TSMC’s 58% surge in first‑quarter profit is the clearest sign yet that the AI boom is no longer a cyclical uplift but a structural shift reshaping the entire semiconductor industry.
The Taiwanese chipmaker delivered record earnings, comfortably beating analyst expectations, as demand for advanced processors continued to outstrip supply.
Net income reportedly reached NT$572.48 billion, marking a fourth consecutive quarter of record profits, while revenue climbed to NT$1.134 trillion, driven overwhelmingly by high‑performance computing and AI‑related orders.
What stands out is the composition of that growth. Roughly three‑quarters of TSMC’s wafer revenue reportedly came from advanced nodes, with 3‑nanometre chips alone accounting for a quarter of shipments.
Nvidia
Nvidia has now overtaken Apple as TSMC’s largest customer, underscoring how AI accelerators have become the industry’s most valuable real estate.
TSMC’s executives described AI demand as “extremely robust”, with customers signalling multi‑year achievements rather than the usual stop‑start ordering cycle.
The company also moved to reassure investors over supply‑chain risks linked to the Middle East conflict, saying it has diversified sources for critical gases such as helium and hydrogen.
With capacity running hot and capital spending set to hit the top end of guidance, TSMC is positioning itself as the indispensable chipmaker in the AI era.
ASML’s decision to raise its 2026 guidance underlines a simple reality: demand for advanced AI chips is not easing, and the world’s most important semiconductor equipment maker remains at the centre of that surge.
The company signalled stronger-than-expected orders for its extreme ultraviolet (EUV) and next‑generation high‑NA systems, driven by chipmakers racing to expand capacity for AI accelerators, data‑centre processors and cutting‑edge logic nodes.
Bottleneck
The upgrade matters because ASML sits at the bottleneck of global chip production. Only a handful of firms can even buy its most advanced machines, and those firms – chiefly TSMC, Intel and Samsung – are all scaling up AI‑focused manufacturing.
Their capital expenditure plans have held firm despite broader economic uncertainty, suggesting that AI infrastructure is becoming a non‑discretionary investment rather than a cyclical one.
Two forces are driving the momentum. First, hyperscalers continue to pour billions into AI clusters, creating sustained demand for the most advanced lithography tools.
Long-term lock in
Second, geopolitical pressure to secure domestic chip capacity is pushing governments and manufacturers to lock in long‑term equipment orders.
ASML’s raised outlook reinforces the sense that the semiconductor cycle is diverging: consumer electronics remain patchy, but AI‑related manufacturing is entering a multi‑year expansion.
The key question now is whether supply can keep pace with the ambition of its customers.
There’s a growing sense that financial markets have drifted into a parallel reality. Not the usual detachment that comes with speculation, but something deeper — a structural break between what is happening in the world and what markets choose to see.
This is how the stock market feels at the moment. I might be wrong, but the overwhelming sense of despair feels so real. I believe the markets are broken at their core, and nobody seems to care. Markets make money and remain devoid of morality.
The system is morally bankrupt.
You can watch a crisis unfold in real time, with footage, statements, explosions and diplomatic failures, and yet the markets behave as though they’re responding to a completely different script.
A ceasefire that barely exists is treated as a turning point. A strategic waterway that is “open” only in the loosest, most cosmetic sense is priced as fully restored. The disconnect isn’t subtle. It’s brazen.
And yes — it feels deceptive
Not because traders are conspiring to mislead anyone, but because the modern market has evolved into something that no longer requires truth to function.
It only needs a narrative.
A headline. A phrase that can be interpreted as “less bad than yesterday”. That’s enough to ignite a rally, even if the underlying situation is deteriorating by the hour.
This wasn’t always the case. There was a time when markets, for all their volatility and irrationality, still behaved like instruments tethered to reality.
When a major shipping lane was threatened, prices moved accordingly. When a ceasefire collapsed, markets reflected the renewed danger. There was at least a rough correlation between events and valuations — imperfect, but recognisable.
Today, that correlation has snapped. The market trades on sentiment, not substance. On the idea of stability, not the presence of it.
Appearance
On the appearance of progress, even when the facts on the ground contradict every optimistic headline. A ceasefire announcement is enough to send equities higher, even if the ceasefire is violated before the ink dries.
A promise to reopen a strait is enough to calm oil prices, even if only a handful of ships actually move.
The deception is structural. It’s the product of algorithmic trading that reacts to keywords rather than conditions.
It’s the result of a decade of central bank intervention that has taught investors to treat every crisis as temporary and every dip as a buying opportunity. It’s reinforced by political communication that prioritises market stability over factual clarity.
The system rewards optimism, even when it’s unjustified. It punishes realism when it’s inconvenient.
Surreal
This is why the current moment feels so surreal. You can see the footage of strikes in Lebanon while reading headlines about “regional de‑escalation”. You can watch tankers stalled while analysts talk about “normalising flows”.
The market shrugs, because the narrative — however flimsy — is enough to sustain the illusion.
If markets don’t need truth, then they are, in effect, trading a deception. Not a deliberate deception, but a functional one.
Economic Truth
A deception that keeps prices elevated, volatility suppressed, and investors soothed.
A deception that allows the charts to climb even as the world beneath them fractures.
A deception that has become the operating principle of a system that no longer reflects reality, only the stories it finds convenient to believe.
This isn’t investing – this is pure manipulative gameplay and benefits only those who know how to play the game.
And ‘they’ set the rules.
Markets make the money but remain devoid of morality.
I feel like I am playing a video game without the controller or at least with a rule book.
Update:
U.S. announces it will blockade of the Strait of Hormuz, or rather Iranian ‘linked’ ships. And not in the Strait but further out in international waters. This is designed to reduce the risk of conflict.
Taiwan Semiconductor Manufacturing Company (TSMC) has delivered a striking 35% year‑on‑year jump in first‑quarter revenue, reaching a record NT$1.13 trillion.
