The enthusiasm went into overdrive following SpaceX’s jaw-dropping, $60B all-stock acquisition of AI coding platform Cursor. It was a move that signaled to Wall Street that SpaceX is not just a rocket company, it is being priced as a sprawling, vertically integrated monopoly dominating space logistics, global telecommunications and next-generation AI infrastructure.

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The potential Total Addressable Market: $28.5 Trillion

SpaceX outlines its Total Addressable Market across 3 core verticals. Crucially, these figures completely exclude Russia and China, making them focused entirely on accessible global markets:

• The Space Segment (Launch & Logistics): $370B

  • Ironically, the division that made SpaceX famous (rocket launches and Starship) represents a mere 1% of their claimed long-term market opportunity.

• The Connectivity Segment (Starlink Broadband & Mobile): $1.6T

  • This is broken down into roughly $870B for Starlink Fixed Broadband and $740B for Starlink Mobile

• The Artificial Intelligence Segment (Orbital Compute & Enterprise Software): $26.5T

  • This is the jaw-dropping kicker that makes up over 93% of SpaceX’s entire TAM. It includes $2.4T for AI infrastructure (like their plan to launch 1 million satellites to serve as orbital data centers), $760B in consumer AI subscriptions, and a massive $22.7T for Enterprise AI applications (leveraging their xAI integration and acquisitions like Cursor)

The FY25 revenue was $18.7B, FY26 should be between $23B and $35B. FY30 forecast is $300B (according to analysts) and $1T (according to Musk) representing a CAGR between 74% and 121%.

The current segment revenue breakdown is as follows

• Connectivity (Starlink): $11.4B (61% of total revenue). This is the only consistently profitable segment today, bringing in $4.4B in operating profit and crossing 10 million active global subscribers

• Space (Launch): $4.1B. While they completed a record 165 Falcon 9 launches in 2025, only 43 were for outside commercial/government clients, nearly three-quarters were used internally to deploy Starlink. This segment posted a $657M operating loss due to massive Starship development costs

• AI Segment: $3.2B. Despite the revenue, it dragged down the bottom line with a $6.4B operating loss, fueled by a staggering $12.7B in AI capital expenditures as they build out ground and orbital compute capacity

The ultimate promise SpaceX is selling is not about sending rockets to Mars, it is about solving the biggest bottleneck in the AI revolution: power and logistics on Earth. By pitching space-based AI data centers powered by 24/7 uninhibited solar energy, SpaceX is positioning itself to bypass terrestrial power grid constraints. Wall Street bulls, like Dan Ives at Wedbush, argue that investors are not buying a capital-intensive hardware company, they are buying a vertically integrated AI and data infrastructure monopoly that happens to operate in orbit.

The foundation: a masterclass in industrial cost destruction

Before analyzing the astronomical valuation or the AI master plan, we must first look at the bedrock upon which SpaceX is built. The only reason public markets are willing to entertain a multi-trillion-dollar cap for this business is because Elon Musk did something the entire global aerospace establishment claimed was physically and economically impossible: they commoditized space.

For over half a century, the space industry operated on an incredibly inefficient, legacy defense-contractor model. Rockets were treated like expendable, single-use ammunition, gorgeously engineered, hundred-million-dollar pieces of hardware that were thrown into the ocean after a single flight. SpaceX shattered that paradigm through a relentless focus on two structural pillars: vertical integration and rapid reusability.

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A large conglomerate

The structural transformation detailed in SpaceX’s S-1 filing makes it clear that the entity trading on public markets is no longer just a rocket company. Instead, it is a massive industrial and technological conglomerate holding 3 wildly distinct businesses under one corporate umbrella. Each of these segments operates with entirely separate margins, capital expenditure requirements and competitive landscapes.

The first pillar is the foundational Launch division, which acts as the asset-heavy, industrial backbone of the empire. This segment encompasses the Falcon 9 and Starship programs alongside heavy government and military launch contracts. While this division holds an absolute global monopoly over orbital logistics, its financial reality is burdened by the staggering, constant R&D costs required to make Starship a routine commercial vehicle. It represents an unparalleled, physical competitive moat, but it operates as a capital-intensive manufacturing business that acts as a low-margin foundation for the rest of the conglomerate.

The second pillar, and the primary engine of predictable cash flow, is the Starlink satellite telecommunications network. Operating essentially as a global consumer and enterprise internet utility, Starlink has scaled efficiently enough to bypass the traditional pitfalls of satellite hardware. Because it leverages the Launch division’s rockets at near-zero internal marginal cost, Starlink has managed to maintain highly profitable software-like recurring subscription revenue. It functions as the predictable, high-margin anchor of the entire organization, providing the crucial cash reserves needed to fund the conglomerate’s more speculative endeavors.

The third and most volatile pillar is the newly integrated AI infrastructure division, formed by the blockbuster merger with xAI and the subsequent acquisition of the AI coding platform Cursor. This segment operates as a hyper-growth frontier technology player, but it simultaneously serves as a massive financial black hole due to its immense computing hardware demands. Within this ecosystem sits Grok, the conversational AI tied directly to the social network X, which was also absorbed into the corporate structure. Grok exemplifies the extreme financial tension of the conglomerate. While it requires billions in capital expenditures to power its massive terrestrial supercomputer clusters, a recent slowdown in consumer engagement has forced a dramatic pivot. Rather than relying solely on individual software subscriptions, SpaceX has effectively transitioned this AI division into an enterprise infrastructure landlord, renting out its idle compute power to major tech rivals to help offset the segment’s heavy operating losses.

There is no denying it: Musk is a master of the corporate narrative.

An astronomical valuation

To truly understand the disconnect between the public market enthusiasm and fundamental reality, we have to examine the sheer scale of the mathematics currently pricing SpaceX. Pricing its historic IPO at $135 per share, the company initially debuted at a valuation of $1.77T. Within days of hitting the Nasdaq, frantic trading volume and the announcement of the $60B Cursor acquisition sent the stock into a tailspin of upward momentum, topping out at an intraday high of $225. This meteoric rise effectively propelled SpaceX past global enterprise titans like Amazon, solidifying it as the fifth-most valuable company on Earth and officially crowning Elon Musk as the world’s first trillionaire. The stock is now trading close to its IPO price around $150.

When you anchor these numbers against the financial realities disclosed in the S-1 filing, the multiples venture into unprecedented territory. SpaceX generated $18.7B in revenue for the fiscal year 2025 while recording a GAAP net loss of $4.9B. At this market cap, the trailing PS multiple sits around 100x. Even if we use Wall Street’s forward estimates for 2026, which project a doubling of revenue to $36.8B as heavy capital investments begin to yield results, the forward PS ratio remains a staggering 54x.

On the bearish end, fundamental purists like Morningstar peg the company’s fair value at a conservative $62 per share, arguing that the true sum of its launch, telecom and AI parts is worth closer to $1.2T (already very high…). On the hyper-bullish end, institutional targets reaching as high as $310 per share assume that the company’s massive infrastructure agreements (such as its cloud-compute leasing deals with Anthropic and Google) will smoothly convert into decades of highly predictable, high-margin revenue. As disciplined investors, looking at this premium requires recognizing that the market is no longer pricing a company based on its present cash flows, it is pricing an absolute leap of faith in Elon Musk's long-term corporate narrative.

To justify a $2T valuation, several extreme hypotheses must simultaneously turn into reality over the next decade:

• First, SpaceX must completely capture its projected $28.5T total addressable market, requiring a suspension of disbelief that nearly all global enterprise software and AI spending will flow through orbital networks

• Second, the company must maintain an absolute, permanent monopoly in both space logistics and satellite broadband, assuming that heavily funded rivals like Amazon’s Project Kuiper or sovereign state networks completely fail to dent Starlink's market share

• Third, Starship must achieve immediate, flawless and routine commercial flight cadences to push launch costs below $200 per kilogram, which is the only way the capital-intensive satellite replacement cycles remain financially viable

• Finally, the newly formed AI division must flawlessly monetize its compute infrastructure, meaning the multi-billion-dollar cloud-leasing deals with tech giants must scale indefinitely without facing a supply glut or a sharp correction in the broader terrestrial AI data center market

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Potential risks

The Retail Mania and the Low Float Trap

A significant portion of SpaceX’s market volatility stems from its unique share structure. Because the company was private for so long and Insiders/Elon Musk retain massive, tight control over the equity, the actual public float (the number of shares available for public trading on the open market) is exceptionally low. When a massive wave of enthusiastic retail investors rushes to buy into a stock with a highly restricted supply of shares, it creates an artificial supply-and-demand squeeze. This low float acts as an accelerant, driving the price up to spectacular heights on pure momentum, but it creates a dangerous trapdoor effect: if sentiment shifts or early insiders decide to lock in profits, the lack of deep institutional liquidity means the stock could drop just as violently as it rose.

Execution Risk on an Unprecedented Scale

Even if we ignore the stock market mechanics, the physical execution required to keep this ship afloat is staggering. Starlink satellites have a lifespan of only 5 to 7 years. To maintain its network, let alone scale it, SpaceX is on a non-stop capital expenditure treadmill, they must launch thousands of new satellites every single year just to replace the ones that are dying. This entire operational loop hinges completely on Starship achieving flawless, routine and ultra-cheap commercial flight cadences. If Starship suffers any major regulatory groundings, technical design setbacks, or launchpad accidents, the financial burden of keeping Starlink alive using older, more expensive Falcon 9 rockets would severely drain the company’s cash reserves.

The Burden of an Excessive Valuation

At a trading multiple of over 130x trailing sales, SpaceX has absolutely zero margin for error. When a company is priced to perfection, the market expects flawless, exponential growth across every single business line simultaneously. Even a minor macroeconomic slowdown, a slight delay in government defense contracts or a temporary plateau in Starlink’s global subscriber growth could trigger a massive, painful repricing. Investors buying at these levels are not just paying for the company’s future success, they are paying a steep premium that assumes SpaceX will completely monopolize multiple global industries without a single operational hiccup for the next decade.

My analysis

SpaceX represents everything I find concerning in the current market: a landscape where hyper-inflated narratives completely overpower fundamental analysis. Across the broader market, there are dozens of high-conviction companies with exceptional growth runways trading at far more logical valuations, and critically, they are already highly profitable.

So, what exactly is an investor purchasing when they buy a share of SpaceX today? A path to superior compounding returns? Historically speaking, no. The risk-reward profile at these levels is heavily skewed to the downside. A piece of the future? Perhaps. A compelling narrative and the emotional high of participating in the next space race? Absolutely. The unshakeable faith that Elon Musk can magically spin gold out of thin air? Indubitably.

But this entire setup carries the unmistakable, echoing hallmarks of previous market tops: frantic retail mania, heavily unprofitable enterprises operating on pure sentiment, historic valuation multiples and extreme market concentration.

The core philosophy of this newsletter has always been about identifying resilient businesses capable of compounding capital steadily over time. But in today’s euphoric market, nobody wants to get rich slowly anymore. I remain convinced that this disciplined approach is the only way to treat the market as a long-term compounding machine, rather than a short-term casino. My ultimate hope is that the investors currently riding this wave manage to navigate the volatility safely and are not left holding the bag when the music inevitably stops.

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But as investors, this is exactly when we are in the greatest danger.

Sometimes, history has proven that the worst thing you can do when a technology changes the world is buy the equity of the companies changing it. We are seeing this paradox unfold in real-time today.

When capital becomes unmoored from disciplined unit economics, the market enters an aggressive Infrastructure Phase Change. To understand how this phase ends, we don’t need to guess. We just need to look back 180 years to a time when the world’s most powerful empire decided to completely re-engineer its economy around a revolutionary piece of iron hardware: the steam locomotive. What happened next is arguably the most perfect case study in history of how great infrastructure can thoroughly incinerate investor wealth.

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The British Rail Boom

To the modern observer, a financial bubble looks like a collective bout of madness. But under the hood, every great market mania is driven by 2 highly rational catalysts: a structural surplus of capital and an elegant bit of financial engineering that creates artificial leverage. The British Railway Mania of the 1840s possessed both in spades.

By 1843, the British economy was utterly flush with liquidity. Consecutive years of bumper agricultural harvests had poured cash into the financial system, driving interest rates to historic lows. The Bank of England discount rate sat at a mere 2.5% and standard government perpetuities (3% Consols) were trading at par for the first time in a century. Starved for yield in safe-haven assets, the burgeoning middle class looked longingly at the early, established railway lines (like the Liverpool & Manchester) which were throwing off highly lucrative, predictable 10% dividends. Investors made a fatal assumption: if the first tracks were compounding cash machines, then all future rail infrastructure would yield the exact same returns (you should begin to understand what went wrong!)

Promoters and corporate insiders quickly recognized this insatiable demand and engineered a structural loophole to hyper-leverage it: the creation of “scrip” or partially paid shares.

