China blocks SoftBank’s $5.4bn takeover of ABB’s robotics division

China has told SoftBank it will not allow the $5.4bn acquisition of ABB’s robotics division to go ahead in a shock move that threatens to throw Masayoshi Son’s ambitions in physical AI into disarray. (…)

China is the biggest market for ABB’s robotics unit, with more than 90 per cent of its robots for Chinese customers manufactured locally. The Swiss-Swedish company employs about 12,700 people in China. (…)

The ABB division’s operations in China were a significant attraction for the deal, say people close to the Japanese group.

The NDRC review had included detailed scrutiny of ABB’s Chinese supply chains and a demand to retain some of the robotics unit’s manufacturing capabilities in China, according to people familiar with the matter.

The deal cleared China’s competition review in February. It then became subject to a foreign investment security review that highlighted Beijing’s concern over the transfer of assets developed in China to a Japanese company at a time of heightened tensions with Tokyo and strategic competition with Washington.

The NDRC had been concerned about robotics data being transferred overseas, where it could be used to train AI models, including those developed by OpenAI, in which SoftBank is a major investor, said people familiar with the matter.

ABB set up a joint venture with a Chinese partner in 1992 and its China operations, particularly its robotics business, have long benefited from government support. Shanghai’s government also helped ABB build its $150mn robotics mega-factory in Pudong, which began operating in 2022.

According to people briefed on their thinking, regulators had also examined keeping intellectual property relating to some of ABB’s robotics business in China, potentially requiring parts of the business to be spun off to Chinese owners for the deal to proceed.

Very significant, well beyond the impact on Softbank.

Physical AI is where AI interacts with the real world through robots, autonomous machines, vehicles and industrial equipment. Digital AI creates and processes intelligence; physical AI uses that intelligence to perform work in the real world.

Physical AI could become a market worth hundreds of $billions annually. McKinsey estimates that general-purpose robotics alone could generate a $370bn market by 2040 in its base scenario.

With ABB, SoftBank was attempting to position itself for the transition from AI that thinks to AI that acts. That transition could be one of the defining investment themes of the next 10–20 years.

That gets right into (against) China’s strategy.

China’s rejection is effectively asserting control over industrial/robotics AI data.

Industrial robots generate valuable information about:

• How objects are manipulated.

• How machines move and interact with their surroundings.

• How manufacturing processes operate.

• How robots respond to unexpected situations.

• How physical tasks can be performed more efficiently.

The data generated by millions of industrial operations could become a strategic AI resource.

China is applying a national-security bend to that data, rather than treating it simply as the commercial property of a multinational company.

This has potentially profound implications for international AI development.

It suggests that access to industrial data could become as strategically sensitive as access to advanced semiconductors.

China understands the implications of a Japanese company, already a major investor in American OpenAI, acquiring a European company with substantial advanced robotics operations/knowledge/data in China.

A clear no-no for Beijing.

The wider message:

Multinational companies are discovering that owning a business globally does not mean they can freely transfer control of all its assets, intellectual property and data across national borders.

This could make future cross-border acquisitions in robotics, AI, semiconductors, autonomous vehicles and advanced manufacturing considerably more complicated.

The blocking of Meta’s acquisition of AI company Manus earlier in 2026 seemed relatively minor but it was the first indication that China is serious about AI leadership and corporate data.

It thus looks like Physical AI will also be split into 2 ecosystems.

Physical AI requires integration of several things:

• Advanced AI models.

• Computing power.

• Sensors and machine vision.

• Robotics hardware.

• Industrial manufacturing expertise.

• Real-world operational data.

Control over any one of these can create strategic advantages. China considers that the entire combination as strategically important.

The risk is that companies will find it increasingly difficult to develop globally integrated AI and robotics businesses.

The AI industry is moving from a competition over who builds the most capable models to a much broader competition over who controls the computing, data, machines and industrial ecosystems that make those models useful.

Our research trip to China last December included robotics.

From Bots On The Ground:

(…) On the battlefield for technological supremacy, robotics is now on the front line and China’s efforts are centered in Shanghai.

So far, robotics was essentially supplying fixed industrial robots. China already totally dominates this field.

The battle is now getting more serious: this is the “bots on the ground” era.

