US Stocks Surge 16% in Two Months: Only 4 Occurrences in History, the Most Recent Was Just Before the 1987 Crash

marsbitPubblicato 2026-06-03Pubblicato ultima volta 2026-06-03

Introduzione

U.S. stocks have surged 16% over April and May, a gain seen only four times since WWII, according to Deutsche Bank strategist Henry Allen. Three prior instances followed recessions, but the sole non-recession precedent was in early 1987, months before the "Black Monday" crash. The current rally is underpinned by AI enthusiasm and strong data, but its speed without an economic recovery is historically unprecedented. Meanwhile, credit spreads remain near record lows despite growing consumer strain—the U.S. savings rate hit just 2.6% in April, a level last seen before the Global Financial Crisis, and consumer sentiment is at its lowest since 1952. Market risks are concentrated. While stocks and credit markets appear immune to geopolitical tensions, sovereign bonds tell a different story. Treasury yields have tracked oil prices and recently hit multi-year highs, creating a widening divergence with equities. Surprisingly stable oil prices, despite the prolonged closure of the Strait of Hormuz, have been a key pillar for risk assets. However, if the blockage persists, this support could fade, raising the risk of a stagflation shock not currently priced in.

Original Author: Zhao Ying

Original Source: Wall Street News

The recent strong rally in U.S. stocks is triggering historical alarms. The S&P 500 index has accumulated a 16% gain from April to May, a magnitude of increase that has occurred only 4 times since World War II. Three of those instances happened during recovery phases following economic recessions. The sole precedent not in a post-recession context occurred just months before the "Black Monday" crash in 1987.

Deutsche Bank macro strategist Henry Allen points out that the current rally is not taking place against a backdrop of post-recession recovery, making the historical comparison particularly stark. Meanwhile, credit spreads remain at historically low levels, but pressure signals from the consumer side are accumulating, expectations for Federal Reserve interest rate hikes are heating up, and the divergence between sovereign bond markets and stock markets continues to widen.

With multiple risk factors converging, market tail risks are becoming exceptionally concentrated. Henry Allen wrote in the report, "The tail risks in the current distribution are exceptionally prominent, both at the geopolitical level and at the market level."

Historical Precedents Are Rare, Only One Non-Recession Example Exists

The S&P 500's two-month gain of 16% from April to May has only 4 precedents since WWII.

Three of them occurred during powerful rebounds following recessions: the post-COVID-19 recovery from April to May 2020, the post-global financial crisis rebound from March to April 2009, and the recovery rally following the first oil crisis from January to February 1975.

The 4th instance was from January to February 1987. That was just months before October's "Black Monday" — the day the S&P 500 plunged 20% in a single session.

Henry Allen emphasizes that the current rally has its fundamental support, including high enthusiasm for artificial intelligence and strong economic data, but "the pace of gains itself has broken all recent precedents." In an economy not emerging from a recession, a rebound of this speed has never ended well in history.

Furthermore, the S&P 500 is on track to achieve its fourth consecutive year of double-digit gains, a record not seen since the late 1990s.

Excessive Optimism in Credit Markets, Consumer Pressure Signals Overlooked

The strength in equities has also spread to credit markets. Credit spreads in both the US and Europe are currently narrower than before the US-Iran conflict erupted, showing the market's high tolerance for risk.

However, warning signals at the consumer level are accumulating. The US savings rate was just 2.6% in April, a similarly low level historically seen in only two other periods: a single month in 2022 (when pandemic-era excess savings were being depleted) and just before the global financial crisis erupted. Meanwhile, the University of Michigan Consumer Sentiment Index hit its all-time low in May since records began in 1952.

The monetary policy environment is also tightening. The European Central Bank is widely expected to raise interest rates this month, and market bets on Federal Reserve rate hikes in 2026 are heating up — with US PCE inflation reaching 3.8% year-on-year in April, providing support for this expectation.

Henry Allen notes that historically, hawkish stances from the Federal Reserve have often coincided with widening credit spreads, as seen in 2022, late 2018, and from 2015 to 2016. The current calm in credit markets forms a clear divergence from this historical pattern.

Bond Market Bearing Pressure Alone, Divergence with Stocks Continues to Widen

While equity and credit markets show high immunity to geopolitical risks, sovereign bond markets have charted a distinctly different course.