When a new railway company was formed to lay down tracks between 2 towns, it didn’t ask investors for the full price of a share upfront. Instead, it required only a nominal initial deposit, typically just 5% to 10% of the share’s face value (often just £2 to £5 on a £50 share), to fund preliminary engineering surveys and parliamentary legal fees.

This mechanism acted as a synthetic options contract. An investor with £100 of actual cash didn’t just buy 2 fully paid shares of £50, they could buy the “scrip” for 50 shares. If speculative excitement pushed the value of that scrip up by just £2 on the secondary market, the investor could flip it for a quick 100% return on their invested capital.

The trouble was that investors completely ignored the fine print. By signing the subscription contract, they legally bound themselves to pay the remaining 90% of the share price in cash whenever the railway directors demanded it over the next 5 years to fund actual construction.

For a railway to actually lay physical iron, it required an Act of Parliament to authorize land acquisition. In 1843, Parliament received 63 petitions, by late 1845, that exploded to over 1,200 projected lines. Instead of acting as a strict quality-control regulator, Parliament essentially rubber-stamped hundreds of competing, directly parallel routes (A speed race, you say? Does it seem familiar?)

This uncoordinated allocation of capital completely shredded the economic moats of the entire network. Rather than a single, highly profitable line connecting 2 major industrial hubs, there were suddenly three or four parallel tracks competing for the exact same passengers and freight.

The house of cards collapsed when those hundreds of paper companies transitioned from surveying routes to actually pouring gravel. Directors began issuing their legal capital calls for the remaining 90% of the share value. Investors who had hoarded dozens of lines on thin 5% margins suddenly faced legal demands for cash they simply did not possess.

To meet the capital calls on their best positions, investors were forced to dump shares across their entire portfolios. The secondary market suffered a catastrophic liquidity cascade. By 1850, the index of British railway shares had crashed by more than 65% from its peak, leaving a trail of bankruptcies across the country.

The ultimate irony, and the lesson that echoes loudest today, is that the Railway Mania was profoundly productive for society. It built the foundational spine of the United Kingdom’s modern transportation infrastructure, laying down over 8,000 miles of track that permanently lowered industrial transport costs and boosted long-term GDP. The infrastructure survived and changed the world, but because capital was over-allocated into redundant capacity, the aggregate return on capital employed (ROCE) permanently collapsed. The world got its revolution, the equity owners got wiped out.

Some Metrics

To fully grasp the magnitude of the Railway Mania, we have to look past the stock market ticker and evaluate its scale relative to the entire British economy. The numbers are staggering. At the absolute peak of the frenzy in 1845, Parliament authorized the construction of over 8,500 miles of new track, requiring an estimated capital investment of roughly £294M

To put that into a modern context of capital allocation:

• The authorized railway CAPEX represented nearly 90% of Great Britain’s entire annual Gross Domestic Product at the time

• In the peak construction years of 1846 and 1847, actual physical spending on railway infrastructure topped £40M annually, accounting for more than 6.5% of total national income and an astonishing 50% of the country’s entire gross domestic capital formation

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The Parallels With the Current Market

The parallels between 1845 and the current AI buildout are close, with the world’s most profitable tech companies caught in a classic prisoner’s dilemma. The scale of today’s AI CAPEX perfectly mirrors the macroeconomic distortion of the Victorian railway boom, showing that when structural hype takes over, the fundamental laws of capital allocation do not change.

Today, the numbers are scaled to a global backdrop, but the weight is just as crushing. Combined 2026 capital expenditures for just 4 tech giants (Amazon, Alphabet, Meta and Microsoft)—have skyrocketed to a staggering $610B. Cumulative global AI capital expenditure between 2026 and 2030 is projected to hit an unfathomable $4.7T.

Much like the British rail boom swallowed 50% of domestic capital formation and starved other sectors, today we are seeing a similar systemic concentration of capital. CAPEX as a percentage of operating cash flows for the largest hyperscalers has surged from roughly 40% in 2023 to nearly 70%. When you strip away dividends and stock buybacks, AI infrastructure is now consuming more than 90% of Big Tech’s aggregate free cash flow. Every spare dollar generated by dominant software monopolies, search engines and e-commerce platforms is being funneled into a single asset class: data centers, advanced cooling systems and specialized accelerators.

Just as 19th-century Parliament authorized separate, redundant railway tracks between the same industrial towns, modern hyperscalers are building completely overlapping digital infrastructure. Microsoft, Google, Amazon and Meta are all building sovereign clusters, buying identical Nvidia chips and competing for the exact same enterprise workloads. This would not be an issue if the AI economic performance is as high as expected. Otherwise, you understand the pattern.

The Law of Capital Allocation

For quality-focused investors, the structural lesson across centuries of manic infrastructure cycles remains completely unchanged: Societal utility does not equal equity returns.

True business quality is defined by 2 immutable pillars: sustainable pricing power and disciplined capital allocation. When an industry enters a structural phase where its dominant participants are forced to consume up to 70% of their operating cash flows to fuel a market hard to estimate, the underlying economic engine shifts. In case of market saturation (created by overcapicity or lower-than-expected monetization), the business model stops operating as a high-margin compounding asset and transforms into a capital-devouring infrastructure utility.

To go further

A Note on Portfolio Survival

Ultimately, acknowledging that AI is an undeniable revolution does not solve the structural mathematical equation facing your portfolio. The core risk today is not a lack of technological potential, it is that the ultimate size, shape and monetization timeline of the actual end-market remain profoundly unknown (for data centers, models, GPUs, software

History tends to repeat itself with ruthless precision because human psychology and competitive dynamics do not change. When the macro-environment presents an infinite total addressable market (TAM), corporate leadership teams predictably shift from returns-focused operators to empire builders. They massively invest, assuming the future cash flow will justify the upfront destruction of their balance sheets.

But if the past centuries of market infrastructure cycles have proven anything, it is that the true winners of a technological revolution are rarely the ones we think.

• In the 1840s, the investors who bought the prominent railway operators were completely eviscerated, while the consumer economy and industrial factories reaped decades of cheap shipping efficiency

• More recently, the telecom giants that buried hundreds of billions of dollars in fiber-optic cable returned poorly, only for Web 2.0 platforms like Google, Netflix and Amazon to benefit from it to build multi-trillion-dollar monopolies

For the quality-focused allocator, this reality demands a return to fundamental humility. When the underlying unit economics of an entire asset class become obscured by CAPEX wars, protecting your capital through strict risk management and conservative position sizing is more vital than ever. The data centers breaking ground today will undoubtedly change the world. But be careful until the fog clears.

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The market is not just pricing in a bad quarter, it is pricing in an existential crisis. Investors are terrified that the consulting moat is being drained by the very technology (Artificial Intelligence) that these firms were supposed to sell. But is the business model truly broken or is the market failing to see the birth of the new consulting?

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What is consulting?

To understand why the stock market has historically treated these firms as quality compounders, one must first understand the fundamental value proposition of the consulting industry. At its core, the business model thrives on 3 pillars: expertise, capacity and neutrality. Clients turn to consultants for expertise when they face a problem they lack the internal skill set to solve, such as navigating a complex cross-border merger or implementing a bleeding-edge technology stack. Beyond knowledge, consulting provides a capacity lever. Large organizations often have the will to change but lack the hands to do it. Consultants act as a variable labor force that can be switched on or off, allowing a company to scale its efforts without the long-term liability of increasing permanent headcount. Finally, the external point of view acts as a form of corporate insurance. A CEO may know exactly what needs to be done, but they hire a consultant to provide a neutral, third-party stamp of approval that can be used to build consensus among a skeptical board of directors or a resistant workforce.

The industry is far from a monolith and the investor must distinguish between the various sub-sectors, each with its own margin profile and moat durability. Strategy consulting sits at the top of the food chain, where firms like McKinsey or BCG command the highest daily rates (above $5k a day). Here, the product is not a finished system but a high-stakes recommendation on where a company should play and how it can win. Just below this is management consulting, which focuses on the how: optimizing operations, restructuring supply chains or managing large-scale organizational changes. These engagements are longer and more integrated than pure strategy, focusing on the bridge between a high-level idea and its day-to-day execution.

The largest and most capital-intensive segment is IT consulting, which is traditionally divided into project and run services. Project consulting involves the design and building of new digital infrastructure, the heavy lifting of installing an ERP system, moving data to the cloud or creating a software from scratch. Once the system is built, the run side of the business takes over, providing long-term managed services and maintenance. This is the recurring revenue that quality investors love, as it creates switching costs for the client. At the very bottom of the hierarchy lies simple body shopping. In this model, the consulting firm essentially acts as a high-end staffing agency, providing bodies to fill seats for basic tasks. This allows the client to bypass the friction of hiring and firing employees while keeping the consulting firm’s bench active.

The current challenges

The core challenge for consulting firms is that AI is not just a tool they sell, it is a force that could fundamentally shrinking the surface area of their traditional business model. The status of these stocks is under siege because the very mechanics that made them profitable (billing for human time) are being liquidated by algorithmic efficiency.

1. The evaporation of junior labor

The traditional consulting pyramid relies on an army of junior associates to handle the grunt work (data cleaning, research and deck formatting). However, recent data from 2026 shows that AI agents now handle approximately 60–70% of these foundational tasks. A landmark study revealed that consultants using AI finished tasks 25% faster with 40% higher quality. For a business model that bills by the hour, this is a deflationary trap. If a junior consultant becomes twice as productive, the firm potentially loses half its billable revenue unless it can double its project volume.

2. The erosion of the expertise moat

Historically, a major moat for large firms was their proprietary knowledge and the speed at which they could train new cohorts. Today, AI allows newcomers and boutique firms to close that gap almost instantly. An entry-level consultant equipped with specialized LLMs can now perform (at least in theory) financial analyses and regulatory cross-referencing that previously required years of experience to master. This commoditization of expertise means that the premium clients used to pay for a big-name firm’s brain trust is being competed away by smaller, leaner AI-native competitors who can deliver the same insights at a fraction of the cost.

3. The empowered executive

The capacity argument for hiring consultants (the need for extra hands to execute a vision) is also weakening. Corporate executives are increasingly using internal AI suites to handle market synthesis and strategic planning themselves. This shift does not just reduce the frequency of consulting engagements, it moves the work in-house, permanently shrinking the Total Addressable Market (TAM) for external capacity.

4. Accelerated implementation timelines

In IT consulting, the setup phase of a project used to be a reliable multi-month (year) revenue generator. New efficient data architectures and automated coding tools have dramatically compressed these timelines. What used to be a multi-year ERP migration or cloud integration is now frequently completed in months (or at least quarters). While this is a win for the client, it is a structural headwind for the consultant. Since stocks are valued on the predictability of long-cycle revenue, the shift toward shorter, high-intensity projects makes earnings more volatile and harder to forecast.

5. The automation of run services

The most defensive part of the business (the run or managed services) is being cannibalized by autonomous monitoring systems. These AI-driven platforms can predict system failures, patch security vulnerabilities and optimize server loads without human intervention. For firms like Infosys or Capgemini, which rely on large-scale maintenance contracts, this automation removes the need for thousands of offshore support roles. Unless these firms can successfully pivot to charging for the software rather than the people managing it, they risk a permanent contraction in their most stable revenue streams.

6. The AI fatigue

By mid-2026, many C-suite executives have entered a phase of AI fatigue. After spending millions on AI pilots in 2024 and 2025, many have found that while the technology is cool, costs and real usage creates lower than expected ROI. However, this investments have reduced the investments in other legacy software, reducing the project dynamic we previously had.

7. The internalization of the digital core

As AI becomes the central nervous system of a business, companies are realizing that they cannot outsource their brain. Large enterprises are increasingly building internal AI orchestration teams rather than hiring external firms to do it for them. This move toward in-sourcing is shrinking the available market for the high-end strategic work that used to be the crown jewel of the consulting world.

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Why the market is overreacting

While the market is obsessed with the death of the billable hour, it is likely missing the structural resilience and agility of these consulting giants.

1. The software illusion

The market often conflates consulting with pure labor, forgetting that firms like Accenture and Capgemini have spent the last decade becoming massive software implementation and licensing engines. A significant portion of their revenue is tied to the digital core, managing the underlying cloud architecture and enterprise software (SAP, Salesforce, Oracle) that AI actually runs on (or will run on…). AI will not exist in a vacuum, it requires the very infrastructure these firms are paid to build and maintain. As long as enterprise software remains complex, the plumbing revenue of consulting remains intact.

