Last week : new ATH for SP500 ; Oil much higher, Gold lower ; US yields higher led by stronger than expected US CPI/PPI
WEEKLY TRENDS
New All Time High (ATH) for the S&P500 led by semi-conductors and AI infrastructure related Tech stocks (MS new target at 8300). April US PPI and CPI were released last week much stronger than expected at +6% and +3.8% respectively, pushing US yields much higher by 25bps (UST30 broke the psychological 4.5% mark). Steepening of the US curve increased by 5bps last week at +52bps.
The USD strengthened (+1.5%) on the back of the inflation data and Gold came lower (-3.5%). Meanwhile Oil surged by +10% (WTI at $105 after non-conclusive China-US talks). BTC is back below the $80k mark. All eyes shall be placed on Nvidia’s Q1 earnings release on Wednesday together with Walmart, and Home Depot a day earlier.
Last week’s Q1 earnings releases led to a rollercoaster weekly performance (Cisco +22%, Sodexo +11%, Adecco -19%, Tower semi and Technoprobe both at +30%). M&A related news created large movements in a few stocks too (Tate & Lyle in the UK with an impressive offer from US Ingredion at a +64% premium, and OHB in Germany from a strategic alliance with Dassault Aviation).
Macro Data releases : US last FOMC minutes (20 May)
WHAT ANALYSTS SAY
BlackRock : Record US stocks, disconnect or not?
Goldman Sachs : Investing in the architecture of AI’s future
NS Partners : Should the memories of 2000 give us cause for concern?
BlackRock Institute, 11 May 2026
Authors : Jean Boivin, Head of BR Institute—Wei Li, Global Chief Investment Strategist
· We see no disconnect between record U.S. equities and high oil and yields: Markets are pricing both AI-driven growth and the Middle East supply shock.
· U.S. equities hit record highs last week, while oil and yields stayed elevated — reinforcing our view that markets are differentiating the shock’s impact.
· U.S. inflation data this week will test still-firm price pressures, with implications for yields as markets assess the risk of further rate increases.
The resilience in U.S. equities reflects the scale and breadth of the AI buildout. Expected S&P 500 earnings growth for the first quarter has climbed to about 28%, roughly double early-April levels, while MSCI EM tech earnings growth expectations have surged to around 160%. This strength is being reinforced by an emerging AI-driven cybersecurity arms race, sustaining demand for compute, cloud infrastructure and advanced models. The numbers are staggering. The “magnificent seven” are tracking a 57% jump in quarterly earnings (with Nvidia yet to report), three times higher than Bloomberg estimates just last month. Capital spending is now estimated to reach as much as $725bn this year, up some 10% from before earnings. The AI buildout has so far outweighed the typical effect of a macro shock: a drag on growth and earnings that hurts equities.
That leaves interest rates as the key mechanism through which the shock could challenge risk assets. Higher energy and input costs are adding to already sticky inflation, with a more pronounced impact in Europe because of its greater exposure. At the same time, the AI buildout is increasing demand for capital — not only for technology infrastructure, but also for energy security and broader infrastructure rebuilding amid geopolitical fragmentation. Capital that previously flowed to the U.S. is increasingly being diverted to these needs, raising competition for funding and adding to upward pressure on long-term yields. Equity markets are balancing growth against rates: Strong enough earnings growth can offset higher yields, as seen in the AI-driven surge since the launch of ChatGPT. The risk: If disruptions persist, the combined effect of higher inflation and rising capital demand could push yields high enough to weigh on valuations. We stay pro-risk for now, overweighting U.S. and EM equities as beneficiaries of the AI buildout and commodity exports.
We prefer equities over bonds and remain underweight long-term U.S. Treasuries, instead favoring short- and medium-term bonds for income. This stance is dependent on eventual normalization in the Strait of Hormuz even as there are still no signs of a reopening. A prolonged closure would likely shift the balance. It would lift inflation and rates enough to start weighing on valuations and tighten financial conditions, ultimately challenging both risk assets and the pace of the AI buildout Bottom line: We see no disconnect between record U.S. equities prices and elevated oil, commodities and yields. Markets are pricing both AI-driven growth and the impact of the Middle East supply shock. We stay pro-risk as a result.
Europe lagged and more energy-sensitive sectors came under pressure as higher input costs began to bite, while oil prices and bond yields remained elevated. This divergence highlights how markets are absorbing the shock: Equity performance is supported by resilient growth and AIdriven earnings, even as commodities and rates reflect the risk of a more prolonged disruption to global supply chains.
Goldman Sachs Asset Management, 13 May 2026
Author : Leonard Seevers, Head of digital investments
· Agentic AI energy surge and infrastructure obsolescence
Current digital infrastructure is unlikely to sustain "Agentic AI" (AI 2.0), in our view. These autonomous, always-on systems are roughly 60-130x more energy-intensive than AI chatbots, necessitating a total rebuild of the physical architecture beyond just data centers.