The Shanghai Humanoid Robot Kylin Training Ground, covering approximately 5,000 square meters (54,000 sq ft) in the Zhangjiang area of Shanghai, is China’s first national-level, public facility designed to mass-train humanoid robots from different companies in a shared environment. (…)

China clearly displayed its robotics objectives by inserting the word “kylin” above. “Kylin” is a standard brand name for homegrown Chinese “core technologies” intended to replace foreign dependencies.

The facility’s core purpose is to accelerate the entire Chinese robotics industry by centralizing data collection and standardizing how robots learn complex tasks.

It is a “heterogeneous” facility, meaning it trains robots from competing manufacturers (like AgiBot, Fourier, and Unitree) side-by-side rather than serving just one company.​

It aims to collect 10 million high-quality physical data entries (robot movements, interactions) to build a shared “brain” for the industry.​ (…)

The facility also acts as a standard-setter. Just as cars need to pass crash tests, robots here must pass proficiency exams in these standardized environments to prove they are ready for factory work. (…)

The “US model” relies on private enterprise, venture capital, and a university system that fosters fundamental research and innovation.

The “China Model” offers several strategic advantages over the decentralized US approach.

Its primary superiority lies in treating AI training data as a public utility rather than a private asset, which theoretically allows the entire industry to advance faster than any single company could on its own.

In the US, valuable training data is trapped in “walled gardens.” Tesla does not share its Optimus data with Boston Dynamics, and Figure AI does not share with Agility Robotics. This means every US company must solve the same basic problems (e.g., how to open a door, how to walk on gravel) from scratch.

The Kylin center aggregates data from 100+ (1000+ in 2027) different robots into a single, massive dataset targeting 10 million entries.​ This creates a shared “industry brain.”

A startup’s robot can theoretically learn from the mistakes made by a competitor’s robot yesterday, accelerating the baseline intelligence for everyone. (…)

The US market typically waits for a clear winner to emerge before setting standards (e.g., waiting for Tesla’s NACS charging port to become the standard). This can lead to years of fragmentation where parts and software aren’t compatible.

The Kylin center acts as a central certification authority from day one. By forcing all robots to pass the same “exams” in the same physical facility, it enforces early standardization.​ This ensures that supply chains (batteries, joints, sensors) can be standardized faster, lowering component costs for the whole industry.

The Kylin center is “heterogeneous,” meaning it trains robots with different body shapes and mechanical structures side-by-side.​ This diversity is rare. Most US labs only contain one type of robot. Training AI on diverse hardware makes the algorithms more robust.

The China model (centralized infrastructure) and the US model (market competition) generate completely different economic benefits. While the US model maximizes corporate value and radical innovation, the Chinese model is designed to maximize manufacturing scale and supply chain dominance. (…)

US labs have text data; Chinese labs have physical data. This will create a new “data wall” that the US cannot easily climb because it lacks the manufacturing environments to deploy these robots at scale. (…)

Per the International Federation of Robotics:

China totally dominates the Industrial Robots field …

… and has boosted the share of its domestic suppliers from 32% to 55%, creating a huge domestic, efficient ecosystem.

As of September 2026, IFR has identified 174 humanoid robot manufacturers globally. More than 50% are in China, a proportion rising rapidly as a wave of new company creation coincides with breakthroughs in Gen AI.

But all is not lost for the US. Watch this Apple video: Perceptive Humanoid Motion from Simulation.

Here’s what the authors wrote (BTW, 5 Chinese and 3 Europeans):

Humanoid robots have the potential to automate a wide range of physical tasks.

Progress toward generalist humanoid autonomy, however, remains constrained by a data bottleneck: mapping pixels and free-form language to low-level joint commands requires paired supervision, and no corpus of such data exists at sufficiently large scale.

Some approaches rely on human teleoperation and wearable capture devices, which require at least an hour of human time to produce an hour of data.

We present HALO, a humanoid autonomy system powered by a pipeline that synthesizes vision-language-motion data across a thousand procedurally generated homes. The corpus scales with compute rather than human labor.

HALO acquires a repertoire of physical skills, including sitting on chairs, navigating to named objects, stepping sideways through half-open doors, crouching and crawling beneath tables, and pushing boxes. It orchestrates these skills to solve composite, long-horizon tasks.

Without ever seeing a real home during training, HALO transfers zero-shot to the physical world, achieving a 91% success rate across 360 trials in six unmapped real-world environments.

US software teams (including Apple with HALO) often must run their models on Chinese platforms like the Unitree Robotics G1 because equivalent domestic hardware is either scarce or cost-prohibitive.