2. The margin expansion trade-off

Wall Street is currently punishing the sector for slowing revenue growth, but it is ignoring the potential for a massive expansion in productivity. In the old model, growing revenue by 10% required hiring 10% more people, a linear, low-leverage equation. In 2026, if AI allows a firm to deliver the same project with 40% fewer staff, the firm can afford to give the client a 15% discount while still capturing a significantly higher profit margin. We are moving from a volume business to a value business, where the firms will trade top-line vanity for bottom-line sanity (lower revenue, higher margin)

3. The counter-intuitive revenue growth

Despite the efficiency narrative, the aggregate revenue for the industry giants is still hitting record highs. The reason is simple: the complexity gap. While AI makes individual tasks easier, it makes the overall corporate ecosystem much more complicated. This creates a massive, multi-year backlog of work. The market sees AI as a one-off disruption, but for consultants, it is a forever project that requires constant tuning, oversight and integration.

4. The trust premium

In an era where AI can hallucinate and digital security is under constant threat, the value of a brand name consultant has actually increased. A board of directors will not trust a raw LLM to oversee a $500M restructuring. They will trust a firm with a balance sheet, a legal department and a century of reputation.

5. The capital allocation advantage

Finally, the market is missing the sheer fortress nature of these companies’ balance sheets. With stock prices at multi-year lows, firms like Infosys and Accenture are sitting on massive cash reserves. They are in a position to aggressively buy back their own undervalued shares and, more importantly, acquire the very AI startups that are supposed to disrupt them.

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Zoom on Accenture

If you believe the consulting model remains resilient, Accenture’s current valuation represents a compelling entry point. However, the market is currently struggling to price the company accurately due to a volatile mix of macroeconomic uncertainty and shifting industry pressures.

Until the long-term impact of AI is clearly defined (specifically whether it serves as a massive productivity tailwind or a threat to traditional billable hours), the share price may continue to slide. Consequently, it is prudent to avoid going all-in while the market searches for a definitive floor. This setup is not unique to Accenture, as peers like Capgemini, Infosys and Tata Consulting Services face similar headwinds. Nevertheless, the AI revolution will likely favor these larger players who have the scale and capital to integrate the technology most effectively.

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2 sides of AI

The illusion of a uniform AI revolution is finally dissipating, giving way to a far more nuanced reality for the discerning investor. It is crucial to recognize that we are witnessing a great divergence within portfolios. On one side, digital-native companies with deep engineering cultures (such as Alphabet) have already moved past the experimentation phase. For these firms, AI is a direct performance multiplier integrated into existing automated workflows (example: improved ad targeting for Google Search), turning every line of optimized code into immediate operating margin expansion. Here, adoption is tangible and scalable because the underlying infrastructure was already designed to ingest and deploy these models seamlessly. With massive developers teams, these firms also saw an immediate productivity boom.

However, the narrative shifts dramatically when moving beyond this high-tech environment. For the vast majority of traditional enterprises, AI remains trapped in what we can call Pilot Purgatory. Behind the polished marketing narratives intended for shareholders lies a much more complex financial reality.

Costs and ROI

Integrating artificial intelligence is not as simple as purchasing a license, it is a collision with massive structural costs. The first hurdle is the build and glue cost (the interfaces and plumbing required to connect a cutting-edge language model to legacy systems). This custom development often carries a price tag that dwarfs the short-term productivity gains the company hoped to achieve.

Beyond the initial setup, maintenance has emerged as the new financial sinkhole for the unprepared. An AI model is not a static piece of software, it is a "living" entity subject to constant drift. To remain effective, these models must be monitored, re-tuned and adjusted almost constently. If neglected, their accuracy and relevance collapse within months. This lifecycle management, coupled with the recurring token tax for every model call, creates a variable cost structure that can quickly erode the calculated gains if the tool is not used with surgical precision or ROI driven by the use cases is not big enough.

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CAPEX diversion

Currently, CIOs are aggressively diverting significant portions of their CAPEX toward AI initiatives, often at the expense of traditional IT systems. However, because most of these projects remain in the POC stage, they have yet to deliver the exceptional ROI needed to self-fund. The result is a productivity paradox in the short term: companies are incurring the heavy costs of AI setup and integration without a corresponding surge in significant gains. This strategic pivot is a primary driver behind the current slowdown in broader IT spending (excl. AI). It is not that legacy systems or standard software suites have become obsolete. Rather, we are witnessing a tactical diversion of funds as organizations bet heavily on an AI future, creating a temporary budgetary bottleneck for the rest of the tech stack.

The future of software

This perspective leads to an inevitable conclusion for the enterprise: the path from experimental cost-center to true industrial scale-up will be paved through deep integration into existing software ecosystems, rather than the creation of isolated AI islands. As I explored in my previous analysis of the SaaSpocalypse, the market’s recent brutal repricing of the software sector was not a signal of the death of software, but rather the death of the un-integrated, seat-based business model. While thin-wrapper apps and horizontal tools face an existential threat from AI’s ability to automate simple human tasks, the mission-critical platforms (the Agentic Fortresses) are becoming more indispensable than ever.

The current complexity and maintenance burden of bespoke AI deployments prove that even the most advanced autonomous agents require a system of record to function. As NVidia CEO Jensen Huang noted during the peak of the February 2026 market anxiety, it is illogical for an AI to reinvent the wheel when it can simply use a proven tool. For the enterprise, this means that the real ROI will materialize when AI stops being a standalone experiment and starts integrating established, high-gravity systems. These incumbents will decouple their revenue from human headcount and anchoring it to the value of work completed by AI, effectively turning seat compression into a story of margin expansion and architectural dominance.

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A shoe brand

Allbirds began as the ultimate symbol of Silicon Valley’s “cool” minimalism, launching in 2016 with a merino wool sneaker that promised a revolution in sustainable footwear. By the time of its 2021 IPO, the company was a venture capital darling valued at over $4B, fueled by a narrative that it was a materials science powerhouse rather than just another apparel brand. It captured the zeitgeist of the ESG movement, appearing on the feet of everyone from tech CEOs to former presidents and successfully commanded premium pricing for a product that prioritized comfort and carbon neutrality. This initial success was built on a genuine quality brand identity and niche market dominance, leading many to believe that the direct-to-consumer model had finally produced a permanent retail titan.

However, the descent was as rapid as the ascent was meteoric. In a desperate attempt to justify its tech-like valuation, Allbirds expanded into overpriced apparel and expensive brick-and-mortar flagships that hemorrhaged cash while alienating its core audience. By the time the company filed its 2025 reports, the brand was in a death spiral of declining sales and mounting losses. The current market cap is now $90M (and was under $20M 2 weeks ago). The destruction of $4 billion in shareholder value was nearly absolute, leaving behind a hollowed-out corporate shell that had failed at its primary mission, only to pivot toward the AI frenzy in a last-ditch effort to exploit the market’s current obsession.

The pivot

The pivot from Allbirds to NewBird AI represents one of the most jarring corporate transformations in recent memory, marking the final abandonment of a once-celebrated retail vision. After offloading its entire footwear IP and sustainable branding for a fraction of its former value, the company’s husk secured a $50M credit facility to purchase high-end GPUs and rebrand as a GPU-as-a-Service provider. This shift from merino wool to silicon chips was not born of strategic synergy, but of survivalist opportunism. By shedding its physical inventory and operational baggage, the company successfully leveraged the AI suffix to trigger a massive short squeeze and a 400% surge in its stock price, effectively trading its identity for a ticket to the current tech mania.

The hype cycle

The Gartner Hype Cycle, which illustrates this journey of market sentiment, begins with an Innovation Trigger that sparks massive public interest, leading directly to the Peak of Inflated Expectations. At this summit, the excitement surrounding a technology’s potential completely decouples from its current utility, leading to irrational valuations and a FOMO among investors. Following this peak, the market invariably collapses into the Trough of Disillusionment as the reality of implementation fails to meet the hype, before eventually climbing the Slope of Enlightenment toward a Plateau of Productivity where the technology finally finds its practical, sustainable value.

As usual, the market overestimates AI in the short term while underestimating the long-term reality.

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A red flag

NewBird AI is the definitive signal of Peak Expectations because it demonstrates that the market is currently rewarding the mere label of AI over any actual competitive advantage or operational history. In a rational market, a failing footwear brand with no infrastructure, no specialized engineering talent and a rounding error budget for compute would be viewed as a non-competitor against hyperscale titans like Microsoft or AWS. However, when the worst companies on the exchange can mint hundreds of millions in market cap simply by promising to buy a few server racks, it proves that speculative fervor has reached its ceiling. Much like the Long Blockchain pivot of 2017 or what we saw in the dot com bubble, this event marks the moment where the narrative has become so thin that it can no longer support the weight of the hype, signaling that a descent into the Trough of Disillusionment is imminent.

Conclusion

To be clear: I am an AI optimist. We are witnessing a genuine industrial revolution. However, as I have cautioned before, long-term transformation is often preceded by short-term delusion. Most analysts lack a granular understanding of how AI is actually integrated into a P&L, leaving them unable to forecast what will happen (or when and who will be the winners). My advice remains simple: stay disciplined, trust the data over the headlines and don’t let the frenzy derail your long-term plan.

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The current market environment feels like a minefield. For most investors, the pain is palpable: portfolios are bleeding and high-growth favorites are in freefall.

However, as of today, the S&P 500 is down only 4% YTD. To the casual observer, this looks like a minor, healthy pullback. The consensus is already shouting for us to buy the dip, treating this as just another temporary hurdle on the way to new highs.

But what if this pain is not the climax? What if it is merely the prologue?

History tells us that true market corrections don’t start with a bang; they start with this exact type of stealth erosion, where the broader index is propped up by a few megacap titans while the foundation underneath them quietly crumbles. With a potential return of the inflation, oil above $100, geopolitcal risks, a potential recession in the US and the AI premium finally facing a reality check, the gap between the index and economic reality is huge.

In this article, we will peel back the mask of the S&P 500 to reveal why the real fall may only just be beginning. More importantly, we will outline the strategy designed not just to survive the coming volatility, but to turn a potential broader correction into a generational opportunity.

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The illusion of strength

The 4% drop of the S&P500 hides a structural rot in market breadth. Historically, a healthy bull market is supported by a broad base of participating stocks. Today, we are seeing the opposite. We are witnessing a market where a decreasing number of stocks are carrying the entire weight of the index.

While the headline index sits near its highs, over 50% of its individual constituents are already in their own private bear markets, down 20% or more. This narrowing breadth is a classic late-cycle signal.

Perhaps the most alarming sign is the market’s current denial regarding global instability. Usually, markets react sharply to threats of energy disruption. Yet, despite Brent crude surging toward $110 per barrel due to escalating tensions in the Strait of Hormuz, the broader stock market has remained strangely unfazed. The market is pricing a short war with limited impacts.

The disconnect between Wall Street and reality has reached a breaking point. While unemployment ticks up to 4.4%, $110 oil acts as a silent tax on the economy, recession might be coming, the S&P 500 remains anchored to bubble-era valuations. We are seeing the classic hallmark of a late-stage cycle.

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Far from a true bear market

Predicting the exact depth of a market cycle is a fool’s errand and I make no claims to have a crystal ball. However, history provides a sobering map: in the most severe secular bear markets, the S&P 500 has historically bottomed at a PE multiple below 10x. While I am not forecasting a return to those depths, a disciplined investor must account for that tail risk. We don't build strategies based on what we hope will happen, we build them to withstand the full range of historical scenarios.

The strategy

In a market defined by extremes, the most dangerous thing an investor can do is succumb to binary thinking. On one side, you have the all-in influencers urging you to chase every 2% bounce, ignoring the systemic risks under the surface. On the other, you have the perma-bears sitting entirely in cash, waiting for a bottom that may never look exactly how they imagine it.

Both of these extremes are traps. Being fully invested right now ignores the lack of a margin of safety in current valuations. However, being entirely uninvested is historically the most effective way to destroy long-term performance. Missing just a handful of the market’s best days, which often occur during high-volatility regimes, can permanently stunt your compounded returns.

The strategy for the Quality Investor is neither blind optimism nor total retreat. It is Tactical Deployment.

The goal is to move through this correction with a buy zone framework (the action part of the Quality Stocks Investment Framework). Instead of trying to time a single bottom, we deploy capital progressively as high-quality businesses hit levels of extreme value. This is why I consistently provide 3 distinct Buy Zones for every stock I cover. While the third buy zone often feels impossible during a bull market, it is triggered only during periods of true capitulation and forced liquidation. Buying here is how generational wealth is cemented.

By using this tiered approach, you remove the emotional burden of being right about the macro bottom. You are not guessing, you are reacting to price. If the market only drops 10%, you have your exposure. If we see the sub-10x PE scenario I mentioned earlier, you have the dry powder and the psychological roadmap to buy when everyone else is selling.

If you listen to the quarterly earnings calls of the Magnificent 7 in 2026, the narrative is near-unanimous: the risk of under-investing is far greater than the risk of over-investing. This sentiment has fueled a historic arms race, with annual CAPEX across the tech giants now soaring toward the half-trillion-dollar mark.