Over the past month, the yield on the 10-year US Treasury note has almost completely tracked oil price movements, clearly decoupling from other asset classes. In mid-May, sovereign bond yields hit multi-year highs: the 30-year US Treasury yield rose to 5.18%, the highest since 2007; the 10-year German bund yield climbed to 3.19%, the highest since 2011.

At that time, stocks were just a step away from record highs, while bond yields were already at levels not seen in over a decade. This divergence shows no signs of convergence to this day.

Henry Allen believes that bond markets more directly price in inflation and fiscal risks, hence reacting more sensitively to geopolitical shocks. The persistent divergence between stock and bond markets is itself a manifestation of current market fragility.

Unexpectedly Stable Oil Prices: A Key Pillar for Risk Assets

The blockade of the Strait of Hormuz has lasted far longer than initial market expectations, yet the reaction in oil prices has been surprisingly mild, which partly explains the resilience of risk assets.

When the US-Iran conflict erupted on February 28, the White House initially estimated the operation would last 4 to 6 weeks. However, the Strait of Hormuz remains blocked to this day. According to prediction market Polymarket data, the probability of normal navigation resuming by the end of June has plummeted from around 80% in mid-April to just 22%.

Despite this, the oil futures curve has remained relatively stable. Just two weeks after the conflict began, on March 13, the 6-month Brent crude futures contract settled at $85.66 per barrel. On June 1, the same contract was quoted around $84.88, barely moving.

Henry Allen points out that it is precisely because the oil futures curve has not shifted significantly higher that investors have not priced in serious stagflation risks, thereby avoiding larger-scale selling of risk assets. However, he warns that if the Strait of Hormuz blockade persists, whether this support can be maintained remains uncertain.

Domande pertinenti

QAccording to the article, how many times since WWII has the S&P 500 gained 16% in a two-month period, and what is the key characteristic of the only non-recessionary precedent?

AAccording to the article, the S&P 500 has gained 16% in a two-month period only 4 times since WWII. Three of these instances occurred during recoveries from recessions. The only non-recessionary precedent was in January-February 1987, which preceded the 'Black Monday' crash later that year.

QWhat consumer-related warning signs are mentioned in the article as potential risks being overlooked by the market?

AThe article mentions two key consumer-related warning signs: the U.S. savings rate was only 2.6% in April (a level historically only seen briefly in 2022 and before the global financial crisis), and the University of Michigan Consumer Sentiment Index hit its lowest recorded level since 1952 in May.

QWhat historical anomaly does the article point out regarding the current relationship between Federal Reserve policy expectations and credit spreads?

AThe article points out a historical anomaly where tightening Federal Reserve policy has typically coincided with widening credit spreads, as seen in 2022, late 2018, and 2015-2016. However, currently, despite rising expectations for Fed rate hikes, credit spreads remain at historically low levels, showing a clear divergence from this past pattern.

QHow has the sovereign bond market behaved differently from the stock and credit markets in response to recent geopolitical risks?

AWhile stock and credit markets have shown resilience, the sovereign bond market has been under significant pressure. Specifically, the 10-year U.S. Treasury yield has closely followed oil price movements, decoupling from other assets. Yields on long-term U.S. and German government bonds recently hit multi-year highs, indicating the bond market is more directly pricing in inflation and fiscal risks.

QWhy has the oil market's reaction to the prolonged closure of the Strait of Hormuz been described as a 'key pillar' for risk assets?

AThe oil market's reaction has been a 'key pillar' for risk assets because, despite the Strait of Hormuz closure lasting much longer than initially expected, oil futures prices have remained surprisingly stable. This lack of a sharp upward move in the oil futures curve has prevented investors from pricing in severe stagflation risks, thereby avoiding a larger sell-off in riskier assets like stocks.

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After Marvell's 32% Surge, the Chinese Chip Family Behind It Emerges