The US seeks to overcome the data collection bottleneck using systems like Apple’s HALO, Nvidia Cosmos, and Google DeepMind Genie to generate hundreds of thousands of synthetic hours of photorealistic motion and perception across randomized 3D environments.

While simulation excels at visual navigation and high-level trajectory planning, physics engines struggle to accurately model complex micro-frictions, soft-body deformations, and tactile grasping. Analyses from robotics practitioners at Field Motion AI emphasize that contact-rich manipulation (such as tool use or precise mechanical assembly) still heavily relies on real-world demonstration data

Analysts from the Carnegie Endowment for International Peace note that Chinese state initiatives and factory deployments generate massive feedback loops. Deploying thousands of robots directly onto manufacturing floors yields corner-case physical failure data that synthetic models cannot anticipate.

And the US must convert whatever algorithmic lead it may get into commercial dominance, requiring overcoming reliance on foreign hardware manufacturing.

Trump: New Iran attacks “quite unlikely”

President Trump said Monday that a renewed military campaign against Iran is “quite unlikely” and “doesn’t seem to be necessary.”

Trump stopped short of saying the war was over, but his comments on Truth Social and at an impromptu press conference were the furthest he went in that direction since February.

The president in recent days has been weighing three options: launch new strikes, continue to strangle Iran’s regime economically, or cut a deal that includes significant concessions to the Iranians.

• Trump signaled on Monday that he’s going with the strangle strategy for now. That means keeping up the “status quo” — continuing the naval blockade, in addition to a new operation dubbed “Iron Gate” to cut off land routes that Iran uses to move advanced weaponry and other technology.
• Trump said the war is “effectively over” militarily. But he added that he doesn’t want to formally announce that before he makes sure U.S. allies in the region are safe.

Trump made his comments hours after meeting with Qatari Prime Minister Sheikh Mohammed bin Abdul Rahman Al Thani about the negotiations with Iran.

• “Qatar, Saudi Arabia, UAE, Bahrain, Kuwait, and others, would prefer the status quo” to resuming the war, Trump said.
• The Qatari prime minister also met separately with Vice President Vance, who’s been leading the Iran talks for the administration in recent weeks. Al Thani wrote on X that he discussed with Trump ways “to progress the U.S.-Iran talks.”
• A diplomat briefed on the details of the meeting said Trump made clear to Al Thani that he wants a deal and will give negotiations a chance. But he also noted that if Iranians don’t take negotiations seriously, he could reverse course, the diplomat said.

“Should there be any change with respect to developments in the Middle East, the United States of America is locked and loaded and ready to go. At this point, however, that seems to be quite unlikely,” Trump wrote on Truth Social.

• “We are seeing positive momentum toward an end to this Conflict, and will ensure that America’s interests are at all times protected. At the conclusion of this Military Engagement, the American People, and the World, will be far safer and more secure,” he added.

Trump said that Iran is “talking very politely” with the U.S. and noted that there is a “good chance that could get ended,” seemingly referring to the military conflict.

“Hope we are gonna be able to make a deal with them,” he added.

Iran’s Supreme National Security Council secretary, Mohsen Rezaei, wrote on X shortly after Trump made his comments that the war “has wrecked the U.S. government.”

He called Trump comments about negotiations with Iran “imaginary” and called on the U.S. “to SURRENDER” to Iran’s conditions for ending the war.

In effect, the GCCs told Trump to stop hurting them.

BOOMFLATION CONFIRMED

On September 4, after the release of the August Services PMI, I suggested that the US economy seemed to be shifting gears.

The August CPI released on September 14 accelerated from mild June-July core and services inflation.

I boldly titled my September 24 post “Boomflation!” following the September Flash PMI:

“The Services PMI has thus jumped from 54.6 in July to 56.5 in August and now to 58.7 in September with strong new orders. The September Manufacturing PMI’s 3.1 points jump to 57.0 with accelerating new orders confirms that business is clearly booming now in both manufacturing and services”.

Add “the most severe supply chain bottlenecks seen in the near-two-decade survey history” and the ingredients are there for sustained inflation in coming months.

Supply shortages with little prospects for quick improvements provide strong pricing power, everything feeding on itself.