To the average growth investor, this looks like a bold bet on the future. But to a student of the Capital Cycle, it looks like a classic siren song. History is littered with revolutionary technologies that followed a predictable & painful pattern. When capital floods a sector indiscriminately, the result is rarely a sustained moat. Instead, it creates a glut of supply that triggers commoditization, erodes pricing power, and ultimately collapses Return on Invested Capital (ROIC).

In this issue of Quality Stocks, we are stepping away from the excitement of what AI can do to look at the math of what the current investment binge will do. We are exploring the supply-side trap of the AI revolution and why the most innovative companies often make the poorest long-term investments.

To be clear: I am a firm believer in AI’s transformative power. The demand is undeniable. However, my background in Supply Chain management has taught me to spot the Bullwhip Effect long before it hits the balance sheet. Just as distorted demand signals can wreck a global supply chain, overinvestment in AI could create excess capacity. For over 2 years, this newsletter has been about avoiding traps. Today is no exception!

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The engine of overinvestment: understanding the capital cycle

Here is the first section of your article. It establishes the “Capital Cycle” framework and uses the historical parallel of the fiber-optic bubble to show your readers why “believing in the tech” isn’t enough to justify the investment.

The Engine of Overinvestment – Understanding the Capital Cycle

To understand why massive investment can be a red flag, we must look at the “Capital Cycle”, a framework made famous by financial historian Edward Chancellor.

Most analysts spend 90% of their time obsessing over demand: How many people will use ChatGPT? How many enterprises will integrate Copilot? But for a Quality investor, another important question is almost always about supply.

The Capital Cycle is a simple, recurring psychological and economic loop:

• 1. The flare. An industry enjoys high returns on capital (ROIC), often due to a new technology

• The rush. These high returns act as a flare, attracting a flood of capital from CEO, VC and Wall Street

• The glut: This capital is used to expand capacity (more factories, more chips, more data centers)

• The crash. Eventually, supply outstrips demand. To fill that excess capacity, companies slash prices. Profits vanish, capital flees and only then (when the “weak hands” are liquidated) does the cycle start over, leaving survivors more powerful

As Chancellor notes: “high returns tend to attract capital, just as low returns repel it”. Today, we watch hundreds of billions pour into AI shovels.

Is AI spending excessive?

In supply chain management, we often talk about the Bullwhip Effect: how a small nudge in consumer demand can lead to massive, distorted over-ordering at the top of the chain. In 2026, we are not just seeing a nudge, we are witnessing a global scramble for capacity that has no historical equal.

To understand the scale, look at the CAPEX guidance for the “Big Five” (Amazon, Microsoft, Google, Meta, and Oracle) for this year. Collectively, they are projected to spend a staggering $650B on infrastructure.

For over a decade, the “Quality” thesis for Big Tech was built on their asset-light nature. They generated billions in cash because they did not need to build massive physical networks. That era is over. The new reality: by early 2026, these companies are spending nearly 65% of their gross profit on Capex, a level of capital intensity comparable to ExxonMobil or Ford.

Why are they spending this much? Because they have entered a prisoner’s dilemma. If Microsoft stops buying H200s or B200s, they risk losing their cloud lead to Google or Amazon. They are spending to stay relevant.

In a capital cycle, when investment is driven by the fear of being left behind rather than clear, incremental Return on Invested Capital (ROIC), the cycle is nearing its peak. As we move into 2026, the gap is widening: CAPEX is growing at 30–50% while the AI-enabled revenue at the software layer is struggling to keep pace.

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The commoditization trap

The first sign of the trap is the Price War. As long as volume increases very fast, this is not an issue, but it could squeeze margins in the long-term. Efficiency gains have driven AI token costs down by over 70% annually (maybe just a sign that we are at the beginning of the learning curve).

Chinese models like DeepSeek and open-weight giants like Llama 4 have broken the premium paywall. Western incumbents are being forced to slash prices just to maintain market share: OpenAI recently implemented an 80% price cut on flagship APIs.

For the Hyperscalers (Microsoft, Google, Amazon), this is a nightmare for margins. They are spending record sums on infrastructure while the unit price of their output is plummeting. When margins are squeezed at the top, the first thing to be cut is the next round of capital investment.

Note: we are likely witnessing a fundamental shift in the AI value chain. The capital cycle suggests that money will not be made in the models (which are being commoditized), but in the application. We will therefore see the revenge of the SaaS. The ultimate winners might be the software companies that leverage cheap, standardized AI to deliver massive value to end-users.

The Whiplash for Equipment Providers

The real first danger of the capital cycle lies with the companies that provide the tools for the shovels:the semiconductor equipment manufacturers like ASML, Applied Materials (AMAT), Lam Research (LRCX) and KLA Corporation (KLAC).

For now, orders are massive, driven by the massive capacity expansion of TSMC and Intel. On the surface, this looks like a secular bull market. But through a supply-chain lens, it looks like a classic shortage gaming peak.

When a chipmaker like TSMC or Samsung fears they won’t have enough capacity for the next generation of Nvidia’s Rubin or Blackwell chips, they don’t just order what they need, they order for future needs based on current forecast (that are rather optimistic). This creates a demand cliff.

The equipment providers (at the very top of the whip) will feel the snap first and hardest. History tells us that in a capital cycle, the companies with the most impressive backlogs today are often the ones with the most painful cancellations tomorrow.

The cyclical nature of equipment providers (ASML, AMAT, etc) is a masterclass in operational leverage. A 20% decline in end-user demand does not lead to a 20% revenue dip for the toolmakers. It leads to a total stop of new investment as customers digest their over-ordered capacity.

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Spotting the survivors

To find the stocks that can weather the capital cycle whiplash, I am looking for 3 specific traits.

The first trait to look for is deep vertical integration, a strategy exemplified by giants like Alphabet and Microsoft. Rather than being at the mercy of the capital cycle’s whiplash, these companies have spent the last few years building closed loops. By designing their own silicon, such as Google’s TPUs and owning the massive distribution networks of Search, Office and Cloud, they have effectively reduced their dependency from where the price wars are happening: at the model layer.

The second trait marks what I call the real value providers. While the market was obsessed with who would build the biggest LLM, the true quality survivors may be the software companies that will successfully moved into the deployment phase. These firms don’t need to win the intelligence race because they will win the workflow race. By embedding cheap, standardized AI into existing enterprise systems like SAP, ServiceNow or Dassault Systemes, they turn a volatile technology into a sticky & high-margin utility. Another value provider comes from the physical bottlenecks of the cycle, specifically the energy and ressource providers. While GPU orders can be canceled in a heartbeat due to the bullwhip effect, the structural demand for electricity to run the world’s data centers is only moving in one direction

Conclusion

We are currently standing at a crossroads where technological potential meets economic reality. There is little doubt that AI represents a generational shift: a transformative force that will reshape how we live, work and create. However, as investors, we must decouple our enthusiasm for the technology from our discipline regarding the capital cycle. History suggests that the more revolutionary a technology feels, the more likely it is to attract the kind of undisciplined capital that destroys long-term returns and create risks.

Risks are high that the next few years will be defined by disillusionment for the some actors. As the Bullwhip Effect snaps and the Price War at the model layer intensifies, many of today’s market darlings will find that their massive CAPEX bills have become anchors rather than engines. The winners of the infrastructure phase will probably not be the winners of the deployment phase: the risk being on the equipment providers.

To succeed in this environment requires a contrarian mindset: the courage to look past the current order backlogs and focus on who actually owns the customer, the energy and the workflow.

The narrative driving this sell-off is simple: If AI can write code, automate workflows and replace human seats, then the $600B SaaS industry is a house of cards. But this view misses the nuance of evolution. While thin-wrapper apps and horizontal tools are indeed facing an existential threat, a new class of software is emerging. We are not witnessing the death of software, we are witnessing the death of the un-integrated, seat-based business model. The moats are not disappearing, they are moving.

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The SaaSpocalypse

The "SaaSpocalypse" of has been defined by a brutal market. We saw this play out in real-time with a lot of software like Dassault Systemes, which suffered its worst trading day in history on February 11th, with shares plunging over 20% following their Q4 release. Despite a stable operating margin of 37%, the market balked at a mere 1% revenue growth and a 2026 guidance that felt like a relic of the pre-AI era.

In this environment, investors are ruthlessly repricing any incumbent that has not yet proven it can turn AI agents into a meaningful top-line driver, proving that the old "subscription stability" moat is being breached.

What does the market fear?

For years, the software-as-a-service model thrived on a simple, linear relationship where revenue grew in tandem with customer headcount (per-seat). However, the sudden proliferation of agentic AI tools like Claude Cowork has effectively decoupled software from labor. When a single AI agent can autonomously navigate a CRM, log support tickets and generate compliance reports, the need for dozens of human licenses evaporates. This seat compression turned the sector’s most reliable growth engine into a liability overnight, as investors realized that the more efficient a software’s AI becomes, the fewer paid users it actually requires.

Beyond the shrinking user base, the sell-off reflects a growing fear that traditional software moats are being dismantled by vibe coding and AI-native competition. In this new regime, the barrier to entry for complex software has dropped significantly that internal IT teams and small startups can recreate specialized tools in a fraction of the time it once took. This has led to a ruthless prioritization within enterprise budgets. To fund massive investments in AI infrastructure and chips, companies are auditing their SaaS portfolios and cutting soft ROI tools that offer simple productivity gains.

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Which software will survive?

The software that find themselves in the most immediate danger are those whose primary value is serving as a visual interface for human coordination. Platforms like Monday are particularly vulnerable because they are often utilized as horizontal project management tools where revenue is strictly tied to the number of people logging in to update statuses. Additionally, the level of integration is very low.

In a world where AI agents can autonomously track progress and sync data across teams, the need for dozens of individual human seats for simple check-in work evaporates. This is reflected in the market’s nervous reaction to companies that still rely on per-seat pricing for basic collaboration, as these tools risk becoming ghost towns where the work is happening via background automation rather than active human engagement. This same risk extends to basic point solutions in marketing or customer support that offer productivity gains for humans but fail to capture the value of the actual work being performed by AI.

In contrast, the software companies that will thre during this transition are those that have repositioned themselves as the essential execution layer for the agentic era.

ServiceNow serves as a prime example of a survivor: it has effectively moved from being a ticketing interface to a system of action where its workflows are deeply integrated into the core IT and HR plumbing of an enterprise. Because an AI agent requires these structured workflows and data permissions to execute a task (like onboarding an employee or resolving a server crash) ServiceNow becomes more valuable as automation increases, regardless of how many humans are involved.

Similarly, Salesforce has aggressively pivoted toward outcome-based monetization through its Agentforce platform, which charges per conversation or action rather than just per user. By decoupling their revenue from headcount and anchoring it to the successful completion of work.

To identify the software survivors in your portfolio, look for these characteristics:

• System of record dominance. The software acts as the single source of truth for proprietary enterprise data (like financial ledgers, clinical records or supply chain physics) that AI agents require to function accurately. Examples: SAP, ServiceNow or Manhattan Associates

• Outcome-based monetization. The business model has successfully decoupled from human headcount, instead charging based on the value or work completed by AI agents Examples: Salesforce

• High architectural gravity. The platform is so deeply integrated into the company’s mission-critical workflows and regulatory compliance stacks that the cost and risk of ripping and replacing it are prohibitively high. For those outside the industrial sector, it is difficult to grasp the sheer gravity of an enterprise deployment. Unlike a simple SaaS subscription, integrating a PLM or ERP system is a multi-year digital heart transplant where the technical complexity and implementation costs create a moat that AI cannot simply bypass. Examples: SAP or Dassault Systemes

• Agentic interoperability. The software offers robust, high-velocity APIs that allow autonomous agents to not just read data, but to execute complex write actions back into the system of record. Example: ServiceNow

• Vertical specialization. The product solves highly complex, industry-specific problems (like specialized engineering simulation or legal discovery) where generic LLMs lack the necessary precision and domain-specific guardrails. Examples: RELX or Dassault Systemes

3 Examples

1. ServiceNow

ServiceNow is the ultimate System of Action. While the market fears AI will replace human help desks, it ignores that an AI agent still needs a structured environment to execute tasks. ServiceNow provides the plumbing for the enterprise. Its high-velocity APIs allow autonomous agents to not just identify a problem, but to write the fix directly into the IT record. By moving toward a model where they charge for the value of the automated resolution rather than the number of agents sitting in a call center, they are turning "seat compression" into a margin expansion story.

• System of record 🟢

• Outcome-based monetization 🟠 (emerging)

• High architectural gravity 🟢

• Agentic interoperability 🟢

• Vertical specialization 🔴 (or partial with IT, Supply Chain or Finance)

2. SAP

SAP represents the Digital Heart of the global economy. As the primary system of record for finance and ERP, it holds the proprietary data that a corporate AI needs to be accurate. You cannot have an AI agent manage a supply chain if it does not have access to the real-time ledger and inventory data that lives inside SAP. Because these deployments are digital heart transplants with high architectural gravity, the risk of an AI startup replacing SAP is virtually zero. The AI will simply become a new interface for the SAP engine.

