choices led to user harm. Additionally, broader ad budgets became more uncertain due to the conflict in Iran. While we continue to monitor the regulatory landscape, we believe the company can drive premium revenue and profit growth in the foreseeable future. Meta benefits from AI investments across its core business, driving improvements in content recommendations (with rising time spent) and in ad targeting and ranking (leading to higher conversions and better return on ad spend). Longer term, Meta’s leadership in mobile advertising, massive user base, innovative culture, leading generative AI capabilities, and technological scale, position it well for continued strong performance, with additional monetization opportunities ahead in areas such as smart glasses and commerce.

Amazon.com, Inc. is the world’s largest retailer and cloud services provider. Shares declined 9.8% during the quarter after the company guided to $200 billion in fiscal year 2026 capital expenditures, above Street expectations. While we believe AWS revenue growth will accelerate meaningfully over the next two years, particularly as leading AI companies increase AWS usage, investors are concerned about the impact of sizable incremental investments on near-term profitability. Nevertheless, the company continues to expand operating margins across core North American retail, AWS, and international retail, driven by improved cost discipline and operational efficiencies. Over the longer term, Amazon has substantial room for growth in e-commerce, where it has less than 15% penetration of its total addressable market. Amazon also remains the clear leader in the large and growing cloud infrastructure market, with significant opportunities in application software, including enabling generative AI workloads while its full-stack approach, spanning silicon, systems, software, and developer ecosystem, and hence its competitive moat continues to widen.

The portfolio is constructed on a bottom-up basis with the quality of ideas and conviction level, rather than benchmark composition and weights, determining the size of each individual investment. Sector weights tend to be an outcome of the stock selection process and are not meant to indicate a positive or a negative view.

As of March 31, 2026, the top 10 positions represented 59.1% of the Fund’s net assets and the top 20 represented 86.3%. We exited the quarter with 30 investments, down from 31 at the end of 2025.

Financials and IT represented 64.8% of the Fund, while Communication Services, Consumer Discretionary, Industrials, Real Estate, and Health Care represented another 33.4%, with the remaining 1.8% held in Consumer Staples (Costco) and cash.

During the first quarter, we initiated a new position in the semiconductor wafer fabrication equipment (WFE) supplier, Lam Research.

We also took advantage of stock market volatility to add to 9 existing investments: the index and data provider, MSCI, the premium senior housing owner, Welltower, the software and cloud infrastructure provider, Microsoft, the electrical components provider, Amphenol, the energy-focused specialty contracting company, Quanta Services, the payments network, Visa, the aerospace and defense parts supplier, TransDigm, the alternative asset manager, Brookfield, and the ratings agency, Moody’s.

To finance these purchases, we exited two investments: Danaher and CoStar, and reduced 4 existing positions – Broadcom, MPS, Apollo, and Thermo Fisher.

During the quarter, the Fund initiated a new position in Lam Research Corporation. Lam is a leading global supplier of semiconductor WFE, specializing in etch, deposition, and clean technologies used in the manufacturing of integrated circuits. Lam's tools are critical in the production of DRAM and NAND memory chips (which store data) as well as logic devices – including CPUs, GPUs, SoCs, FPGAs, and ASICs – that process data.

We believe the industry is at a key inflection – one that we expect to disproportionately benefit Lam given its outsized exposure to etch and deposition, the most layer-intensive process steps in chip manufacturing. A host of secular tailwinds supports this view: the proliferation of AI workloads, growing chip complexity, increasing materials content as nodes shrink, and the verticalization of chip designs over time. Each of these trends necessitates more layers on chips, directly driving demand for complex deposition and etch work. As CEO Tim Archer noted on the fiscal first quarter 2026 earnings call, the surge in AI data center demand is creating "billions of dollars of served available market expansion and share gain opportunity for Lam in the coming years."

Lam is competitively advantaged thanks to its decades of proprietary etch and deposition expertise, the high switching costs embedded in its deep fab integrations, and a massive installed base of over 100,000 chambers globally that generates recurring, annuity-like revenue through its Customer Support Business Group – on average earning more revenue over the life of a tool than from the initial sale itself. Nowhere is this more evident than in high-bandwidth-memory (HBM) that is in high demand for AI and advanced packaging areas, where increasingly complex high-aspect-ratio etches – extremely deep, precision cuts into the wafer – are required, and where Lam holds virtually 100% market share. We also believe the market is underestimating the company's earnings power as NAND WFE spending should recover over the next few years from one of its most severe downcycles on record, having fallen approximately 50% from its 2022 peak – creating meaningful pent-up demand that we expect to benefit Lam in the coming years.