The October Flash PMI confirmed:

• US economic growth is broadening and accelerating to “booming conditions”.
• Employment growth is also accelerating, “at the fastest rate since June 2022”.
• Corporate costs are also surging due to “material shortages, low stock levels, overloaded suppliers, labour shortages, rising back orders and shipping or import delays”.
• Strong demand allows businesses to broadly boost selling prices.

I wrote: “The strengthening labor demand is particularly significant since wage inflation is the only missing ingredient in current subdued inflation scenarios.”

The October employment report provided that missing ingredient, showing +165k new jobs and having revised the August-September total from +162k to +246k. In effect, the US economy created nearly as many jobs (411k) in 3 months than during the previous 7 months (450k).

Unsurprisingly, wage inflation has now entered the picture.

Between March and July, wages rose 2.4% annualized on average. August to October: +3.9%, October +4.5%.      

The wage component of the Employment Cost Index was a low 3.1% in Q3. Job switchers are now getting a 4.7% wage bump, up from 3.5% in May.

CPI-Core Services inflation was a low 3.1% in Q3.

The price pipeline is filling up as Ed Yardeni illustrates:

PPI-Final Demand is up 6.4% YoY but PPI-Processed Goods is up 14.2% and Unprocessed Goods +21.7%.

Ten-year Treasury yields have retreated from their October 6 peak of 5.33% to 4.86%. Investors dismissed the employment report, focusing on the new narrative of slowing data center expansion and a more subdued wealth effect to curb any excess demand.

The 5-year breakeven inflation rate remains well within the FOMC target, however elusive it has been since 2024. This is a strong bet on Warsh delivering or, perhaps more simply, on an hopeful decline in oil prices.

Question is: how many rate hikes will be needed?

This week we get the CPI (Tuesday), the PPI (Friday) and 10 Fed officials scheduled to speak.

San Fran Fed Mary Daly told CNBC on Friday that “the job market remains stable and solid, but not booming.”

For her info, from the recent PMI surveys:

• Manufacturing is generating jobs at a pace not seen for five-and-a-half years. Backlogs of work increased for an 8th successive month, with the latest net increase the steepest since April’s near four-year peak.
• New services business inflows rose sharply. Demand was reported to be high. Jobs growth was solid. Companies were keen to expand employment to help support new business and as part of company expansion plans. Backlogs of work are rising steeply and to the greatest degree in four-and-a-half years.

JP Morgan economist wrote that he is seeing “a few hints” of ending wage disinflation but refuses to call it:

Certainly GDP growth was good in 3Q and business surveys look decent in October, which would be supportive of faster job gains. But the unemployment rate has hardly budged over the last few months and remains right in line with where it was from mid-2024 to mid-2025.

Business surveys don’t only look decent, they’re sweating booming conditions. And BTW, the unemployment rate is a lagging indicator, as most people know. BTW #2, the labor force is declining and so is the participation rate.

Feroli also noted that “aggregate earnings (the payroll proxy) are rising 6.2% saar over three months, equaling the fastest rise of the last few years.”

Americans have yet to show any inclination to restrain consumption:

• US Consumer Credit Surges by Most in Nearly Four Years

(…) Credit-card and other revolving debt outstanding climbed $16.3 billion, the most since November 2023. Non-revolving credit, which includes car and school loans, rose $11.5 billion — capping the fastest three months of such borrowing since 2022. (…)

The data suggest consumers are leaning on credit cards to keep spending as worker pay struggles to keep pace with inflation.

• DATA CENTER WATCH

Morgan Stanley confirms SemiAnalysis projections that planned compute supply will not be impacted much in 2027.

It’s more an issue for the 96 GW expected in 2028. Based on election results, 37.5 GW may be subject to a “pause” with another 15 GW subject to “conditions”. While pauses are the more impactful outcome, conditions can be onerous: requiring data centers to pay grid costs to protect ratepayers, ending tax incentives, imposing water limits, setting requirements for onsite backup power, mandating labor requirements and banning non-disclosure agreements during permitting (most of which seem sensible to me). If the data center buildout starts to slow at some point, upgrading to better NVIDIA chips might be the only way to generate more tokens.

While “conditions can be onerous”, they likely would not be critical in a world where hyperscalers see themselves in an existential race. According to infrastructure cost data mapped by Epoch AI, the chip stack and its associated networking infrastructure account for nearly 80% of a facility’s total cost.