• System of record 🟢 (transactions and finance at least)

• Outcome-based monetization 🟠 (emerging)

• High architectural gravity 🟢 (the heart)

• Agentic interoperability 🟠

• Vertical specialization 🔴

3. Dassault Systemes

Dassault is the definition of Vertical Specialization. Their PLM (Product Lifecycle Management) tools manage the physics and engineering of ultra-complex products like aircraft and surgical equipment. This is not word processing, it is high-precision simulation. Their moat is built on decades of deeply integrated engineering IP and a technicity that creates massive switching costs.

• System of record 🟢 (product)

• Outcome-based monetization 🟠 (emerging)

• High architectural gravity 🟢

• Agentic interoperability 🟠

• Vertical specialization 🟢

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Conclusion

Panic is rarely a profitable strategy. While SaaSpocalypse headlines focus on the loss of seat-based revenue, they ignore the birth of a new industry. When technology makes a task easier, the volume of that work explodes. The Agentic Fortresses controlling the System of Record will capture this volume, transitioning from human tools into autonomous engines.

These companies are not static, they are reinventing themselves. NVidia CEO Jensen Huang addressed this market anxiety in February 2026, calling the fear that AI would replace software “the most illogical thing in the world”. He argued that even the most advanced AI will choose to use a proven tool rather than reinventing it:

For the patient investor, this anxiety is a gift: a chance to acquire mission-critical infrastructure like Dassault Systèmes or SAP at a discount. These platforms are currently challenged but they are not yet disrupted. By pivoting toward outcome-based pricing and becoming the execution layer for AI, they are securing the next decade of growth.

As always, caution is key. if you like this sector, don't blow your capital on one entry, scale in and stay diversified to weather the volatility.

I have scored 21 industry leaders using the Quality Stocks Investment Framework to find the best opportunities in the current sell-off

Silicon Valley and Wall Street are currently locked in a high-stakes drama: The Two Acts of AI. In Act I, the narrative is driven by raw power: an infrastructure arms race where the price of admission is measured in billions of dollars, gigawatts of energy and hundreds of thousands of chips. It is a period of rational over-investment, where the risk of being left behind outweighs the risk of overspending.

However, the curtain is beginning to rise on Act II: The End-User Reality. This is where the hype hits the spreadsheet. The market’s focus is shifting from who can build the most sophisticated model to who can monetize it at scale.

This article explores the tension between these two acts. We will analyze why the current winners of the hardware gold rush may not be the same names that dominate the coming era of application and how market fears of a CAPEX bubble are not necessarily absurd.

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The infrastructure arms race

With collective capital expenditures projected to exceed $650B in 2026, Microsoft, Alphabet, Amazon and Meta are outspending the entire annual GDP of mid-sized nations.

This massive wave of CAPEX is not just a line item on a balance sheet: it is a tidal wave of liquidity feeding an entire global ecosystem. It flows from the hyperscalers directly into a specialized supply chain that has become the new backbone of the global economy (and one of the only remaining part of the US economy still growing).

The immediate beneficiaries are the high-profile architects of intelligence: the chip designers like NVIDIA and AMD of course but the money travels much deeper. It reaches:

• The foundries and memory giants like TSMC, Micron, and Intel

• Equipment manufacturers like ASML, Lam Research and Applied Materials

• The software used to design these impossible circuits, provided by Synopsys and Cadence

• The companies actually building and cooling the datacenters Schneider Electric or Vertiv

When you look at this side of the ledger, there is no room for doubt. The $650B is real, tangible and currently changing hands. This is not speculative paper money or vaporware. It is hard capital funded by the cash cow” of the digital age '(like Alphabet’s advertising and Microsoft’s software ecosystem). Furthermore, these giants are now leveraging their pristine balance sheets to issue debt, guaranteed by their massive cash flows, to ensure they don’t lose an inch of ground in the race.

The end-user reality

If the money is real and the infrastructure is tangible, why does a sense of unease still permeate the market? The answer lies in the fundamental tension between the equipment cycle and the adoption cycle. While the supply chain is moving at warp speed, the end-user reality is dictated by human and institutional inertia.

The first risk is a matter of integration. Currently, most enterprises are in Proof of Concepts (POCs) phase that have yet to touch the core of their business models. While digital-native firms are sprinting ahead (like Alphabet using AI to better target users with ads), the traditional giants (the Fortune 500) move with a measured speed. For AI to truly pay off, it cannot remain a standalone chatbot on a side tab, it must be deeply embedded into the enterprise software that governs daily workflows. Until we see wide-scale implementation that produces measurable productivity gains on a balance sheet, the end-user reality remains more of a promise than a profit. I have no doubt AI will dramatically change companies, but it may be slow.

Secondly, there is the risk of a mismatched tempo. By spending $650B in a single year, hyperscalers are betting that entire industries will transform. But history shows that the global economy is a massive vessel that turns slowly. If adoption lags even slightly behind these aggressive projections, we will likely witness a classic Bullwhip Effect. This supply-chain phenomenon occurs when over-anticipation at the top leads to a catastrophic collapse in orders further down the line. If the hyperscalers realize they have built too much too fast, the orders for chips and equipment will not just slow down, they will evaporate as the industry corrects for overcapacity. In such a scenario, the current hardware premium would vanish, replaced by a brutal price war.

Finally, we must look at the structural endgame. If the end-user usage succeeds too well, it brings a new set of existential questions. If AI truly displaces millions of white-collar roles, it alters the very foundation of the consumer economy. We have to ask: in a world where labor is radically decoupled from production, will consumption patterns remain the same?

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Conclusion

Ultimately, the market’s fear is rooted in this decoupling. We have an equipment cycle running on high-octane rocket fuel, while the end-user adoption cycle is still navigating the speed bumps of corporate culture and economic inertia. Whether these two cycles eventually sync up or collide will define the next decade of the global economy. The winners of Act I are already on the podium, the winners of Act II have yet to even enter the stadium.

In this article, we will peel back the layers of the earnings report to uncover the negative spots hidden beneath the growth metrics. From a record-breaking $37.5B CAPEX bill to a sudden transparency regarding OpenAI exposure, we will explore why the market is suddenly demanding more than just a beat, it is demanding a clearer path to ROI.

Beyond the earnings, we analyze a deeper trend: a fundamental change in the market's risk appetite. We will discuss why this new stance from analysts might be the opening chapter of a major sector-wide correction.

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Earnings report summary

Microsoft delivered a powerhouse performance for its fiscal Q2 2026, surpassing Wall Street’s expectations on nearly every major metric. Revenue reached a record $81.3B (+17% YoY) while adjusted EPS hit $4.14, handily beating the $3.93 consensus.

The Intelligent Cloud segment remained the primary engine of this growth, with Microsoft Cloud revenue crossing the historic $50B milestone for a single quarter. Azure specifically grew 39% (38% in constant currency), proving that the appetite for AI infrastructure and enterprise cloud services remains robust.

The darker side of the results

In the following sections, I will break down the specific catalysts that spooked the market. However, my analysis leads to a different conclusion than the current consensus. After we examine the red flags through the market's lens, I will present my view.

1. The artificial GAAP EPS boost

Impact: ⭐️ (low)

A major point of confusion in this report is the massive gap between Microsoft’s reported GAAP earnings and its operational reality. On a GAAP basis, diluted EPS skyrocketed 60% to $5.16, but this figure was heavily inflated by a net gain related to investments in OpenAI.

When you strip away these non-cash accounting gains to look at the actual business performance (Non-GAAP), the EPS drops to $4.14. While a $4.14 result is still a beat, the market realized that the headline growth was fueled by paper gains rather than purely by the company’s activities.

2. The surge in CAPEX

Impact: ⭐️⭐️⭐️ (high)

The most glaring concern was the massive jump in capital spending, which reached a record $37.5B for the quarter, a 66% increase YoY. Investors are beginning to push back against this blank check approach to AI infrastructure, fearing that the bill for data centers and chips is growing much faster than the actual profits they produce. This surge in spending has directly pressured free cash flow, leading to a timing mismatch where the costs are immediate, but the financial rewards remain years away.

3. The OpenAI concentration risk

Impact: ⭐️⭐️ (medium)

For the first time, Microsoft revealed the scale of its dependency on a single partner, disclosing that 45% of its $625B commercial backlog (approximately $280B) is tied specifically to OpenAI. This created a concentration risk alarm for Wall Street: if OpenAI faces a slowdown (due to competition or slower than expected adoption), regulatory hurdles or financial instability, nearly half of Microsoft’s future growth projections could vanish. Analysts pointed out that when you strip away the OpenAI contracts, the organic backlog growth was a much more modest (28%).

4. Azure’s disappointing growth

Impact: ⭐️⭐️ (medium)

While a 39% growth rate would be a triumph for almost any other company, analysts expected more. History appears to be repeating itself. For those with a long memory, this mirrors the 2022 sell-off when analysts punished the stock for a mere 1% miss on Azure growth expectations. The market was positioned for an acceleration above 40%. Instead, Azure’s performance suggests that Microsoft is hitting a temporary growth ceiling. Management attributed this to capacity constraints, essentially admitting they cannot build data centers fast enough to meet demand.

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My analysis

While the market’s reaction was swift and severe, I believe we are seeing a classic case of short-term overreaction fueled by profit-taking. Microsoft’s valuation, while certainly not cheap, was far from irrational given its dominant position and growth outlook. However, as we saw in 2022, the market treats any Microsoft miss (even a 1% deviation) as a catalyst to derisk.

In my view, this -10% move says less about Microsoft’s fundamental health and more about a market that was looking for any excuse to rotate out of high-flying tech. We are currently witnessing a significant market rotation. While headlines focus on the tech giants, defensive sectors like healthcare and utilities are quietly outperforming.

This volatility may be the first signal of a deeper shift in the market’s psychological state. Historically, the stock market is a discounting mechanism that anticipates the next phase 6 to 9 months in advance. The aggressive punishment of a double beat may suggest that investors are silently bracing for a transition, perhaps preparing for the next bear market.

If the market is indeed shifting its stance, the focus will move from growth at any cost, to capital preservation, margins and recession-proofing. Microsoft is not failing, rather it is the canary in the coal mine for a market that is fundamentally rethinking its appetite for risk as we move further into 2026.

Buy the dip or wait? My view

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Over time, writing regularly about stocks has helped me progressively clarify my own investment process. Distinguishing between a high-quality business and a good investment opportunity, setting realistic return expectations, and managing uncertainty around timing and execution are challenges that require structure, not just individual stock ideas. What emerged progressively was not just a collection of stock ideas but a more structured and repeatable decision process.

This article has 3 clear objectives:

• First, it introduces the Quality Stocks Investment Framework, a structured approach that will now underpin all stock analyses shared in the newsletter. The framework is designed to support the entire selection and decision process by answering the key questions that arise throughout the investment journey: do I buy this stock, how much could I reasonably expect, and when should I buy it?

• Second, it defines a more structured editorial line for Quality Stocks going forward. All future content will follow clearer principles, with standardized analyses using the Quality Stocks Investment Framework and one-pagers, making it easier to compare ideas over time and understand how conclusions are reached.

• Finally, this article presents an updated free and paid value proposition. The goal is to clearly distinguish between content that focuses on education and individual analyses, which will remain freely accessible, and content aimed at the systematic application of the framework, screeners, portfolio-level thinking and decision support, which will be reserved for paid subscribers.

The objective is not to change the philosophy of the newsletter, but to formalize it, making Quality Stocks more consistent, more transparent and more useful for readers who approach investing as a long-term, disciplined process.

1. Introducing the Quality Stocks Investment Framework

The visual above illustrates how the Quality Stocks Investment Framework will now be applied consistently across Quality Stocks. The objective of this one-pager is not to summarize everything about a company, but to make the investment decision process explicit and easy to follow. Each section corresponds to one step of the framework and answers a specific question an investor faces.

Step 1. Selection

Is this a quality investment?

This first step focuses on whether a stock deserves consideration at all. It combines data-driven indicators around growth, quality and valuation to assess if the business meets the minimum standards required to enter the investment universe. This assessment is complemented by a checklist designed to highlight key points that require attention. If a stock fails at this stage, it is excluded from further consideration regardless of narrative or popularity.

Step 2. Return Potential

What return can I reasonably expect?

Once a stock passes the selection phase, the framework moves to explicit return expectations. This step translates business fundamentals and valuation into a projected Total Shareholder Return (TSR) over the long term, based on clear assumptions around growth, margins, valuation evolution, and capital returns.
The goal is not precision, but clarity around what must go right for the investment to deliver acceptable returns.