We also believe that the industry's competitive dynamics have become increasingly favorable over time, with meaningfully reduced cyclicality. Historically, technology transitions in the memory market would drive significant increases in bit capacity. Since manufacturing on a smaller node reduces the cost per bit, and cost is the key competitive input in a commodity industry, all players must aggressively chase the most advanced node. This amplified boom-and-bust cycles because technology transitions would increase supply regardless of the demand-supply equation in the market. Over the last several years, however, technology transitions have now enabled significantly slower bit growth (and even more so with HBM), which allows memory suppliers to invest more in congruence with demand as they must actively invest in incremental wafer capacity to grow bit supply.

Our largest addition during the quarter was to MSCI Inc., a leading provider of indices and investment decision support tools. The company reported strong Q4 2025 earnings and management sounded upbeat about the business going forward. Despite the strong fundamentals, the stock was volatile due to industry-wide AI disruption worries. We believe the recent volatility has created a long-term opportunity to own more MSCI. From an AI perspective, we see MSCI as well positioned with CEO Henry Fernandez recently saying that “AI is a godsend to us.” Henry has also been an active buyer of MSCI stock in the open market over the past year, which is a strong signal of his conviction in the opportunity ahead.

MSCI has vast amounts of truly proprietary data and analytics, and nearly everything MSCI sells to customers is proprietary in nature. The index business is further insulated by nature of its benchmark status where it serves as a trusted common language for industry participants. The value of an MSCI index lies in the governance, methodology consensus, regulatory acceptance, and the trillions of dollars of AUM benchmarked to these indices. Once an asset manager has launched an ETF tracking an MSCI index or an asset owner has written MSCI benchmarks into its investment policy statement or a sell-side desk has built its risk system around MSCI’s analytics framework, the cost and career risk of migrating is enormous. AI should make the users of MSCI data more productive, but won’t replace the standard itself and the proliferation of AI-driven systematic and custom portfolios could actually increase demand for MSCI’s data.

We retain long-term conviction that MSCI owns strong, "all weather" franchises that remain well positioned to benefit from numerous secular tailwinds in the investment community and should help drive many years of compounding growth. The ongoing shift to passive (index) investing directly feeds MSCI’s asset-based fee business, while custom indexing should help MSCI push deeper into new client types such as wealth management. Private markets remain much less transparent relative to public markets and given that asset owners want to look at their portfolios on a multi asset class basis, MSCI has been aggressively expanding its private market capabilities (key acquisitions here include Burgiss, Real Capital Analytics and PM Insights). The company is also poised to capture increased demand related to assessing the impact of climate change on client portfolios and the ongoing trend of asset managers outsourcing more back and middle office functions.

We also continued to build our position in the premium senior housing provider, Welltower Inc., which we believe offers both “offensive” and “defensive” investment attributes in the current uncertain environment. Given most of the company’s cash flows are derived from senior housing, “defensive” characteristics are underpinned by a “needs based” service offering. Welltower owns senior housing properties in some of the best micro-markets with substantial pricing power given the company serves a higher net worth demographic. As we have articulated in the past, we remain optimistic about the prospects for both cyclical growth (a recovery from depressed occupancy levels following COVID-19) and secular growth (seniors are the fastest growing portion of the population and people are living longer) in senior housing demand against a backdrop of muted supply that will lead to many years of compelling organic growth. Several of these characteristics were on display in the most recent quarter with 20% same-store net operating income year-on-year growth in senior housing and a 28% year-on-year earnings growth. We regard management as highly astute capital allocators. We anxiously await CEO, Shankh Mitra’s annual letters and this recent one didn’t disappoint¹¹:
 

“2025 represented the most pivotal year in our history during which we meaningfully amplified and added substantial duration to our already strong growth trajectory… 2025 marked the beginning of another period of disruption from within…

"In an era where AI is compressing informational advantages and testing traditional moats, we believe it is critical to distinguish between what can be displaced by technology and, just as importantly, what cannot… Our communities are not lines of code. They are purpose-built, capital-intensive buildings that take many years to entitle, develop, build, and stabilize… People can't live in the cloud."