The result underscores just how dramatically the centre of gravity in global technology has shifted towards advanced semiconductor manufacturing, with artificial intelligence now the defining force behind industry growth.
Relentless AI demand
TSMC’s performance is being powered by relentless demand for cutting‑edge chips from major clients such as Apple and Nvidia.
As AI infrastructure spending accelerates worldwide, the company has become one of the few manufacturers capable of producing the most sophisticated processors required for training and running large‑scale models.
March alone saw revenue climb more than 45%, highlighting the strength and urgency of this demand.
Ambition
Analysts suggest TSMC is on track to exceed its already ambitious 30% annual growth target, helped not only by volume but also by reported price increases for its most advanced nodes.
Even as smartphone and PC markets remain uneven, AI‑related orders are more than compensating.
With more companies—from hyperscalers to AI start‑ups—designing their own chips, TSMC’s strategic position looks increasingly unassailable.
Upcoming earnings and ASML’s results next week will offer further clues about the momentum behind the semiconductor sector’s AI‑driven boom.
For seasoned traders, geopolitical brinkmanship rarely arrives as a surprise. Over the past decade, markets have developed a reflexive understanding of how political theatre interacts with asset prices.
Nowhere is this more evident than in the so‑called TACO trade — shorthand on Wall Street for “Trump Always Chickens Out.”
Pattern
It is not a political judgement, but a market pattern: a repeated cycle in which aggressive rhetoric triggers short‑term volatility before ultimately giving way to de‑escalation.
The latest Iran crisis has revived this playbook. As President Trump reaffirmed his deadline for Iran to reopen the Strait of Hormuz and threatened strikes on power plants and bridges, global markets initially reacted in predictable fashion.
Oil prices swung sharply, Treasury yields dipped, and investors sought safety as the deadline approached.
Positioning
Headlines on various news outlets captured the tension: warnings of higher energy prices, unsettled European markets, and futures trading nervously ahead of each new statement.
Yet beneath the surface, traders were already positioning for the familiar TACO outcome. The pattern is simple: price in the threat early, then fade it.
Hedge funds bought oil and volatility on the initial sabre‑rattling, but quietly prepared to unwind those positions as soon as signs of negotiation emerged.
When reports surfaced that Iran had submitted a ceasefire proposal — dismissed publicly as “not good enough” but nonetheless signalling movement — markets began to relax.
Oil turned mixed, futures rose, and Treasury yields reversed higher as safe‑haven demand faded.
Behaviour
This behaviour reflects a deeper truth about modern markets: headline risk decays quickly when investors believe the political actor prefers brinkmanship to actual escalation.
Trump’s negotiating style, built on maximalist threats followed by last‑minute recalibration, has become sufficiently familiar that traders now model it. The TACO trade is simply the codification of that expectation.
What makes this episode notable is how efficiently markets anticipated the pivot. Even as rhetoric hardened, the S&P 500 futures market edged higher, suggesting investors were already discounting the likelihood of military action.
Analysts warned that markets might be “completely wrong” about the risk of war, yet price action told a different story: traders were betting on de‑escalation before it arrived.
Whether the TACO trade remains reliable is another question. Markets adapt, and geopolitical actors can surprise.
But in this latest Iran standoff, Wall Street’s instincts proved consistent: fade the fear, wait for the climb‑down, and trade the relief rally when it comes.
Is it “playing with the markets”?
From a trader’s perspective, what you’re seeing isn’t so much deliberate market manipulation as a predictable feedback loop between political communication and investor psychology.
Markets react to signals, not intentions
When a political leader issues threats, deadlines or ultimatums, markets price the risk of escalation. When those threats repeatedly end in de‑escalation, markets begin to price the pattern instead of the words.
That’s how the TACO trade emerged: investors noticed the pattern and traded accordingly.
The pattern becomes self‑reinforcing
If traders expect a climb‑down, they position for it. If enough traders position for it, the market moves in that direction. This makes the pattern appear even stronger.
It’s not “playing with the markets” in the sense of intentional manipulation — it’s more that political brinkmanship creates volatility, and markets learn to anticipate the likely outcome.
Markets hate uncertainty but love repetition
If a leader consistently escalates rhetorically but de‑escalates in practice, markets adapt. They stop reacting to the drama and start trading the expected resolution.
That’s what happened around the Iran ceasefire discussions:
Oil spiked on the threats
Traders anticipated a softening
Oil fell sharply when negotiations appeared
Equity futures rose as the risk premium evaporated
This is classic pattern‑recognition, not evidence of someone intentionally moving markets.
Why it feels like market‑playing
Because the cycle is dramatic:
Threat → volatility
Deadline → fear trades
Climb‑down → relief rally
To an outside observer, it can look like the political actor is pulling the market up and down. But from a market‑structure perspective, it’s simply headline‑driven trading meeting predictable political choreography.
The real issue is transparency, not intent
Markets can handle tough talk. What they struggle with is ambiguity — when the gap between rhetoric and action becomes wide enough that traders start pricing the gap rather than the policy.
That’s why the TACO trade exists: it’s a market response to inconsistency, not a claim of manipulation.
Is it a form of manipulation or planned market reaction.
Meta has unveiled Muse Spark, its first major artificial intelligence model since the company overhauled its AI strategy in response to the underwhelming reception of its previous Llama 4 models.
Developed by the newly formed Meta Superintelligence Labs under the leadership of Alexandr Wang, Muse Spark represents a deliberate shift towards smaller, faster, and more capable systems designed to compete directly with Google, OpenAI, and Anthropic.
Foundation
Muse Spark is positioned as the foundation of a new family of models internally known as Avocado. Meta reportedly describes it as “small and fast by design”, yet able to reason through complex questions in science, maths, and health — a notable claim given the company’s recent struggles to keep pace with rivals.