Step 3. Execution

What are the buy zones?

Even high-quality businesses can be poor investments if bought at the wrong price.
This step introduces staggered buy zones to manage valuation and timing risk, acknowledging that uncertainty is unavoidable. Rather than a single entry point, the framework favors disciplined execution through multiple potential entry levels.

Step 4. Overall Verdict

The final verdict (Attractive, Conditional or Unattractive) synthesizes the previous steps into a clear, actionable conclusion based on the current price. Importantly, this verdict is not permanent. It can change over time as fundamentals, valuation, or market conditions evolve.

What changes going forward

The same framework will also be applied beyond individual analyses, including: stock analysis, stock screeners, thematic selections and tools.

A dedicated article will follow shortly to fully detail the Quality Stocks Investment Framework, including its underlying assumptions, limitations, and how it is used consistently across different types of content.

The goal is to bring more clarity, consistency and discipline to how investment decisions are presented and discussed, helping investors adopt a more structured decision-making process and derive real value from the newsletter.

2. A more structured editorial line

To support a clearer and more consistent editorial line, content published in Quality Stocks will now be organized around a few well-defined formats, each serving a specific purpose.

• Stock of the Week. A regular focus on a stock experiencing a strong news flow or a meaningful change in its investment case. Each article will combine situational analysis with a one-pager applying the Quality Stocks Investment Framework.

• Stock Analysis. Analyses of individual companies, often less followed or less well-known, with the objective of helping readers discover interesting long-term investment ideas. These analyses will systematically follow the investment framework.

• Stock Screeners and Thematic Selections. Systematic screenings and thematic investment selections using the Quality Stocks Investment Framework, providing all the necessary elements to assess whether an investment opportunity is attractive, conditional, or unattractive.

• Portfolio Follow-Up. A monthly review of my portfolio, complemented by dedicated articles whenever a position is initiated, adjusted, or exited, with a clear explanation of the underlying decision.

• Miscellaneous Articles. Occasional articles covering broader market developments, investment knowledge, behavioral topics, or specific elements of the investment process.

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3. Updated free to paid value proposition

The approach behind Quality Stocks is deliberately progressive. Free subscribers have access to the core elements of the newsletter: individual analyses, one-pagers, market insights, and educational content, allowing them to understand the framework, follow investment ideas and learn over time.

Paid subscribers, on the other hand, gain deeper insight and access to the full set of tools, including screeners, thematic selections and portfolio follow-up, enabling them to apply the Quality Stocks Investment Framework more systematically and integrate it fully into their own investment decision process.

Free content

Free content will continue to focus on education, transparency, and individual analysis. This includes:

• Individual stock analyses using the full Quality Stocks Investment Framework

• The standardized one-pager format

• Stock of the Week articles combining news flow analysis and framework-based assessment

• Investing knowledge, market commentary and process-related articles

The goal of free content is to make the framework understandable, visible, and useful on a case-by-case basis.

Paid content

Paid content is designed for readers who want to apply the framework more systematically and integrate it into their own decision-making process. This includes:

• Stock of the Week. Access to the detailed TSR calculation, including underlying assumptions, to follow how the investment hypothesis is built and monitored, as well as my full analysis of the situation

• Stock Analysis. Access to the detailed TSR calculation, along with my full analysis beyond the overall verdict, including explicit bull and bear cases to support a more informed and disciplined decision process

• Stock Screeners and Thematic Selections. Full access to all stocks included in thematic selections and screeners. For each stock, access to the complete Quality Stocks Investment Framework, including the score, fair value assessment, projected TSR, and defined buy zones, providing actionable insights

• Portfolio Follow-Up. Full access to my portfolio and watchlist, with transparent updates and explanations provided on the day positions are initiated, adjusted, or exited

The purpose of the paid subscription is to help readers move from understanding investment ideas to applying a structured decision process consistently. The paid subscription is most relevant for readers who:

• Already invest their own capital

• Care about process more than predictions

• Want to reduce behavioral mistakes

• Value transparency and consistency over hype

Conclusion

Over the past 2 years, Quality Stocks has evolved from a collection of stock ideas into a more structured way of thinking about investment decisions. The introduction of the Quality Stocks Investment Framework, a clearer editorial line, and a more explicit free and paid value proposition are simply the formalization of that evolution.

The framework is not meant to predict outcomes or eliminate uncertainty. Its purpose is to make decisions more explicit, assumptions clearer, and execution more disciplined. By consistently applying the same process across analyses, screeners, thematic selections, and portfolio follow-up, the goal is to improve how investment decisions are approached, discussed, and evaluated over time.

Going forward, Quality Stocks will continue to focus on long-term investing rather than short-term signals or market noise. Whether you read the newsletter to learn, to explore ideas or to apply the framework more systematically, the objective remains the same: to provide structure, clarity, and consistency in a domain where those qualities matter most.

As always, thank you for reading, engaging, and contributing to the evolution of Quality Stocks.

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Yet while the short term appears static, the long-term picture is quietly shifting. The United States, by increasingly turning inward, is also creating distance with its allies, Europe foremost among them. Europe, in turn, is refocusing on itself, marked by rising military spending and a growing awareness that it is losing its competitive edge. Meanwhile, across the developed world, aging populations are placing mounting pressure on economic growth, public finances, and social systems and this trend is only just beginning. Finally, AI is rapidly diffusing across the economy, and even if monetization remains uncertain, its disruptive impact on most industries is imminent.

With this context in mind, what should we expect in 2026? Here is my vision.

1. AI will remain at the center of attention

In 2025, AI firmly established itself as the dominant theme across markets and industries. After the initial hype cycles of previous years, the focus shifted from experimentation to scale. Equity markets reflected this dynamic: performance was heavily concentrated in a small group of AI-exposed companies, reinforcing both enthusiasm and concerns about overconcentration.

At the same time, major technology players dramatically increased their investments. Hyperscalers, semiconductor leaders, and infrastructure providers committed tens of billions of dollars to data centers, advanced chips, and AI-specific hardware. While monetization remained uneven in 2025 (often lagging infrastructure spending) early signals began to emerge. Enterprise subscriptions, productivity gains, and vertical-specific applications (in software, healthcare, finance, and industrials) suggested that revenue models were starting to take shape, even if margins and scalability were still works in progress.

Looking ahead to 2026, constraints may become as important as innovation. The rapid expansion of AI workloads is putting growing pressure on energy supply, particularly electricity grids, cooling capacity, and long-term power contracts. At the same time, chip supply (especially advanced GPUs, memory, and specialized AI accelerators) remains tight. Despite aggressive capacity expansion, demand continues to outpace supply, raising the risk of shortages, delays, and higher costs. These bottlenecks could slow deployment in the short term, but they also reinforce AI’s strategic importance and the structural investment cycle that is likely to define the years ahead.

My take: AI will stay at the core of the investment landscape. Prioritize companies with clear paths to monetization or tangible improvements to their underlying business models, and remain vigilant against valuation growth that is not supported by EPS.

2. The healthcare sector’s comeback

In 2025, the healthcare sector significantly underperformed global equities. While the MSCI World Index delivered a strong return of around 19%, the MSCI World Healthcare index gained only about 1%. This gap reflects a broad loss of investor interest rather than a deterioration in fundamentals. Healthcare was crowded out by enthusiasm for AI, mega-cap technology, and cyclical themes, leaving many high-quality healthcare names lagging despite stable earnings and cash flows.

Several factors explain this weak performance. Political pressure played a central role, particularly from the Trump administration, which revived concerns around drug pricing, reimbursement, and regulatory scrutiny. These uncertainties weighed on sentiment across pharmaceuticals, biotech, and healthcare services. In addition, higher interest rates continued to pressure longer-duration assets such as biotech, while uneven innovation cycles and isolated clinical disappointments amplified investor caution. The result was broad multiple compression rather than a collapse in earnings.

Looking forward, the setup for healthcare is becoming increasingly attractive. Structural tailwinds remain intact, led by aging populations in developed economies and rising demand for chronic care, diagnostics, and advanced therapies. Valuations across many subsectors are now reasonable (or even compelling) relative to historical levels and the broader market. At the same time, AI has the potential to meaningfully improve productivity by accelerating drug discovery, optimizing clinical trials, and reducing operational costs across the value chain. After a year (or even years) of disappointment, healthcare may be positioning itself for a return to relevance as both a defensive and long-term growth sector.

My take: Healthcare is a defensive, long-term opportunity, but selectivity is key. Big pharma faces patent cliffs, while biotech carries elevated clinical risk.

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3. Revisiting stocks with overestimated AI disruption risk

In 2025, several sectors were heavily penalized by markets on fears of rapid AI-driven disruption. Investors extrapolated the capabilities of generative AI too aggressively, assuming swift substitution of human-intensive or data-driven business models. This led to sharp multiple compression in industries perceived as vulnerable, even though underlying demand, client behavior, and economics proved far more resilient than expected.

The call-center and customer experience outsourcing sector is a clear example. Companies such as Teleperformance and Concentrix were sold off on the assumption that AI would quickly replace large portions of their workforce. Complex customer interactions, regulatory constraints, multilingual support, and quality requirements continue to require human involvement. Over time, AI is more likely to enhance productivity and margins than destroy the business model outright, suggesting disruption fears were overstated.

A similar dynamic is visible in the data and information services industry, including companies like RELX, Wolters Kluwer, and FactSet Research. Concerns centered on AI models potentially commoditizing information and reducing the value of proprietary datasets. However, these businesses are deeply embedded in client workflows, combining curated data, analytics, compliance, and decision-support tools that generic AI systems cannot easily replicate. Rather than being displaced, these companies are integrating AI into their platforms to reinforce pricing power and customer stickiness. Comparable opportunities can also be found in IT services, business process outsourcing, and professional services (Accenture, Capgemini, TCS, etc), where AI is more likely to augment expertise than replace it and in the short-term will at least boost revenue. After a period of excessive pessimism, these sectors may offer attractive return potential as perceptions normalize and fundamentals reassert themselves.

This pattern reflects a broader truth about innovation adoption: we consistently overestimate the short-term impact of new technologies while underestimating their long-term effects.

My take: Select the stocks you believe in within this theme, but remain cautious of “falling knives”. From a portfolio construction perspective, aim for roughly 50% stalwart, high-quality stocks, 30% growth stocks, and less than 20% in higher-risk bets or recovery situations.

4. Powering the next cycle: energy and renewables

Energy is becoming (and always has been) a key strategic issue, driven in large part by the rapid growth in data-center electricity consumption. AI, cloud computing, and digital infrastructure are highly energy-intensive, and in many regions power availability is now a limiting factor for expansion. This has pushed energy supply, grid capacity, and pricing back to the center of economic and investment discussions.

After several difficult years, renewable energy could be positioned for a rebound. Higher interest rates, rising costs, and regulatory uncertainty have weighed heavily on the sector, compressing valuations despite intact long-term demand. A more supportive rate environment would improve project economics, while structurally rising electricity needs, especially from data centers, reinforce the strategic role of renewables as scalable, long-term energy solutions.

My take: Renewables offer an attractive long-term theme, but investors should remember that the sector is cyclical and highly sensitive to political and regulatory decisions

5. Maintain a strong focus on long-term structural trends

In 2025, several long-term structural growth sectors significantly underperformed, despite strong underlying fundamentals. Areas such as cybersecurity and software outside of AI were largely overlooked as investor attention concentrated on a narrow set of AI beneficiaries. This shift in focus led to valuation compression across many high-quality companies with recurring revenues, strong balance sheets, and durable competitive advantages, even though demand for digital security, enterprise software, and infrastructure continued to grow steadily. For example here are the 2025 performance of several names in the cybersecurity sector: Fortinet -15% / Palo Alto +3% / Qualys +2%.

For long-term investors, periods of underperformance can create opportunity. Rather than attempting to time market bottoms, a disciplined approach involves gradually increasing exposure when valuations become attractive. By building positions progressively, investors can reduce timing risk while accumulating stakes in high-quality companies that are likely to emerge as tomorrow’s leaders. Staying focused on structural trends, and patient through cycles, remains one of the most effective ways to compound returns over the long run.

Some key long-term themes include population aging, cybersecurity, digital payment, industrial automation, digitalization or water.

My take: Follow me for actionable stock ideas and thoughtful analysis, and apply them within your own long-term strategy

Final thoughts

2025 was a year dominated by volatility, concentration, and powerful narratives, often obscuring the deeper shifts reshaping the global economy. While short-term uncertainty remains high, long-term forces (AI adoption, demographics, energy constraints, and geopolitical realignment) continue to define the investment landscape.

Looking ahead to 2026, success will depend on selectivity, valuation discipline, and patience. Rather than chasing headlines, investors should focus on quality companies, structural trends, and opportunities created by temporary dislocations. Staying long-term oriented remains the most effective way to navigate uncertainty and compound returns over time.