The stock price of Marvell Technology surged 32.5% on June 2nd, driven by NVIDIA CEO Jensen Huang highlighting its custom ASICs and optical interconnects as core to AI data center architecture. This event brought attention to the Chinese semiconductor family behind Marvell: the Dai siblings. The story centers on three siblings, all UC Berkeley graduates, whose three-decade entrepreneurial journey aligns with major semiconductor industry shifts. In 1995, youngest sister Dai Wei Li co-founded Marvell with her husband Sehat Sutardja and his brother, focusing on storage controllers. Eldest brother Dai Wei Min founded EDA company Ultima, later sold to Cadence, and later founded VeriSilicon (芯原) in China, becoming a leading semiconductor IP provider. Second brother Dai Wei Jin co-founded EDA firm Silicon Perspective (sold to Cadence) and GPU IP company Vivante, later acquired by VeriSilicon. The combined "Dai-Sutardja" family network extends beyond Marvell. Their ventures and investments form a comprehensive ecosystem for the post-Moore's Law, chiplet era. Key holdings include: Dream Big Semiconductor (AI SuperNICs, acquired by Arm), Alphawave (high-speed SerDes IP, acquired by Qualcomm), and Silicon Box (a chiplet advanced packaging foundry). VeriSilicon itself thrives on the AI ASIC and IP boom in China. Collectively, the family's AI infrastructure-related portfolio is estimated at over $22 billion. Their strategy represents a distinct path: building critical components for open standards and key manufacturing capacity in the chiplet era, rather than pursuing standalone AI chip dominance. While this path may not create the next NVIDIA, it has enabled repeated successful exits and sustained influence within the global semiconductor industry.

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Microsoft is Afraid of Being Marginalized by AI Giants

Microsoft, once the defining force of the PC era, now faces a familiar challenge in the AI age: the risk of being relegated to a profitable but invisible infrastructure provider. This anxiety was laid bare at Build 2026, where CEO Satya Nadella unveiled a major strategic pivot. The catalyst was a quiet April agreement that dissolved Microsoft's exclusive licensing and cloud-hosting deal with OpenAI, its once-vital partner. This erased Microsoft's key AI moat. With OpenAI and Anthropic defining AI applications and gaining enterprise traction—even within Microsoft's own ranks—Nadella had to answer: without exclusivity, what is Microsoft's role? The answer was a suite of seven in-house AI models, a developer-focused AI workstation (Surface RTX Spark Dev Box), and, most crucially, the Agent 365 platform for enterprise AI governance. The models, notably targeting Anthropic's strengths in coding and enterprise, signal a defensive move. However, the broader strategy is to make the models themselves less decisive. Financially, Microsoft's AI revenue is strong, driven largely by Azure running others' models. Yet its user-facing products like Copilot show weak penetration and engagement. Microsoft earns infrastructure money but lacks direct user mindshare. Nadella's core fear is being "hollowed out." As OpenAI and Anthropic prepare for IPOs and gain financial independence, they may build their own infrastructure, threatening Azure's lucrative AI revenue stream. Microsoft's window is to entrench itself deeper: not as the model creator, but as the indispensable platform for securely deploying, managing, and governing all AI models within the enterprise through Agent 365. Build 2026 revealed Microsoft's bet: in the AI era, the ultimate power lies not in any single model, but in the enterprise "operating system" that controls them. Nadella is determined to ensure Microsoft is the driver of this new era, not just a passenger.

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CPU, Quietly Returning to the Center of the AI Computing Power Stage

Over the past three years, AI computing power narratives have been dominated by GPUs. However, starting in 2026, this story began to shift. While training large models remains GPU-intensive, the rapid growth of inference and AI agent workloads, which require high levels of task orchestration, concurrency, and data flow management, has highlighted a renewed critical role for CPUs. These are tasks GPUs are not designed to handle. Intel's recent launch of the Xeon 6+ processor, built on its Intel 18A process and featuring up to 288 efficiency cores (E-cores), exemplifies this strategic pivot. It is positioned not as a mere companion to GPUs but as the essential "control plane" for AI infrastructure, optimized for high-density, energy-efficient, and high-throughput workloads characteristic of AI agents and inference. This "CPU resurgence" is not about CPUs outperforming GPUs in raw computation. It reflects a systemic bottleneck: as AI scales from training single models to deploying countless intelligent agents, the demand for coordination and data handling surges. Major cloud providers are also developing their own high-density ARM-based server CPUs for similar workloads. However, Intel's success with this strategy faces significant challenges. Competition includes NVIDIA's integrated CPU-GPU solutions, the expanding adoption of cloud vendors' in-house ARM CPUs, and the crucial market test of Intel's 18A manufacturing process against rivals like TSMC's N2. In conclusion, CPUs are indeed reclaiming a central, though redefined, role in AI compute—managing the complex orchestration that enables massive-scale AI deployment. While the trend is clear, which company will ultimately lead this CPU resurgence remains an open question to be decided in the data centers of 2027 and beyond.

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