Early evaluations suggest the model performs competitively in language and visual understanding, though it still trails in coding and abstract reasoning.
Crucially, Muse Spark is deeply integrated into Meta’s ecosystem. It already powers the Meta AI app and website and will soon replace Llama across WhatsApp, Instagram, Facebook, Messenger, and Meta’s smart glasses.
Integrated
This rollout signals Meta’s intention to embed AI more tightly into everyday user interactions, from search and recommendations to multimodal tasks such as analysing photos or comparing products.
The company is also experimenting with new revenue streams by offering a private API preview to select partners — a departure from its previous open‑source approach.
Whether this shift will alienate developers who embraced the openness of Llama remains to be seen.
Meta frames Muse Spark as an early step toward “personal superintelligence”, an assistant that can understand the world alongside the user rather than waiting for typed instructions.
It’s an ambitious vision — and one that will be tested as the model expands globally and faces scrutiny over privacy, safety, and real‑world performance.
SpaceX is edging towards what could become the most significant stock market debut in modern history, with expectations that its initial public offering may surpass a valuation of $1 trillion.
A confidential filing with U.S. regulators marks a pivotal moment for the company, signalling its readiness to transition from a privately held aerospace leader to one of the world’s most valuable publicly traded firms.
Record breaking valuation
The anticipated valuation reflects SpaceX’s dominance in commercial spaceflight, satellite deployment and global broadband through its rapidly expanding Starlink network.
Its reusable rocket technology has already reshaped launch economics, and the company’s growing influence across defence, communications and space infrastructure has strengthened investor confidence.
Analysts suggest the timing of the IPO is driven by the escalating cost of SpaceX’s long‑term ambitions, including deep‑space exploration and large‑scale satellite expansion.
Company integration
The recent integration of Elon Musk’s AI venture, xAI, into SpaceX has further broadened the company’s technological footprint, reinforcing expectations that substantial new capital will be required to sustain its momentum.
If market appetite matches current projections, SpaceX’s listing could set a new benchmark for tech‑driven valuations — and potentially position Musk as the first individual to see their net worth approach the trillion‑dollar threshold.
Oracle is swinging hard at its own workforce as the company races to reposition itself as an AI‑infrastructure contender.
Thousands of roles are being eliminated, a drastic move that reflects the sheer financial pressure of trying to keep up with hyperscale rivals in the most capital‑intensive tech shift in decades.
The company’s share price has slumped 25% this year, with investors increasingly uneasy about soaring data‑centre spending and the heavy debt required to fund it.
Oracle has already raised $50 billion to bankroll new GPU‑ready facilities, but unlike Amazon or Microsoft, it lacks the cushion of vast cloud scale.
The result: a balance sheet under strain and a leadership team forced into tough decisions.
Future
Oracle’s remaining performance obligations have ballooned to more than half a trillion dollars, fuelled by major AI partnerships including a huge deal with OpenAI.
But those future revenues don’t solve today’s cash‑flow squeeze. Analysts estimate that cutting 20,000 to 30,000 jobs could free up as much as $10 billion — enough to keep the AI build‑out moving without further rattling the markets.
Oracle is betting that a leaner organisation now will buy it the runway to compete later. The question is whether the cuts arrive in time to match the speed of the AI race.
Financial markets are no strangers to volatility, but even seasoned traders were taken aback by the extraordinary price action that unfolded recently.
Just a minute
In the space of minutes, global indices lurched upwards, oil prices collapsed, and billions of dollars shifted across the financial system — all triggered by a single, unexpected announcement from President Trump claiming “productive talks” with Iran.
What followed was a whiplash-inducing reversal, a diplomatic denial from Tehran, and a growing chorus of questions about whether the market’s initial leap was quite as spontaneous as it appeared.
Spike
The sequence of events is now well documented. In the quiet pre‑market hours, trading volumes in S&P 500 futures and crude oil contracts suddenly spiked.
These were not the tentative probes of retail traders or the routine adjustments of algorithmic systems. They were large, directional, and unusually well‑timed.
Snapshot of Wall Street DFT (Dow Jones Industrial Average) demonstrating the spike in question
Minutes later, Trump posted his statement about progress with Iran — a geopolitical development with obvious implications for equities and energy markets.
Instant
Prices reacted instantly. Equities surged. Oil tumbled. Within the hour, Iran publicly denied that any such talks had taken place, prompting a partial reversal of the earlier moves. Maybe we should draw a distinction between ‘talks’ and ‘messages’.
It is the precision of the trades placed before the announcement that has raised eyebrows. Markets do not move in anticipation of news that does not exist in the public domain.
Yet someone, somewhere, positioned themselves perfectly for the impact of Trump’s message posted on social media.
Fortuitous coincidence or deliberate manipulation?
Scale
The scale of the trades suggests institutional capability; the timing suggests foreknowledge. Whether that foreknowledge was legitimate, accidental, or illicit is now the central question.
Speculation about insider trading is inevitable in such circumstances, but it is important to distinguish between suspicion and proof. Political announcements are not governed by the same disclosure rules that apply to corporate earnings or mergers.
Presidents are not bound by quiet periods. Their advisers, however, are. So are the staff, intermediaries, and diplomatic channels through which sensitive information flows.
Obligation to investigate
If anyone in that chain traded — or tipped off someone who did — regulators will be obliged to investigate.
There is also a broader concern about the integrity of market‑moving communication. If Iran’s denial is accurate, and no talks occurred, then the market reacted to a statement that may not have reflected reality.
Even without malicious intent, such episodes undermine confidence in the informational foundations on which markets depend. When a single message can add or erase trillions in value, the accuracy and reliability of that message become matters of systemic importance.
Suspicion
For now, the episode sits in an ambiguous space: suspicious, but unproven; dramatic, but not unprecedented. Markets will move on, as they always do.