Other sizable additions in the quarter were the following:

• We added to shares of Microsoft Corporation in the quarter on the back of what we believe to be short-term focused volatility. While Microsoft is a net beneficiary of AI, Azure growth came in +38% year-over-year in constant currency, which was light of expectations of +39% to 40% as they allocated capacity across both 1st and 3rd party applications. This is feeding the narrative that Microsoft is losing share even though the company remains capacity constrained, is adding AI capacity rapidly, and is optimizing capacity allocation based on the best long-term value for their portfolio, which includes 1st party applications such as M365 Copilot. Longer term, Microsoft is well positioned to remain a key technology platform for enterprises, which comprises applications, chips, and infrastructure with ingrained governance and security guardrails, and is the "easy button" for most organizations. We also believe the company's distribution and bundling/pricing methodology makes the products sticky which helps it consistently gain share in application spending with pricing leverage on lower ARPU product. Over time we believe that: 1) AI investments will continue to drive rapid growth for Azure; 2) M365 Copilot growth will accelerate (15 million Copilot seats represent only 3% of the 450 million M365 Commercial users with rapid growth) as first party investments help drive faster innovation and better adoption; and 3) the OpenAI concentration go from an overhang to a tailwind as concentration lessens over time.
• We took advantage of price volatility to add to our position in Amphenol Corporation, a leading provider of high-technology interconnect, sensor, and antenna solutions to a diverse set of end markets. Amphenol is benefiting from the AI data center buildout as the leading supplier of high-speed copper interconnects. Its IT datacom segment has been growing rapidly (now around $10 billion revenue run rate), and the recent $10.5 billion CommScope CCS acquisition (closed January 2026) adds fiber optic capabilities, making Amphenol a total solution provider for data center connectivity.
• We added to Quanta Services, Inc., the leading energy-focused specialty contracting company. Quanta continues to benefit from secular growth tailwinds for energy-related infrastructure – AI data centers, grid modernization, electrification, and reshoring – and management believes 15%-plus EPS growth per annum through at least 2029 is achievable (and we agree). Its 68,000-person craft-skilled workforce is at least twice the size of its nearest competitor.

According to ChatGPT, the word “Durable” is associated with the multifaceted nature of broader concepts related to quality, longevity, reliability, and security. We did not choose this word by accident. At an emotional level, the word durable has many positive associations – longevity, reliability, resilience, security… a sense of confidence in the quality of something, and the comfort of knowing the product will NOT fail easily and perform reliably over time. Most importantly, durable is something that must endure. Something that must withstand the test of time!

We tried to construct the Baron Durable Advantage Fund® with all of that in mind. Over the last three years, at the portfolio level (meaning on average), the companies we own grew revenues nearly twice as fast as the index at 15.8% versus 8.6%. Earnings per share grew nearly twice as fast, at 21.2% compared to 11.2% with operating profit margins that were 9.2% higher at 37.6% versus 28.4%. Returns on invested capital at 20.8% were 4.2% higher. At the same time, companies we own used less than half the leverage of the Index (on a debt to market cap ratio) and had lower earnings growth volatility over the trailing five-year period.

As long only investors…

Our goal is to generate an annualized 100 to 200bps of alpha, net of all fees and expenses, while minimizing the probability of permanent loss of capital. We believe that the best way to assess whether we are successful in doing what we set out to do is to measure our performance over longer periods of time and over full market cycles. We believe that rolling monthly returns can be insightful in analyzing whether the process we employ works and whether it is repeatable. This analysis shows that on an annual basis, the Fund has outperformed the S&P 500 Index and its Morningstar Peer Group 58% and 65% of the time, respectively. But as the time horizon extends, so is the Fund’s winning percentage. Over a three-year rolling monthly return period, the Fund outperformed 83% and 89% of the time, while on a five-year basis, the Fund has outperformed 98%, and 100% of the time, respectively. It is the opposite story for our average competitor. Note, of course, that past performance does not guarantee future results.

Sources: Baron Capital, S&P Global Inc., and Morningstar Direct.

Every day, we live and invest in an uncertain world. Well-known conditions and widely anticipated events, such as Federal Reserve rate changes, ongoing trade disputes, government shutdowns, and the unpredictable behavior of important politicians the world over, are shrugged off by the financial markets one day and seem to drive them up or down the next. We often find it difficult to know why market participants do what they do over the short term. The constant challenges we face are real and serious, with clearly uncertain outcomes. History would suggest that most will prove passing or manageable. The business of capital allocation (or investing) is the business of taking risk, managing the uncertainty, and taking advantage of the long-term opportunities that those risks and uncertainties create. We are confident that our process is the right one, and we believe that it will enable us to make good investment decisions over time. 

Our goal is to invest in large-cap companies with, in our view, strong and durable competitive advantages, proven track records of successful capital allocation, high returns on invested capital, and high free cash flow generation, a significant portion of which is regularly returned to shareholders in the form of dividends or share repurchases. It is our belief that investing in great businesses at attractive valuations will enable us to earn excess risk-adjusted returns for our shareholders over the long term. We are optimistic about the prospects of the companies in which we are invested and continue to search for new ideas and investment opportunities.

We thank you for your continued trust and for being our partners in this journey.

Sincerely,