• The governor-elect of Texas, Gina Hinojosa, has explicitly said that all currently permitted datacenters in Texas will be allowed to finish construction. This essentially covers all of the 2027 and likely well into 2028. “It is not that I hate data centers. I hate the way they are taking advantage of Texas, and that stops when I’m governor.”
• Ohio Governor-elect Dr. Amy Acton pledged to block any future data center projects unless they explicitly meet rigorous community, grid, and resource standards.
• Google Takes Over Wyoming Data Center That Crusoe Had Pitched The big players will grab whatever capacity is freed by smaller developers.
• Trump signed an executive order in July 2025 seeking to expedite the permitting of data centers on public land saying the facilities were a priority for the administration’s goals of manufacturing and technical dominance. A top Senate Democrat is putting the Trump administration’s moves to build data centers on public land in the crosshairs, foreshadowing a brewing fight when his party takes control of Congress next year. (Bloomberg)
• Alberta’s data centre policies will help lure projects, power producers say
• Ford government to approve AI data centres ‘sooner rather than later’ amid moratorium calls
• “A lot of people have been asking us today about data centers and maybe now what has happened post midterms in the US will mean less capacity for the US regions,” Shemara Wikramanayake said, speaking after Macquarie reported half-year earnings on Friday. “Australia has land, we have sunshine, we have energy, we have a lot of capacity to build cable connections to the US West Coast.”
• Google to Spend $15 Billion in Malaysia Data Center Expansion Malaysia has emerged as SE Asia’s main data center hub, attracting companies from Oracle Corp. and Amazon.com Inc. to Alibaba Group Holding Ltd. and ByteDance Ltd.
• Nvidia’s answer to data center backlash: retrofitting Apollo’s old phone buildings. Telecom buildings were originally engineered to support heavy, power-hungry analog switching gear, meaning they already have substantial, highly stable power connections. The proposal pitched by Nvidia involves converting 130+ Brightspeed properties spread across roughly 20 U.S. states. Nvidia estimates that retrofitting these specific buildings could collectively unlock 1 gigawatt (GW) of power capacity. Verizon and others own thousands of these buildings. Verizon has already begun its own trials converting them into edge data centers.

In truth, not all US compute demand can be imported. Foreign data centers cannot replace the US domestic footprint for certain critical functions:

• Inference and Network Latency: Interactive AI consumer prompts, gaming, financial high-frequency trading, and real-time enterprise tools require round-trip latency under 20–50 milliseconds. Placing server stacks thousands of miles away introduces physical fiber transit delays that degrade user experience. Edge and inferencing clusters must still reside close to US population centers.
• Data Sovereignty and Compliance: US federal, defence, and heavily regulated healthcare/finance records are subject to strict data-locality rules (such as ITAR, HIPAA, FedRAMP, and DOD clearance frameworks). Foreign facilities generally cannot store or process these workloads under US law.

But foreign facilities can be used for workloads that are not sensitive to millisecond-level network delays:

• AI Foundation Model Training: Training frontier neural networks is asynchronous and takes months of continuous, isolated number-crunching. It does not matter whether an algorithm trains on cluster nodes in Sturgeon County, Alberta, or Ashburn, Virginia, provided the facility has reliable multi-gigawatt power and high-speed inter-chip networking.
• Batch Analytics and Back-Office Processing: Data archiving, nightly risk modelling, batch rendering, and large non-urgent data pipelines can run across international borders with minimal operational friction.

Necessity is always the mother of inventions. AI data centers are no exception as technology is evolving rapidly, helping reduce footprint through increased efficiency and better resource management.

Betting on entrepreneurial motivation and innovation carry better odds than betting on regulations stifling AI growth.

2026: The State of Enterprise AI  Companies Are Spending 5x More on AI Now

Hot off the press (Nov. 3, 2026)

Mainstream coverage of enterprise AI has fixated on companies capping what employees can spend, like Apple cutting engineers’ daily limits. The data says the opposite: Menlo’s fourth State of Enterprise AI report, built on a mid-September Morning Consult survey of around 400 US enterprise decision-makers responsible for about $4 billion in AI spend, shows adoption is not only growing but accelerating off a bigger base. The story of 2026 is agents, and the shift from paying for seats to paying for tokens. (The AI Daily Brief)

• Enterprise AI deployment spend scaled to $177B by September 2026, up from $33B last year. Growth is accelerating: 5.4x vs. 3.9x a year ago. Every dollar that went into developing models this year is generating $1.70 of revenue.