Yet the questions raised yesterday will linger — about transparency, about the porous boundaries between politics and finance, and about the unseen hands that sometimes seem to move just a little too quickly.
Does the idea that Trump ‘massages’ the market carry any weight?
It’s a fair question, and one that keeps resurfacing because the pattern is hard to ignore.
The idea that Trump “massages” the markets isn’t a conspiracy theory in itself — it’s an observation that his public statements often have immediate, dramatic financial consequences.
The real issue is whether those consequences are accidental, strategic, or exploited by people with advance knowledge.
The VIX index currently (18th March 2026 – 8:30GMT) at 21.62, down around 8% from its previous close of 23.51. This drop suggests a modest easing in market fear, despite looming catalysts like the Fed decision and geopolitical tension.
VIX Snapshot – 18th March 2026
Metric
Value
Current Price
21.62 USD
Previous Close
23.51 USD
Day Change
−1.89 Down 8%
Intraday High/Low
21.72 / 21.47
52-Week High/Low
60.13 / 13.38
One-year market volatility index snapshot image 18th March 2026 at approx: 08:30 GMT
Implications
Still Elevated: A VIX above 20 suggests lingering unease, even if not full-blown panic.
Compression Context: This aligns with your “coiled spring” thesis — volatility is contained but not absent.
Directional Bias: If VIX continues to fall post-Fed, it supports a bullish breakout. A spike, however, would signal risk-off sentiment and potential sell-off.
Markets rarely sit still without reason. When they do — as they have in recent sessions, grinding sideways in an ultra‑tight range — it signals not calm but compression.
Price action becomes like a coiled spring: energy building, tension rising, and traders waiting for the moment when restraint snaps into motion.
This week’s narrow trading bands reflect a market holding its breath. Geopolitical tension in the Middle East, oil volatility, and a Federal Reserve decision all loom over investors, yet equities have refused to break down.
Futures are edging higher, European indices are opening firmer, and even the tech wobble — with Nvidia’s muted reaction to its latest showcase — hasn’t derailed broader sentiment
Tight range – a waiting game.
Historically, such tight ranges rarely resolve with a whimper. When volatility is suppressed for too long, the eventual breakout tends to be sharp and directional. The question, of course, is which way.
Right now, the evidence suggests upward. Markets have absorbed war‑driven oil swings, shrugged off hedge‑fund losses, and continued to find buyers on dips.
Breadth is stabilising, and risk appetite — surprisingly resilient given the backdrop — is creeping back into European and Asian sessions.
That doesn’t guarantee a bullish surge, but it does suggest the path of least resistance is higher.
Fed tone
If the Fed avoids surprising investors and signals comfort with the current trajectory, the spring is more likely to uncoil to the upside.
A dovish‑leaning tone could ignite a breakout as sidelined capital rushes back into equities. Conversely, a hawkish shock would release the same stored energy — but violently downward.
The market is coiled. The catalyst is imminent. And when the range finally breaks, it won’t be subtle.
You know, it almost doesn’t matter what disasters are ongoing in the world – the stock market just wants to win and go up!
Just how bad does it have to be before the stock market corrects? And what will be the catalyst to make that happen?
Debt, credit concerns, geopolitical tension, political scandal, Epstein, a rogue nuclear attack, AI failure, war or just another Trump tariff scenario?
Who knows? And does anybody really care as long as ‘making money’ isn’t interrupted.
For years we’ve clung to the comforting fiction that financial markets are rational machines. Prices rise and fall based on fundamentals, investors weigh risks carefully, and governments act as steady hands guiding the system through uncertainty.
It’s a pleasant story — and almost entirely untrue. Modern markets no longer behave sensibly because the people and structures shaping them no longer behave sensibly either.
Instead, we’ve built a hyper‑reactive ecosystem that rewards drama, amplifies noise, and punishes patience. The 24-hour mind numbing rolling news media frenzy helps feed the ‘stupid’ stock market indifference.
The result is a marketplace that convulses on command. A single line in a political speech can send oil and equities plunging, equities soaring, and futures whipsawing before most people have even digested the words.
This isn’t forward‑looking behaviour. It’s a system addicted to the ‘dollar’ adrenaline.
A Market Built on Complexity, Not Clarity
The first step in understanding today’s dysfunction is recognising just how complicated markets have become. The old world of human traders weighing company quality and long‑term prospects has been replaced by a tangled web of:
algorithmic trading systems scanning headlines for emotional triggers
derivatives hedging flows that move the underlying market
passive investment vehicles pushing money in and out mechanically
central bank signalling that distorts risk pricing
geopolitical noise that algorithms treat as gospel
Each layer adds speed, leverage, and opacity. None of it adds stability.
When markets were simpler, they could afford to be sensible. Today, they are too complex to behave rationally even if they wanted to.
The Incentives Are All Wrong
If you want to understand why markets behave badly, follow the incentives.
Traders are rewarded for short‑term performance, not long‑term judgement. Fund managers fear underperforming their peers more than they fear being wrong.
Algorithms are rewarded for speed, not context. Politicians are rewarded for drama, not restraint. News outlets are rewarded for shock and sensation, not nuance.
A comment or speech fed through central banker infiltrates opinion and moves the markets. It’s irrational behaviour – because it is now ingrained and expected!
In such an environment, knee‑jerk reactions aren’t a flaw — they’re the logical outcome of the system’s design.
A calm, measured response to geopolitical tension doesn’t generate clicks, flows, or political capital. A dramatic statement, however, can move billions in minutes. And some actors know this.
And we have blindly accepted this. One of the most uncomfortable truths about modern markets is that drama is profitable for certain players.
Volatility traders thrive on big swings. High‑frequency firms thrive on rapid order flow. Media outlets thrive on sensational headlines. Political figures thrive on attention. Algorithms thrive on sharp, binary signals. Not a constructive mix.