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Developed by a 30-person team on a $10M budget, it surpassed 5 million sales by October and became Game Pass’s biggest third-party launch of the year.

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Turbulence in the gaming world

As I wrote almost a year ago, the video game industry is facing a period of intense structural stress. High-profile examples underscore a broader pattern: even legacy players with global IPs and deep pockets are struggling to adapt. Flagship titles, expected to carry commercial momentum, have instead underperformed, raising uncomfortable questions about the long-term viability of blockbuster-focused strategies.

The industry’s traditional growth model, built on escalating budgets, sequelization, and publisher-driven scaling, is showing signs of exhaustion. Studios are increasingly trapped in a cycle where creative spark is diluted by corporate oversight, tight deadlines, and rigid franchise formulas. As development costs soar into the hundreds of millions, each release becomes a make-or-break gamble, and when the stakes are that high, risk-taking (ironically the lifeblood of great games) tends to disappear.

Worse, the industry is now caught between rising expectations and diminishing returns. Gamers demand higher graphical fidelity, deeper narratives, and longer experiences, yet even as games become more expensive to produce, returns have not scaled proportionately. A $200M game that sells modestly is now a financial disaster. In response, publishers often cut corners, rush timelines, or lean into aggressive monetization tactics like battle passes and microtransactions, decisions that may please short-term investors but alienate players. This erosion of goodwill, paired with repeated layoffs, project cancellations, and a growing disconnect between studios and their fanbases, has created a toxic feedback loop.

Unlike other entertainment sectors, where established IPs can be reliably milked, video games demand a rare fusion of art, technology, and timing to succeed. That fusion is harder than ever to achieve, especially within the constraints of a legacy system built for a different era.

David vs Goliath

In contrast to the struggles of large studios, smaller, agile teams are increasingly demonstrating that creativity, passion, and flexibility can outperform massive budgets and corporate muscle. The clearest recent example is Clair Obscur: Expedition 33, developed by the 30-person French indie studio Sandfall Interactive. This success was not born from corporate mandates or franchise extensions but from a team deeply invested in its vision, unburdened by layers of approval and legacy constraints. They even stated that within a traditional studio structure, developing such a game would have taken two decades. Their openness about learning development through online tutorials, paired with a cohesive artistic direction, allowed them to create a game that not only stood out but moved millions of players worldwide.

This is not an isolated case. Baldur’s Gate 3, developed by the independent Belgian studio Larian, was named Game of the Year in 2023 and became a commercial and critical juggernaut. Larian’s approach emphasized player agency, narrative depth, and systemic gameplay, features often sacrificed in AAA production pipelines constrained by marketing teams and shareholder expectations.

Similarly, The Witcher 3: Wild Hunt, released in 2015 by Poland’s then-mid-sized CD Projekt Red, became a global phenomenon precisely because the studio poured genuine passion and cultural authenticity into its adaptation of Andrzej Sapkowski’s novels.

All 3 titles reflect a broader shift: when smaller studios are granted the freedom to focus on quality and originality rather than scalability and quarterly earnings, they are often better positioned to deliver the kind of groundbreaking experiences that resonate deeply with players, and win Game of the Year.

These examples, while not exhaustive, highlight a stark contrast with major industry players, who often acquire studios, overexploit franchises, and ultimately erode the very creative spark that made them valuable.

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The future of the video game industry

The ongoing wave of consolidation in the video game industry, led by tech giants like Microsoft, has created both opportunities and challenges. Microsoft alone has spent over $75B in recent years acquiring major publishers and studios, including Bethesda for $7.5B in 2020 and Activision Blizzard for a staggering $68.7B in 2023.

While these acquisitions offer scale, access to valuable IP, and greater control over distribution platforms like Game Pass, they also introduce significant complexity. Integrating diverse studio cultures, maintaining creative quality across sprawling teams, and managing development pipelines at scale is no small feat. In many cases, the result has been stagnation rather than innovation, with highly anticipated titles delayed or released in underwhelming states. As more creative output is centralized under a few corporate umbrellas, the risk of homogenization and slow value destruction rises, a concern that can’t be ignored given the industry’s reliance on fresh, resonant content.

To regain momentum and avoid long-term erosion of creative and financial value, large players must rethink their strategies. Instead of relying solely on scale, they should focus on cultivating internal “micro-studios” with independent creative authority, small, empowered teams that operate with the flexibility of indie developers but benefit from the parent company’s resources.

Investing in long-term talent retention, minimizing crunch culture, and incentivizing innovation over short-term delivery targets will be key. Additionally, platforms like Game Pass should be curated for quality over quantity to reinforce player trust and engagement. Finally, decentralizing risk, by supporting a diverse portfolio of experimental projects alongside blockbuster titles, can help large publishers rediscover the magic that originally fueled the industry’s growth. Success in gaming has never been just about size; it is about resonance, originality, and giving teams the space to create something extraordinary.

In this article, we will explore 3 sectors that have historically outperformed during market downturns and tend to show resilience in bear markets. These sectors can also serve as valuable diversification tools, potentially moderating long-term returns slightly, but reducing portfolio volatility and making it easier to stay invested over time.

Finally, we will highlight a selection of defensive stocks within these 3 sectors that could offer attractive opportunities in a more volatile environment.

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The 3 sectors

If you would like to learn more, you can read the article I published a year ago on understanding the different market cycles.

The 3 sectors that consistently perform well across the 2 most challenging phases of the market cycle (periods of slowdown and contraction) are:

• Healthcare. A defensive sector supported by steady demand regardless of economic conditions. Companies in this space often benefit from demographic trends and inelastic demand for medical products and services

• Utilities. Characterized by stable cash flows and regulated revenue models, utilities tend to hold up well when growth slows and investors seek predictable income through dividends

• Consumer Staples. This sector includes essential goods such as food, beverages, and household products. Because these items remain necessities, consumer staples companies typically maintain sales even during recessions

Some additional elements

As timing the market is notoriously difficult, investors shouldn’t focus solely on trying to do so. However, adopting a contrarian mindset can also be effective. In this light, rather than worrying about potential overvaluation in tech stocks, investors might consider directing their attention toward undervalued sectors.

The chart below illustrates that, as of Q4 2024, the healthcare sector appears significantly undervalued.

Furthermore, the healthcare sector has lagged meaningfully behind the overall market in recent performance.

Finally, it’s worth noting that the largest stocks now account for an exceptionally high share of the S&P 500 index, a concentration that becomes even more striking when compared with the “defensive” sectors.

To be clear, I am not suggesting that these sectors will return to their previous share of the total market, structural changes in the economy make that unlikely. However, their short to medium-term performance could prove resilient, especially in periods of market stress.

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Diversification over full portfolio rotation

In the current market environment, it can be tempting for investors to consider a full rotation. However, such an approach often proves counterproductive. Momentum and earnings leadership in these growth sectors remain strong, and abandoning them completely could mean missing potential upside if market optimism persists longer than expected. Timing these shifts precisely is notoriously difficult, and history shows that investors who attempt to do so often underperform those who maintain balanced exposure.

Instead of pursuing an all-or-nothing rotation, I believe the focus should be on diversification. Adding exposure to traditionally defensive sectors (such as healthcare, consumer staples or utilities) can enhance portfolio resilience without sacrificing participation in growth trends. These sectors tend to exhibit more stable earnings and lower volatility, offering a cushion during periods of market stress or when leadership rotates away from high-valuation segments.

Ultimately, a well-diversified portfolio acknowledges both sides of the market cycle: the potential for continued strength in leading sectors, and the need for stability if conditions shift. By blending growth and defensive exposures rather than overreacting to short-term risks, investors can position themselves to capture opportunities while mitigating drawdowns, achieving steadier performance across changing market regimes.

9 stocks worth watching

To explore some new opportunities, I have highlighted 10 stocks that I believe are worth watching. These are not part of my current portfolio, so they represent fresh ideas to consider.

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Those of you who have followed me for years know I am neither a fearmonger nor a blind permabull. I have always tried to take a balanced, data-driven view of the market. And right now, I am not telling you to sell everything, far from it.

What I am saying is that the risk–reward ratio for tech stocks does not look attractive at the moment. Let’s dig into why that is.

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Expensive markets

The market can stay irrational for much longer than most investors expect. But when valuations become stretched, the risk of a correction rises significantly.

In these environments, tech and other growth stocks tend to struggle, as their lofty expectations collide with tighter financial conditions and profit pressures.

The chart clearly shows that the market is expensive, trading more than one standard deviation above its historical average, just as it did in 2000 and 2021 (most of you probably know what happened there).

Most valuation metrics are now above their long-term means, and it is evident that tech stocks are driving much of this overextension.

A small ecosystem

When you take a closer look, it is clear that a handful of mega-corporations are carrying the entire market. Their relationships are often deeply intertwined, creating a fragile ecosystem.

For now, much of the investment activity is funded either by the free cash flow of these giants or by readily available capital, driven by the belief that future growth will be extraordinary.

But what if it is not? The entire structure could crumble like a sandcastle. And “slowing down” does not necessarily mean going from 100% growth to 0%, even a shift from 100% to 80% growth could send shockwaves through valuations.

Do not get me wrong: I still believe AI is a genuine game changer in the medium term. But even transformative technologies can’t escape market cycles and investor euphoria.

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An example: Oracle

Let’s run a quick calculation.

Oracle’s expected EPS for its 2026 fiscal year is $4.90. Using a simple DCF model with a 10% discount rate, the current market price implies roughly 28% EPS growth per year over the next decade.

Now, let’s assume that half of this growth is driven by the massive order from OpenAI (which should be roughly right). But what if OpenAI’s expansion reaches only 70% of current expectations, which would still be a phenomenal outcome? In that case, Oracle’s yearly EPS growth would likely fall closer to 24% instead of 28% - it doesn’t look like much at first glance.

A DCF based on 24% growth yields a fair value of around $221, roughly 25% below today’s market price.

In other words, even a slight adjustment in growth expectations could justify a significant correction in valuation. This is why I believe the risk–reward balance no longer justifies adding to tech positions.

Conclusion

The bottom line is simple: tech stocks have rarely looked this expensive, and much of the optimism baked into current prices assumes near-perfect growth for years to come. That does not mean the story is over, far from it. Innovation, especially in AI, will continue to reshape industries and create long-term winners.

But even great companies can be bad investments at the wrong price. Right now, valuations leave little margin for error, and expectations have outpaced reality.

This is not a call to sell everything, it is a call for discipline and patience. Markets tend to punish excess enthusiasm, and the best opportunities often emerge after the crowd cools off.

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I believe one metric will play a decisive role in signaling AI’s fate. Let’s explore it together.

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The impact of AI

We see thousands of studies explaining the impact of AI on jobs, markets, businesses, individuals, etc. Goldman Sachs estimated that more than 300 million jobs worldwide could be lost to AI. 300 million!

Other analysts estimate than by 2040 50% of the jobs could be affected, destroyed or transformed by AI.

In a recent study, Microsoft outlined the jobs most likely to be impacted by AI.

An impact already visible?

A recent study highlighted the impact of AI on certain roles, many of which had already appeared on Microsoft’s list.

This naturally raises the question: are we witnessing AI actively displacing these jobs, or are we simply observing the effects of a normal market cycle?

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The proof

The clearest proof that AI is delivering on its promise should appear first in the industries most impacted. In the short term (before potential new competitors flood in) the pure players should see one unmistakable signal: a margin increase.

That is the real value proposition of AI. Productivity gains and cost efficiencies should be so significant that companies can fund their AI spend with just a fraction of the savings generated.

If businesses begin to see sustained improvements in productivity and margins, AI investments will accelerate. In that case, the bullish projections for OpenAI, Amazon, Microsoft, Alphabet, Oracle, Nvidia, and others will be validated. If not, the skeptics calling AI a bubble may be proven right.

Time will tell which narrative wins out. My bet: AI gains are real, so keep an eye on margins as the ultimate signal!

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In this article, we will explore the main reasons behind this collapse and examine the possible scenarios for what lies ahead.

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A concentrated market

The Cognac market is highly concentrated, dominated by 4 major houses.

Hennessy leads by a wide margin, holding nearly 50% of global market share. It is owned by LVMH, and even provides the “H” in the group’s acronym.

The other 3 players operate at similar volumes: Martell (owned by Pernod Ricard), Remy Martin (owned by Remy Cointreau), and Courvoisier, the only independent house among the 4.

The rise…

In the 20th century, cognac developed a powerful and unexpected cultural connection in the United States, particularly among African-American consumers. After World War II, Black American soldiers stationed in France were introduced to cognac and brought an appreciation for the spirit back home. Over time, this taste became embedded in African-American culture, especially as cognac brands began to recognize and actively market to this loyal and influential demographic.