• Agents changed the math: OpenRouter agent traffic is up 37x since overtaking human traffic in February, tying spend to work performed rather than users.

• For now, money follows capability: Frontier labs command 69% of deployment dollars (vs. 50% last year). Anthropic’s share of enterprise API spend increased from 40% to 55%, OpenAI’s from 27% to 31%, while Google’s fell from 21% to 9%. Open-source remains 4% of spend despite 19% of usage.

• AI spend concentrates where agents work best: Coding ($34.0B) and chatbots ($25.0B) make up 76% of the $77.3B app market because they offer environments in which agents can act, workflows they can learn, and results they can verify.

• AI-natives are winning new agent categories like coding, which is 96% AI-native. Compared to last year, incumbents are gaining share in IT (91%), data science (88%), and HR (68%).

• AI is expanding the software economy: 55% of AI dollars is from net new spend, rather than existing software or labor budgets.

• In the race to win AI builders, Anthropic and OpenAI now account for 86% of enterprise LLM API spend, up from 67% last year. As the market consolidates around the frontier leaders, model capability—not price—is proving to be the decisive competitive advantage.

Chinese Producer Inflation Hits 5.7% for Post-Covid Era High

Prices at the factory gate climbed 5.7% in October from a year earlier, after a gain of 5% in September, according to data released by the National Bureau of Statistics on Monday. (…)

Nine industries — led by upstream sectors such as coal mining, oil and gas extraction and fuel processing — contributed to over 6 percentage points to the overall increase in producer inflation, NBS statistician Dong Lijuan said in a separate statement. (…)

At the same time, the surge in producer inflation masks a deep divergence within China’s industry, with only half of the 30 key sectors tracked by the NBS recording price gains while the rest all saw declines.

By contrast, the consumer-price index slipped more than forecast to 0.7% in October, versus 0.9% in prior month. The core CPI, which strips out volatile food and energy prices, slid to 0.8%, matching this year’s low. (…)

While higher gasoline prices provided a lift to CPI, other categories including consumer goods, gold jewelry and services all saw moderating price gains, according to Dong. A steeper decline in the cost of fresh vegetables, pork and fruit resulted in a 0.54 percentage point drag on consumer inflation.

Non-food: +1.5% YoY in October. Fuel costs rose by +20.2% YoY in October (vs. +14.9% in September), transportation services price inflation increased by 5.3% in October (vs. 4.5% in September), and telecom equipment price inflation rose to 16.1% in October (vs. 14.3% in September). (GS)

This ING chart suggests China is getting out of its deflation problem.

EARNINGS WATCH

From LSEG IBES:

435 companies in the S&P 500 Index have reported earnings for Q3 2026. Of these companies, 83.2% reported earnings above analyst expectations and 13.8% reported earnings below analyst expectations. In a typical quarter (since 1994), 67% of companies beat estimates and 20% miss estimates. Over the past four quarters, 82% of companies beat the estimates and 15% missed estimates.

In aggregate, companies are reporting earnings that are 5.4% above estimates, which compares to a long-term (since 1994) average surprise factor of 4.4% and the average surprise factor over the prior four quarters of 7.7%.

Of these companies, 73.2% reported revenue above analyst expectations and 26.8% reported revenue below analyst expectations. In a typical quarter (since 2002), 63% of companies beat estimates and 37% miss estimates. Over the past four quarters, 77% of companies beat the estimates and 23% missed estimates.

In aggregate, companies are reporting revenues that are 2.5% above estimates, which compares to a long-term (since 2002) average surprise factor of 1.3% and the average surprise factor over the prior four quarters of 2.5%.

The estimated earnings growth rate for the S&P 500 for 26Q3 is 33.4%. If the energy sector is excluded, the growth rate declines to 28.1%.

The estimated revenue growth rate for the S&P 500 for 26Q3 is 14.4%. If the energy sector is excluded, the growth rate declines to 12.7%.

The estimated earnings growth rate for the S&P 500 for 26Q4 is 29.5%. If the energy sector is excluded, the growth rate declines to 24.5%.

The strong economy brings strong earnings. The last 2 weeks were particularly solid and analysts are scrambling to revise upwards:

• Inflation Fears Return as Corporate America Counts the Cost

Mentions of inflation on S&P 500 earnings calls have reached the highest level in more than two years, underscoring growing concerns over skyrocketing costs and weakening consumer confidence.