A calm market is good for society. A dramatic market is good for business.
So we’ve normalised the abnormal. Markets now move on:
rumours
tone
misinterpreted headlines
algorithmic overreactions
political theatre
hedging flows
central bank adjectives
This isn’t price discovery. It’s noise discovery.
We Could Have Chosen a Different Path
Here’s the part that stings: none of this was inevitable.
If governments communicated with clarity and restraint, markets would be calmer. If market makers prioritised liquidity and stability over speed, volatility would fall.
If traders were rewarded for long‑term thinking, the system would breathe more slowly. If algorithms were designed to interpret context rather than react to keywords, markets would behave more like markets and less like mindless sheep following a lost leader.
But we didn’t choose that path. We chose complexity, speed, and drama — and now we live with the consequences.
A System Too Complicated to Behave Sensibly
The modern market is not a rational judge of value. It is a behavioural ecosystem shaped by incentives, emotion, and structural institutional distortions.
It reacts to tone. It can price uncertainty, not fundamentals. It amplifies drama, not discipline.
When a single political sentence can move global markets, the problem isn’t the sentence. It’s the system that reacts to it.
Markets haven’t lost their minds. We’ve simply built a marketplace too complicated — and too dramatic — to act as if it still has one.
Fortunately, at least a good quality business can still provide a good quality return – but we all have to ride the stupid stock market roller-coaster to get there!
BYD’s sharp fall in electric‑vehicle sales across January and February 2026 marks a significant moment for the world’s largest EV maker, signalling both cyclical pressures and a deeper shift in China’s hyper‑competitive market.
Adjusted for the disruption caused by the mid‑February Lunar New Year holiday, BYD’s combined sales for the first two months of the year were down roughly 36% year on year, a rare contraction for a company that has spent the past three years dominating China’s new‑energy vehicle segment.
Slump
Several forces converged to produce the slump. The reinstatement of a 5% purchase tax on new‑energy vehicles at the end of 2025 pulled demand forward, leaving a vacuum in early 2026 as buyers rushed to complete purchases before the levy returned.
At the same time, China’s EV market is maturing, with consumers becoming more discerning and competitors far more aggressive.
Xiaomi, Leapmotor, Nio and Geely’s Zeekr all posted strong double‑digit growth over the same period, with Xiaomi’s YU7 SUV even becoming China’s best‑selling passenger vehicle in January.
This intensifying competition reflects a broader levelling of the playing field. Rivals are increasingly attacking BYD’s core mid‑market territory by packing more features into vehicles while keeping prices tight — a trend known locally as involution.
Leading still
Analysts note that while BYD’s lead remains substantial, it is narrowing as alternatives become more compelling.
Yet the picture is not uniformly negative. BYD’s strategic pivot towards overseas markets is beginning to pay off: in February 2026, its exports surpassed domestic sales for the first time, underscoring the company’s growing global footprint and providing a buffer against domestic volatility.
Later in 2026, BYD is expected to launch new models featuring its next‑generation Blade Battery 2.0 and faster flash‑charging technology — innovations that could help reignite domestic demand without resorting to a price war.
MiniMax’s M2.5 model has emerged as the unexpected frontrunner in China’s latest wave of artificial intelligence releases, earning a clear endorsement from analysts.
While much of the recent global conversation has fixated on DeepSeek’s rapid evolution, China has quietly produced five new frontier‑level models in recent weeks.
Widening choice
Among them—Alibaba’s Qwen 3.5, ByteDance’s Seedance 2.0, Zhipu’s latest offerings, DeepSeek’s V3.2, and MiniMax’s M2.5—it is MiniMax that reportedly has captured institutional attention.
Some analysts reportedly cite its performance, pricing, and commercial readiness as the reasons it stands apart.
MiniMax, which listed publicly in Hong Kong in January, released M2.5 in mid‑February 2026. The model rivals Anthropic’s Claude Opus 4.6 in capability while costing a fraction of the price—an advantage that has driven a surge of developer adoption.
Data from OpenRouter reportedly shows developers increasingly choosing M2.5 over DeepSeek’s V3.2 and even several U.S. based models.
Analysts argue that this combination of competitive performance and aggressive pricing positions MiniMax as the Chinese model with the strongest global commercial potential.
Productive and less expensive
The model’s technical profile reinforces that view. M2.5 is designed for real‑world productivity, with strengths in coding, agentic tool use, search, and office workflows.
It reportedly scores around 80.2% on SWE‑Bench Verified and outperforms leading Western models—including Claude Opus 4.6, GPT‑5.2, and Gemini 3 Pro—on tasks involving web search and office automation, all while operating at ten to twenty times lower cost.
MiniMax describes the model as delivering “intelligence too cheap to meter,” a claim supported by its lightweight Lightning variant, which generates 100 tokens per second and can run continuously for an hour at roughly one dollar.
This shift signals a broader trend: China’s AI race is no longer defined by a single breakout model. Instead, a competitive ecosystem is emerging, with MiniMax demonstrating that cost‑efficient frontier performance can reshape developer behaviour and enterprise planning.
For global markets, UBS’s preference suggests that investors are beginning to look beyond headline‑grabbing releases and toward models with sustainable commercial trajectories.
Comparison of China’s Five New AI Models
Model
Developer
Key Strengths
Performance Notes
Pricing Position
MiniMax M2.5
MiniMax
Coding, agentic tasks, office automation
Rivals Claude Opus 4.6; 80.2% SWE‑Bench Verified; outperforms GPT‑5.2 and Gemini 3 Pro on search/office tasks
Extremely low cost; “too cheap to meter”
DeepSeek V3.2
DeepSeek
Reasoning, general chat
Strong but losing developer share to M2.5
Low‑cost but not as aggressive as MiniMax
Alibaba Qwen 3.5
Alibaba
Enterprise integration, multilingual capability
Part of Alibaba’s expanding Qwen family
Competitive mid‑range
ByteDance Seedance 2.0
ByteDance
Video generation
Focused on multimodal creativity
Premium creative‑tool pricing
Zhipu (latest models)
Zhipu AI
Knowledge tasks, enterprise AI
Continues Zhipu’s push into LLM infrastructure
Mid‑range enterprise
MiniMax M2.5 leads China’s AI surge with performance rivalling Claude Opus and Gemini 1.5 Pro, yet at a fraction of the cost.