· Critical physical bottlenecks
The expansion of AI is currently limited by severe "chokepoints" in the broader ecosystem. These include strained data center capacity, a projected power shortfall in the US, a massive shortage of skilled grid workers, limited land for large-scale projects, and extended supply chain wait times for high-voltage components and steel. Addressing these requires a diverse array of companies and solutions.
· Value shift
While 90% of AI profit pools are currently captured by chips, memory and manufacturing, we believe the investment opportunity is shifting downstream. Future growth depends on "pick and shovel" companies providing solutions across data centers, power transmission, advanced cooling, grid-connected generation, and the skilled workers to resolve the physical constraints.
Capitalizing on the Agentic opportunity set
While the market has been fixated on data centers and chips, the visible peaks of AI innovation, we believe the bottlenecks will dictate the pace and scale of the expansion of the entire AI ecosystem. This oversight is starkly reflected in the current value attribution: the combined EBIT of chips, manufacturing, memory, and servers is nearly nine times that of power, components, and data center service companies. We believe this imbalance suggests a mispricing of the essential infrastructure that underpins the entire AI ecosystem, which signals a significant investment opportunity for digital infrastructure investors. Consider the extended supply chain wait-times for critical components like substations and high-voltage cables—these are not just logistical hurdles, but fundamental constraints that directly impact the speed and cost of Agentic AI infrastructure deployment, representing potential value for those who can address them. We believe seasoned investors with expertise in complex transactions (e.g., taking a public company private), developing differentiated financing solutions, and strong global sourcing capabilities to secure proprietary deal flow, are especially well placed to succeed in this new era. Once invested, we believe, rapid and strategic deployment of operating resources will be required to help drive efficient and successful value creation over time.
The advancement of Agentic AI is contingent upon successfully addressing several critical structural impediments that the market has yet to appreciate. This transition to autonomous, always-on systems creates unprecedented demand across the physical infrastructure stack, including power generation and grid infrastructure, advanced cooling, connectivity, high-voltage components, and mission critical infrastructure services. Ultimately, we believe these physical constraints have transformed the AI race into a competition for infrastructure readiness, shifting the investment opportunity from the models themselves to the nascent enablers of the broader ecosystem.
NS Partners, 12 May 2026
Authors : Pierre Mouton, Long Only Head of Investment
The end of 1999 and the start of 2000 were marked by an impressive wave of IPOs, takeovers and spin-offs, all taking place against a backdrop of widespread euphoria. We know how that story ended. Certain parallels raise questions. 2026 could well be the year of IPOs with unprecedented valuations: some sources suggest 1.5 trn or more for SpaceX, 850bn for OpenAI and possibly 600bn for ByteDance. Unprecedented, by a long shot! Even more surprising is that the long-faded stars of the year 2000, such as Cisco and Intel, have this year returned to historic highs, more than 25 years after the bursting of the dot-com bubble.
The dot-com bubble ticked all the boxes of speculative madness: untenable valuations, a relentless stream of IPOs from companies whose business models had, in some cases, yet to be invented, wildly fanciful revenue and profit forecasts, and a culpable complacency on the part of much of the analyst community.
If we look today at market dynamics and IPOs, the situation is very different. Even if certain stock market performances and projected valuations for IPOs may raise questions, as might the sheer scale of investment programmes in artificial intelligence, the current enthusiasm centres primarily on companies that are already profitable, generating substantial revenues and sustaining steady growth. This is probably the first fundamental difference from the year 2000. At the time, the dot-com bubble was fairly self-contained and had little ‘trickle-down’ effect on the wider economy.
The investment cycle we are experiencing today is more cross-sectoral. We estimate that nearly 60% of the capital expenditure deployed by hyperscalers benefits the ‘old economy’: construction, cabling, ventilation, generators. Another significant difference concerns financing. A large proportion of investment relied on massive debt in 2000. The balance between debt and cash flows is much better today. Added to this is a key factor: the spread between the cost of capital and the return on that capital remains very favourable to hyperscalers in 2026, which was not at all the case during the internet bubble. The famous ROIC – WACC (Return on Invested Capital minus Weighted Average Cost of Capital), which was largely negative at the time, remains comfortably positive today.
The scale of current capital expenditure programmes is significantly weighing on the balance sheets of major technology leaders and calling into question their long-sought status as ‘asset-light businesses’, which normally exerts downward pressure on stock market multiples. Furthermore, the future return on investment from these programmes remains unknown at this stage.
Finally, amongst other uncertainties, the future pricing of artificial intelligence applications is impossible to determine on the one hand, and could come under pressure from intense competition on the other.
In conclusion, we must not overlook the tremendous upward momentum that the development of artificial intelligence provides for the stock markets. But enthusiasm does not replace discernment, and one should invest by paying particular attention to the soundness of business models, the quality of balance sheets and valuations, whilst never forgetting a basic rule: diversification.
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