From paint makers to spice manufacturers, company bosses have been evaluating the impact of rising prices, coming up with ways to alleviate the pressure and reassure investors worried about the impact on margins. (…)

S&P 500 Valuation Dives As Earnings Soar

(…) Forward earnings rose to a record $418.25 [IBES is at $405.71]. It is converging on the 2027 estimate of $426.28, which continues to climb. (…)

The S&P 500 forward P/E fell to 17.6 last week, below the 2025 Liberation Day low. P/E plunges typically accompany corrections and recessions. (…)

Since the bull market began on October 12, 2022, the S&P 500 has risen 106.2%. Forward earnings is up 75.5%, while the forward P/E is up 22.5%.

The P/E and E both drove the rally until the forward P/E peaked in October last year. Since then, E has done all the work. Investors are finding it harder to predict the return on all the AI capital spending. They won’t pay an excessive multiple given that uncertainty. (…)

The S&P 500 Semiconductors industry accounts for much of the P/E drop. The industry index’s forward P/E has plunged to 13.1, well below the S&P 500’s. Semis are now cheaper than they were during the 2022 bear market.

Good odds …

Source:  @RyanDetrick

… though not starting well …

Data: FactSet; Chart: Matt Phillips/Axios

… no dry powder …

… and more selling than buying:

• AI Has Taken Over Every Corner of the Market

(…) A Bloomberg analysis of thousands of corporate and regulatory filings and credit deals shows markets and economies around the world are now more dependent on tech than ever before. And much of that dependence rests on AI. Any downturn in the AI industry, either in the buildout of its infrastructure or the valuations of its stocks, will reverberate far beyond Silicon Valley.

(…) About 44% of pension holders’ equity investments hinge on tech, based on a Bloomberg review of more than 70 pension funds.

Pension funds aren’t the only ones piling in. Bloomberg’s analysis shows tech has emerged as the largest share of equity investments for hedge funds and insurance companies as well. (…)

Tech firms have borrowed $296 billion in investment-grade debt this year through Oct. 12, turning them into the largest borrowers of any industry outside of finance, a Bloomberg analysis of corporate bond deals shows.

The six largest hyperscalers are expected to spend more than $850 billion this year to finance projects tied to AI, an 83% increase from 2025. And that figure may rise to as much as $9 trillion through 2031, Bloomberg Intelligence analyst Robert Schiffman estimated before the midterms.

This year alone, tech heavyweights have priced a record nine US high-grade bond sales of at least $25 billion — once a rare event reserved for massive acquisitions. That’s more than the entire market produced in the previous eight years combined.

Technology is now nearly the biggest source of junk-bond issuance. Its share of the market has almost tripled since last year to a record 19.7%, driven by data center financing. AI infrastructure developers including TeraWulf Inc. and Applied Digital Corp. alone have sold more than $43 billion of high-yield notes this year through Oct. 13, up from just $8.5 billion last year and zero before 2025. (…)

Investment in tech hardware, software and data centers now comprises more than a third of all US business investment — the most on record in data going back to 1947. In growth terms, that share is even starker: Those categories accounted for the vast majority of all US investment expansions over the past year and have now eclipsed the boost they provided at the height of the dot-com bubble, underscoring how much of the economy’s momentum is riding on the AI boom. (…)

US, Iran Edge Closer to Deal With Nuclear Issue Back in Play

The US and Iran are moving closer to a potential breakthrough in efforts to end the war, with Tehran showing a willingness to discuss issues related to its nuclear program that were previously off the table, according to a diplomat with knowledge of the talks.

Iran is studying proposals related to its atomic activities that were presented by chief mediator Qatar, according to the diplomat, who asked not to be identified discussing sensitive information. Any concession on that issue could lead to a significant step forward in negotiations, which have been stagnating since the collapse of an interim peace deal agreed in June. (…)

In other recent diplomatic moves, Iranian Foreign Minister Abbas Araghchi discussed “efforts aimed at establishing stability in the region” in separate phone calls with his Saudi and Qatari counterparts on Thursday, according to a statement on his official Telegram channel. He also spoke to his opposite numbers in the United Arab Emirates, Turkey, Kuwait, Cyprus and Jordan. (…)

Al Jazzera has much more:

(…) Speaking at the university event, Qatar’s Prime Minister and Minister of Foreign Affairs Sheikh Mohammed bin Abdulrahman bin Jassim Al Thani said that “for the past couple of weeks, we have worked with colleagues in the US administration who have very genuine intentions to find a way to contain the situation and de-escalate it”.