It excels in coding, search, and office automation, scoring 80.2% on SWE‑Bench Verified. DeepSeek V3.2 offers strong reasoning but lags in developer adoption.
Compared to ChatGPT-4, Claude 2.1, and Gemini 1.5, China’s models are closing the gap in capability, with MiniMax M2.5 now outperforming Western leaders on several benchmarks—especially in speed and cost efficiency.
Comparison of leading Chinese and Western AI models
(SWE‑Bench Verified — latest public leaderboard, early 2026) guide data
Model
Developer
Primary Strengths
SWE‑Bench Verified
Notes
Claude 4.6 Opus
Anthropic
High‑end reasoning, long‑context reliability
76–77%
Current top performer on independent coding benchmarks.
Nvidia’s earnings didn’t disappoint on the numbers — they were spectacular — but Wall Street was disappointed by the guidance, the pricing signals, and the shift in the AI‑chip cycle, which is why the stock fell despite a blowout quarter.
Nvidia’s latest quarterly results were, on the surface, extraordinary. Revenue surged, margins remained enviably high and demand for its AI chips continued to reshape the global technology landscape.
Yet the company’s shares fell sharply, dragging broader markets with them. The reaction reflects a deeper unease on Wall Street: not about what Nvidia has achieved, but about what comes next.
The company delivered a blowout quarter, but investors were looking for something even more explosive.
Cooling expectations after a year of euphoria
Nvidia has become the defining stock of the AI boom, and with that status comes a valuation that assumes relentless acceleration.
This quarter’s guidance, while strong, suggested growth is beginning to normalise. Investors who had priced in another step-change in demand instead saw signs of a company settling into a more sustainable—though still impressive—trajectory.
In a market conditioned to expect perpetual hyper‑growth, “very strong” can feel like a disappointment.
Fears of peak pricing power
A second concern is whether Nvidia’s extraordinary pricing power is nearing its peak. The company’s flagship AI chips have commanded eye‑watering prices, but cloud providers and enterprise customers are now signalling resistance.
Competitors are improving, and hyperscalers are accelerating development of their own silicon.
Some analysts are asking – whether the industry has already seen the high‑water mark for Nvidia’s margins, a question that goes straight to the heart of the stock’s valuation.
China remains a structural drag
Regulatory constraints continue to weigh on Nvidia’s China business. The company has not yet been able to meaningfully sell its U.S. approved AI chips into the market, and executives have warned that local rivals could fill the gap.
China was once a major contributor to Nvidia’s data‑centre revenue; now it is a source of uncertainty. Investors are increasingly factoring in the possibility that this revenue may not return in its previous form.
A crowded trade unwinds
Finally, Nvidia’s sell‑off reflects positioning as much as fundamentals. The stock has been one of the most crowded trades in global markets.
When expectations are stretched, even exceptional results can trigger profit‑taking. The pullback spilled into broader indices, with Asia‑Pacific markets trading mixed as investors digested the slump.
Nvidia remains the central force in the AI hardware boom, but Wall Street is beginning to ask harder questions about sustainability, competition and the next phase of growth.
When artificial intelligence first ignited investor enthusiasm, it lifted almost every major technology stock.
The narrative was simple: AI would transform industries, boost productivity and unlock vast new revenue streams.
Yet as the cycle matures, markets are becoming more selective. In recent weeks, shares of IBM have drifted lower, illustrating how the ‘AI effect’ can cut both ways.
At first glance, IBM should be a prime beneficiary. The company has spent years repositioning itself around hybrid cloud infrastructure, data analytics and enterprise AI solutions.
Its Watson platform has been refreshed with generative AI tools designed to automate customer service, streamline software development and enhance business decision-making. Management has repeatedly emphasised AI as a core growth engine.
Market Expectations
However, the market’s expectations have shifted. Investors are increasingly rewarding companies that sit at the very heart of AI infrastructure — those supplying advanced semiconductors, high-performance computing capacity and hyperscale cloud services.
These businesses are reporting visible surges in AI-related demand, often accompanied by sharp revenue acceleration and expanding margins.
By contrast, IBM’s AI exposure is embedded within broader consulting and software operations, making its growth trajectory appear steadier rather than explosive.
This distinction matters in a momentum-driven environment. When earnings updates fail to deliver dramatic upside surprises, shares can quickly lose favour.
Less AI Effect
IBM’s results have shown progress in software and recurring revenue, but they have not reflected the kind of dramatic AI-driven uplift seen elsewhere in the sector. For some investors, that raises questions about competitive positioning and pricing power.
There is also a perception issue. Despite its reinvention efforts, IBM still carries the legacy image of a mature technology conglomerate rather than a cutting-edge AI disruptor.
In a market captivated by bold innovation stories, narrative can influence valuation just as much as fundamentals.
If capital flows concentrate in a handful of high-growth AI names, diversified players may struggle to keep pace in share price performance.
AI Tension
Yet the sell-off may also highlight a deeper tension within the AI theme. Enterprise adoption of AI tools tends to be gradual, cautious and closely tied to measurable productivity gains.
IBM’s strategy is built around long-term integration rather than short-term hype. While that approach may lack immediate fireworks, it could prove more durable as corporate clients prioritise reliability, governance and cost control.
For now, though, the AI effect is amplifying investor discrimination. In a market eager for rapid transformation, IBM’s more measured path has translated into weaker share performance — a reminder that not all AI exposure is valued equally.