By the 1990s and early 2000s, cognac was deeply intertwined with hip-hop culture, with artists like Tupac, Busta Rhymes, and Jay-Z frequently referencing Hennessy and Courvoisier in their lyrics.

More recently, cognac has ridden the wave of global premiumization, finding explosive growth in markets like China and across Asia, where Western luxury goods are potent status symbols. High-end cognac has become a staple in both corporate gifting and nightlife, helping brands like Hennessy and Rémy Martin expand their global footprint.

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… and the fall

While cognac remains a globally respected luxury spirit, it has faced a significant decline in recent years, driven by a mix of economic pressures, shifting consumer preferences, and geopolitical tensions. One of the most immediate causes of this downturn has been the sharp drop in demand from China and the US, the 2 cognac’s largest export markets. In China, anti-corruption measures and a cooling economy have reduced corporate gifting and luxury consumption. Meanwhile, in the US, consumer tastes are shifting toward other spirits like premium tequila, bourbon, and Japanese whisky, which are perceived as more versatile or trend-forward, especially among younger drinkers.

Cognac also suffers from an aging brand image and limited relevance in modern cocktail culture. While its heritage and complexity are undeniable, cognac is often viewed as a sipping spirit reserved for special occasions or older demographics. This has made it less adaptable to the growing demand for mixable, sessionable drinks in casual settings. Additionally, rising production costs and global inflation have put pressure on pricing, making high-end cognac even more expensive at a time when affordability is top of mind for many consumers.

Another critical factor amplifying cognac’s decline is the inventory overhang across distribution channels, which has had a disproportionately strong impact on producers. This destocking cycle has led to a dramatic short-term drop in shipments from manufacturers, creating a lagging effect where actual sales to end consumers may not seem as dire as the plummeting figures reported by cognac producers.

And now?

Looking ahead, 2 scenarios could define cognac’s future. The first is a slow, partial recovery, where demand gradually stabilizes as excess inventory clears and macroeconomic pressures ease. But in this view, cognac’s boom years are behind it. The shift in consumer tastes (toward more casual, mixable, and affordable spirits) has left cognac somewhat out of step with the times. Even if volumes recover modestly, it may remain a niche luxury product with limited relevance among younger drinkers.

The second, more optimistic scenario envisions a stronger rebound, driven by brand reinvention and global recognition. Cognac’s deep heritage and cultural cachet still carry weight, especially in emerging markets and travel retail. But the path to growth will depend on evolving with the market, not just waiting for the past to return. In this scenario, potential growth would translate to a 3% to 6% compound annual growth rate (based on different analysts) over the next decade modest and steady, but far from explosive.

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Potential for investors

Rémy Cointreau is now trading at the same level as it was in 2011, effectively erasing 14 years of market gains. A local bottom appears to have formed in April 2025 around 40€, and the stock has since rebounded by roughly 20%. From a technical standpoint, the current zone is intriguing, but any meaningful upside will depend on which recovery scenario plays out.

If the slower recovery (scenario 1) materializes, the upside appears limited. The stock already trades at a price-to-earnings ratio above 25x, inflated by collapsing margins, which leaves little room for multiple expansion. However, if the stronger rebound (scenario 2) takes hold, driven by a return to growth and margin recovery, the stock could potentially climb back toward 90€, its first major resistance level.

Pernod Ricard faces a similar market setup, though with key differences. The company is more diversified than Rémy Cointreau and has successfully preserved its margins, keeping its PE ratio below 15x, a much more reasonable valuation. However, it is not immune to the broader downturn. Pernod is contending with a widespread decline in global demand for alcoholic beverages (as I described in this article), which weighs on its growth outlook. Technically, the chart shows a similar setup.

Conclusion

Cognac's dramatic fall has exposed the fragility of even the most iconic luxury products when faced with structural shifts in consumer behavior and global demand. What was once a booming symbol of cultural relevance and premiumization has now entered a period of deep uncertainty. The industry is at a crossroads: either evolve to meet the tastes and habits of a new generation, or risk becoming a relic of its past success.

For investors, the market offers both risk and opportunity. Valuations reflect much of the pessimism already, but the path forward remains unclear. Whether this downturn marks a cyclical low or a more permanent contraction will determine the returns from here. It may look like a speculative bet, but for investors who have long considered entering these names, current valuations and technical levels are aligning for a potential first entry point. That said, cautious investors are likely to stay on the sidelines.

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Yet, beneath the surface, there are signs suggesting that a market rotation might come. Let’s see why!

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2 important articles

I have already written two articles on this topic. In the first one, I highlighted that markets are currently discounting very little potential risk, with optimism running high. Positive developments (such as a possible resolution to the war in Ukraine) could certainly trigger short-term rallies. However, the overall risk/reward profile remains unattractive in my view, and I expect a period of consolidation could follow.

It is important to note that I approach this as a fear seller: I remain invested at all times. The purpose of this analysis is not to time the market, but to help identify moments when it may be more advantageous to deploy capital, at least within the framework of my investment strategy.

In the second article, I explored a different form of market rotation, the potential resurgence of small-cap stocks after years of underperformance.

The potential return of defensive sectors

Defensive sectors have largely underperformed in recent periods. For example, big pharmaceutical companies have struggled to generate meaningful returns, and alcoholic beverage stocks have also lagged.

This trend is clearly reflected in the data: as the chart shows, the weight of healthcare stocks in the S&P 500 has fallen to its lowest level in 25 years.

I won’t dwell too much on theory, but sector rotations often act as powerful market catalysts. While I would not recommend going “all in,” exploring selective opportunities through stock picking could prove worthwhile.

Some examples

Please note that the following are only examples, I am not invested in any of these stocks. Technical analysis can provide clues about market sentiment, but it does not guarantee that these names will prove to be good investments.

Many stocks are currently showing signs of potential reversal patterns. But is it a genuine turnaround, or just a dead-cat bounce? For now, the answer remains uncertain, and we will need to wait for confirmation.

Merck&Co - MRK

Sanofi - SAN.PA

Remy Cointreau - RCO.PA

Pfizer - PFE

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Conclusion

Tech continues to drive markets higher, but how long this leadership rarely will last? Early signs suggest that a rotation, toward small-caps or defensive sector, could be taking shape.

While uncertainty remains and not every reversal will endure, sector shifts often create powerful opportunities. My approach stays the same: remain invested, avoid chasing, and look for the right moments to deploy capital when the risk/reward profile improves.

But 2025 finds the market at a potential turning point. With monetary policy normalizing, inflation settling (at least expected to settle), and historically low valuations, the small-cap universe could be poised to regain performance. Valuations in many corners of the small-cap market now reflect years of skepticism, offering an intriguing setup for patient investors.

Is this the start of a small-cap renaissance? In this article, we explore the factors that could set the stage for a decade of small-cap outperformance.

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Signs of a new cycle

These 2 charts provide strong historical context for the thesis that small caps may be due for a comeback, but they also highlight why timing and patience are critical.

The first chart shows clear cycles of relative performance between small caps and large caps, with multi-year stretches of outperformance alternating with long periods of underperformance. Notably, the recent 14-year stretch of large-cap dominance (2011–2024) mirrors past large-cap cycles in both duration and slope. Historically, such long stretches have tended to reverse, often leading to a decade or more of small-cap outperformance. This cyclical behavior supports the idea that markets may now be primed for another shift back toward small caps.

The second chart (the 10-year rolling return spread) further illustrates this cyclicality, showing how small-cap leadership tends to swing in long arcs. What stands out is the depth and persistence of the negative spread over the last decade, one of the longest and most pronounced periods of large-cap dominance since the 1980s. If history is any guide, these extremes have often been followed by strong reversals.

Of course, these patterns are not guarantees, anything can happen. It is important to stay cautious and view them as indicators of increasing probability, not certainty.

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Fundamental drivers of potential outperformance

Several factors suggest that small-cap stocks could be poised for a period of outperformance, not just as a rebound from recent weakness, but as a structural opportunity. While past cycles do not guarantee future results, the following dynamics create a compelling case for renewed investor interest in small caps:

• Faster growth potential. Small-cap companies, by nature, tend to have greater room for expansion than mature large-cap firms. They often operate in niche markets, emerging industries, or are early in their growth cycle. In a world where economic growth is expected to normalize rather than accelerate, companies with internal growth drivers may attract renewed investor focus

• More attractive valuations. After a prolonged period of underperformance, small-caps now trade at historically low valuation multiples relative to large caps. PEs in many small-cap indices reflect years of investor skepticism. Historically, investing at times of low relative valuations has delivered superior long-term returns

• Rising M&A activity. Periods of small-cap underperformance often precede waves of mergers and acquisitions. Larger companies and private equity funds look for undervalued, high-potential targets and the current valuation gap makes small caps an attractive hunting ground. An uptick in M&A can provide direct upside for investors holding takeover candidates (as for Cantaloupe or Altium in my small-cap portfolio!)

• Potential shift in market flows. Over the past decade, passive flows and mega-cap concentration have fueled large-cap dominance. However, signs of rotation toward active management, equal-weight strategies, and style diversification could redirect flows into smaller names. As investor preferences evolve, small-cap stocks may capture a larger share of capital, providing a secondary catalyst for performance

Of course, there are other potential factors (value versus growth dynamic, inflation and interest rates, deglobalization, or infrastructure investments) but I find these arguments less compelling and harder to translate into a strong investment thesis.

Conclusion

As you know, my small-cap portfolio has delivered strong returns: over 50% in just 18 months. This performance reflects a disciplined and selective stock-picking process, prudent risk management, and, importantly, the renewed flow of capital and investor interest into small caps. If we are indeed at the start of a new cycle, this outperformance could have room to run.

If you are curious, feel free to take a look at my small-cap portfolio!

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The rollercoaster ride since April

April 2025 was marked by significant volatility. The S&P 500 experienced a sharp decline of over 20%, driven by escalating trade tensions and geopolitical conflicts. However, a 90-day pause on new tariffs announced in early April acted as a catalyst for recovery. By the end of the quarter, the S&P 500 had not only recouped its losses but also reached new all-time highs . This rebound underscores the market's capacity to recover swiftly from shocks, albeit raising questions about the sustainability of such gains.

Interestingly, the market's ascent has been propelled, in part, by widespread skepticism. Many investors remained cautious, anticipating further declines. This pervasive disbelief led to underinvestment, creating a scenario where positive news triggered rapid buying as investors rushed to catch up. Such dynamics highlight how contrarian sentiment can sometimes drive markets higher, as sidelined capital re-enters the market in response to unexpected resilience.

An article to go further on this topic

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Navigating through global turbulence

Despite the market's upward trajectory, several underlying issues pose significant risks:

• Geopolitical conflicts. The recent Israel-Iran conflict has heightened tensions in the Middle East, leading to concerns over oil supply disruptions and increased volatility in energy markets

• Trade wars. The expiration of the 90-day tariff truce looms, with potential new tariffs threatening to disrupt global trade and supply chains

• Economic indicators. Signs of a slowing labor market in the US, coupled with inflationary pressures from tariffs, raise concerns about economic growth and consumer spending

• Debt overhangs. Public debt levels in the US, France, and Japan are reaching historic highs. In the US, contentious debates over fiscal deficits and government shutdown threats continue to undermine confidence. In Europe and Japan, mounting debt amid weak growth could constrain policy responses in future downturns

• Taiwan and East Asia tensions. Rising military activity and nationalist rhetoric around Taiwan present a flashpoint for global markets. A sharp escalation involving China could trigger a significant market correction, particularly in tech-heavy sectors with supply chains dependent on Taiwan

• Valuation risks. As equity markets surge, valuations in several sectors appear stretched. Without corresponding earnings growth, markets may be vulnerable to corrections triggered by even modest negative surprises

These factors contribute to an environment of uncertainty, where markets must balance optimism with caution. Naturally, risk is an inherent part of investing, and as you know, I don’t subscribe to panic, nor to blind optimism. The key is to remain grounded, recognizing potential threats without losing sight of long-term opportunities.

As markets reach elevated levels, the question arises: what will sustain this momentum? Without new positive catalysts, such as robust corporate earnings, favorable economic data, or geopolitical de-escalation, markets may struggle to maintain their current trajectory. The risk of consolidation or correction becomes more pronounced in the absence of supportive developments.

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Seasonal patterns: the August-September effect

Historically, August and September have been challenging months for equities, often marked by increased volatility and lower returns. This seasonal trend, combined with the current global uncertainties, suggests that investors should prepare for potential turbulence in the coming months.

Conclusion

While the market's resilience is noteworthy, it is essential to approach the current environment with a balanced perspective. Remaining invested allows participation in potential gains, but vigilance is crucial given the array of risks on the horizon. Diversification, regular portfolio reviews, and a focus on long-term objectives can help navigate the complexities of today's financial landscape.

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