Mediation efforts continue “to prevent the situation from spiralling out of control”, he confirmed, adding that “thanks also to some wise voices in Tehran, we have prevented that from getting out of control”. (…)

On Thursday, Iran offered the US a new nuclear and peace proposal via Qatari mediators, to be discussed only after Washington meets Tehran’s seven demands, a senior Iranian official told Reuters. The US is examining the proposal, Reuters reported.

Iran has made meeting its seven demands a condition for reopening the Strait of Hormuz and restarting peace talks, including on its nuclear programme. The demands include the lifting of sanctions on Iran, the unfreezing of Iranian assets and the end to the US naval blockade of its ports in and around the Strait of Hormuz, among other things.

It has also stepped up ties with Russia, with its top security official, Mohsen Rezaei, travelling to Moscow for talks on Thursday. During that visit, Rezaei said: “On the issue of diplomacy, we have announced seven conditions ⁠to the Americans. As long as they do ⁠not execute our seven conditions, we will neither open the Strait of Hormuz nor have negotiations.”

Meanwhile, the US has insisted a deal on Iran’s nuclear capacity must be part of any ceasefire agreement before wider peace talks can restart. (…)

Iran continues to tightly control shipping lanes through the strait, where several ships have been damaged in recent days. It has granted exemptions to shipping restrictions to Iraq and Qatar, in the Gulf region, as well as to India and China. (…)

Iranian officials said Iran has the capacity to strike further than the Gulf using weapons manufactured in Iran.

On Thursday, a spokesman for the Supreme Advisor to the Commander of the Aerospace Force of the Islamic Revolutionary Guard Corps said: “In the event of a new aggression, any country or force that helps America attack Iran can be a legitimate target of the Islamic Republic.”

Iran’s state media outlet Tasnim News reported: “Our missile bases have a suitable range to target the Zionist regime and American bases,” adding “Iran’s response to the possible new aggression of the enemies will not be geographically limited.”

Iran has also previously warned that cables, data centres and artificial intelligence (AI) facilities across the Gulf region could be attacked if war with the US erupts again. (…)

Meanwhile, Iran’s Revolutionary Guard Corps navy says at least seven tankers have caught fire after sailing into mines while attempting to transit through the Strait of Hormuz using “unauthorised routes” near Oman this week. (…)

• Rubio Sees No Iran Breakthrough as Trump Downplays Strikes

US Secretary of State Marco Rubio played down the chances of a breakthrough in talks on ending the conflict with Iran, saying Tehran’s demands to date are unacceptable and in some cases “outrageous and ridiculous.”

Rubio’s comments to reporters contrasted with Donald Trump’s tone after CNN quoted the president earlier Sunday as saying it’s “highly unlikely” he’ll order more strikes on Iran if negotiations make substantial progress.

“You have a number of countries that continue to engage them with different ideas, but I wouldn’t say we’re on the verge of a breakthrough,” Rubio said in Florida before leaving to meet Group of Seven counterparts in Paris, where the Iran war will be on the agenda. (…)

• Iraq has reached understandings with US to allow oil exports through Hormuz, minister says

Iraq has reached ​understandings with the United ‌States to allow Iraqi oil exports through ​the Strait of ​Hormuz via a shipping lane ⁠near Oman, Foreign ​Minister Fuad Hussein said ​in an interview with Al Jazeera.

He said Iraq’s losses ​from the Iran ​war and disruptions to oil ‌exports ⁠had reached $60 billion.

Iraq’s oil exports recovered in October after a ​sharp drop ​the ⁠previous month. Exports rose to ​about 3.5 million ​barrels ⁠per day from 2.65 million bpd in ⁠September, ​according to Iraqi ​energy officials.

SO WHAT

Bruce Mehlman:

For months every indicator flashed “big blue wave.” If anything, they undersold it.

The next two years will be the most disruptive & unpredictable in modern memory. Business will be squeezed between a still-powerful Executive Branch it must work with and an electorally-emboldened Congress determined to find & expose corruption. Both parties face early, bruising and drawn-out presidential primaries pitting populists against more mainstream contenders.

And all this while AI transforms everything at accelerating speed and new forces reshape the world order in real time.

Buckle up.

Someone suggested to dismiss the notion of a lame duck president. Think mad dog.