Further discussion
IBM has found itself on the wrong side of the artificial intelligence boom, with its shares tumbling more than 13% after Anthropic unveiled a new capability that directly targets one of the company’s most enduring revenue pillars: COBOL modernisation.
The sell‑off reflects a broader market anxiety that AI is beginning to erode long‑protected niches in enterprise technology, and IBM has become the latest high‑profile casualty.
For decades, IBM has been synonymous with mainframe computing and the maintenance of vast COBOL‑based systems that underpin global finance, government services, airlines, and retail transactions.
These systems are notoriously complex, expensive to update, and dependent on a shrinking pool of specialist developers.
Premium Brand
That scarcity has long worked in IBM’s favour, allowing it to charge a premium for modernisation and support.
Anthropic’s announcement threatens to upend that equation. Its Claude Code tool, the company claims, can automate the most time‑consuming and costly parts of understanding and restructuring legacy COBOL environments.
Tasks that once required teams of analysts months to complete—mapping dependencies, documenting workflows, identifying risks—can now be accelerated dramatically through AI‑driven analysis.
The implication is clear: modernising legacy systems may no longer require the same level of human expertise, nor the same level of spending.
Investors reacted swiftly. IBM’s share price fell to $223.35, extending a year‑to‑date decline of more than 24% – recovering later to $229.39
IBM one-year chart as of 24th February 2026
The drop reflects not only concerns about lost revenue, but also the fear that IBM’s competitive moat—built on decades of institutional reliance on COBOL—may be eroding faster than expected.
The timing has amplified market jitters. Only days earlier, cybersecurity stocks were hit by another Anthropic announcement: Claude Code Security, a feature designed to scan codebases for vulnerabilities.
AI Mood Logic
The rapid expansion of AI into specialised technical domains has created a ‘sell first, ask questions later’ mood across the market, with investors increasingly wary of companies whose business models depend on labour‑intensive or legacy‑bound processes.
For IBM, the challenge now is to demonstrate that it can harness AI rather than be displaced by it.
The company has invested heavily in its own AI initiatives, but the latest market reaction suggests investors are unconvinced that these efforts will offset the threat to its traditional strongholds.
The AI revolution is reshaping the technology landscape at speed. IBM’s sharp decline is a reminder that even the industry’s oldest giants are not insulated from disruption—and that the next wave of AI competition may hit the most established players hardest.
But remember, this is IBM we are talking about.
Explainer
What is COBOL?
COBOL is an old but remarkably durable programming language created in the late 1950s to run business, finance, and government systems, and it’s still powering much of the world’s banking and administrative infrastructure today.
It was designed to read almost like plain English, making it easier for non‑technical managers to understand, and its stability means many core systems have never been replaced.
For much of the past three years, the so‑called Magnificent Seven – Apple, Microsoft, Alphabet, Amazon, Meta, Tesla and Nvidia – have powered US equities to repeated record highs.
Their sheer scale, earnings strength and centrality to the AI boom turned them into a market narrative as much as an investment theme.
But as 2026 unfolds, the question is no longer whether they can keep leading the market higher, but whether the idea of treating them as a single trade still makes sense.
The short answer is closer to: the trade isn’t dead, but the era of effortless, broad‑based mega‑cap dominance is fading.
Mag 7 fatigue
The first sign of fatigue is the breakdown in cohesion. Last year, only a minority of the seven outperformed the wider S&P 500, a sharp contrast to the near‑uniform surges of 2023 and early 2024.
Nvidia and Alphabet continue to benefit from the structural demand for AI infrastructure and cloud‑driven productivity gains. Others, however, appear to be wrestling with slower growth, regulatory pressure or strategic resets.
Apple faces a maturing hardware cycle, Tesla is contending with intensifying global competition, and Meta’s spending plans continue to divide investors.
Mag 7 trade – which company is missing?
Divergence
This divergence matters. For years, investors could simply buy the group and let the rising tide of AI enthusiasm and index concentration do the work.
That simplicity has evaporated. Stock‑picking is back, and the market is finally distinguishing between companies with accelerating earnings power and those relying on past momentum.
At the same time, market breadth is improving. Capital is rotating into industrials and defensive sectors as investors seek exposure to areas that have lagged the mega‑cap rally. However, AI is affecting software stocks, law and financial sectors.
Healthy future
This broadening is healthy: it reduces concentration risk and signals that the U.S. economy is no longer dependent on a handful of tech giants to sustain equity performance.
Yet it would be premature to declare the Magnificent Seven irrelevant. Their combined earnings growth is still expected to outpace the rest of the index, and their role in AI, cloud computing and digital infrastructure remains foundational.
Change
What has changed is the nature of the trade. These are no longer seven interchangeable vehicles for tech exposure; they are seven distinct stories with diverging trajectories.
The Magnificent Seven haven’t left the stage. They have likely stopped performing in unison – and for investors, that marks the beginning of a more nuanced, more selective chapter.
Nvidia has formally severed its financial ties with Arm Holdings, selling the final tranche of its shares and closing the book on one of the semiconductor industry’s most ambitious — and ultimately unsuccessful — takeover attempts.
Regulatory filings reportedly show the chipmaker disposed of roughly 1.1 million Arm shares during the fourth quarter, a holding valued at around $140 million based on Arm’s recent market price.
Sale of entire ARM stake
The move brings Nvidia’s ownership of the British chip‑architecture specialist to zero, marking a symbolic end to a saga that began in 2020 when Nvidia launched a bold $40 billion bid to acquire Arm.
That deal, which would have reshaped the global semiconductor landscape, collapsed under intense regulatory scrutiny and resistance from major industry players concerned about competition and neutrality.
Despite the divestment, the relationship between the two companies is far from over. Nvidia remains a major licensee of Arm’s instruction‑set technology, which underpins its current and next‑generation CPU designs.
Strategic move
Analysts note that the sale appears to be strategic housekeeping rather than a shift in technological direction, especially given Nvidia’s rapid expansion across data‑centre, AI, and edge‑computing markets.
Arm’s shares initially wobbled on news of the disposal but quickly stabilised, even edging higher as investors interpreted Nvidia’s exit as a clearing of legacy baggage rather than a signal of weakening confidence in Arm’s long‑term prospects.
The company, now primarily owned by SoftBank, continues to push ahead with its growth strategy following its public listing.
For Nvidia, the sale represents a clean break from a failed acquisition that once promised to redefine the industry.
For Arm, it marks another step in its evolution as an independent powerhouse at the centre of global chip design. The strategic paths of both companies however, remain intertwined
The world’s largest cloud providers are engaged in one of the most expensive technological races in history.
Amazon, Microsoft, Meta and Alphabet are collectively on track to spend as much as $700 billion on AI‑related capital expenditure this year — a figure that rivals the GDP of mid‑sized nations and has understandably rattled investors.
The question now dominating markets is simple: can hyperscalers justify this level of spending, and should analysts remain so bullish on their stocks?
A Binary Bet on the Future of AI
The scale of investment has shifted the AI build‑out from a strategic growth initiative to what some analysts describe as a binary corporate bet. As some analysts suggest, the leap in capex — up roughly 60% year‑on‑year — means the payoff must be both rapid and substantial.
If monetisation fails to keep pace, the consequences could be of severe concern.
This is compounded by the fact that hyperscalers are now consuming nearly all of their operating cash flow to fund AI infrastructure, compared with a decade‑long average of around 40%. That shift alone explains the recent market jitters.
Why Analysts Remain Upbeat
Despite the turbulence, many analysts still argue the long‑term fundamentals remain intact. One reason is that hyperscalers are pre‑selling data‑centre capacity before it is even built, effectively locking in revenue ahead of deployment.
That dynamic supports the bullish view that AI demand is not only real but accelerating.
There is also a belief that as AI tools become embedded across consumer and enterprise workflows, willingness to pay will rise sharply.
If that scenario plays out, today’s eye‑watering capex could look prescient rather than reckless.
The Real Risk: Timelines
The challenge is timing. Much of the infrastructure being deployed — from chips to data‑centre hardware — has a useful life of just three to five years.
That gives hyperscalers a narrow window to recoup investment before the next upgrade cycle hits.
Without clearer monetisation strategies and firmer payback timelines, investor anxiety is likely to persist.
AI capex justification?
Hyperscalerscan justify their AI capex — but only if demand scales as quickly as they expect and monetisation becomes more transparent.
Analysts may be right to stay bullish, but the margin for error is shrinking. In the coming quarters, clarity will matter as much as capital.
A curious shift has taken place over the past year. The fear of AI ‘taking over’ is no longer confined to software engineers, coders, or the legal and financial professions.
It has spilled into transport logistics, estate agency, recruitment, customer service, and even the once‑untouchable world of creative work.
Anxiety spreads
The anxiety is spreading horizontally across the economy rather than vertically within a single industry — and that tells us something important about where we are in the technological cycle.
At the heart of this unease is a simple realisation: AI is no longer a specialised tool. It is becoming a general‑purpose capability, much like electricity or the internet.
When a technology can be applied to almost any workflow, the boundaries between ‘safe’ and ‘at risk’ jobs dissolve.
Estate agents see AI systems that can generate listings, negotiate pricing models, and automate client follow‑ups. Logistics managers watch algorithms optimise routes, staffing, and inventory with a precision no human team can match.
Even white‑collar professionals, once insulated by complexity and regulation, now face AI systems capable of drafting contracts, analysing case law, or producing financial models in seconds.
This broadening of impact is what’s fuelling the current wave of concern. It’s not that AI is replacing everyone — it’s that it could plausibly reshape the value chain in every sector.
Axis shift
For the stock market, this shift has created a two‑speed economy. Companies building AI infrastructure — chips, cloud platforms, foundation models — are being rewarded with valuations that assume long‑term dominance.
Meanwhile, firms whose business models rely on labour‑intensive processes are being quietly repriced. Investors are asking a new question: Which companies can integrate AI fast enough to defend their margins? Those that can’t risk being treated like legacy utilities.
But the story isn’t simply about winners and losers. The diffusion of AI across industries also creates a multiplier effect.
Productivity gains in logistics lower costs for retailers; smarter estate agency tools accelerate housing transactions; automated legal drafting reduces friction for start‑ups. Each improvement compounds the next.
AI taking over?
The fear, then, is partly a misunderstanding. AI isn’t ‘taking over’ — it’s infiltrating. It is dissolving inefficiencies, redrawing job descriptions, and forcing companies to rethink what they actually do.
The stock market has already priced in the first wave of this transformation. The second wave — where every sector becomes an AI‑enabled sector — is only just beginning.
Alphabet’s decision to issue a 100-year sterling bond has captured the attention of global markets, not only because of its rarity but also because of what it signals about the escalating competition in artificial intelligence.
100 year sterling bond
A century-long bond denominated in pounds is an extraordinary financing move, particularly for a technology company.
It reflects both investor confidence in Alphabet’s long-term prospects and the scale of capital now required to compete in the AI era.
On the surface, the benefits are clear. Locking in funding for 100 years at today’s rates provides financial certainty. Alphabet can secure vast sums of capital without facing refinancing risk for generations.
In an industry defined by rapid change and enormous upfront costs — from data centres and semiconductor procurement to specialised AI chips and energy infrastructure — patient capital is invaluable.
Sterling
The sterling denomination also diversifies Alphabet’s funding base beyond U.S. dollar markets, potentially appealing to European institutional investors seeking stable, long-duration assets.
The bond may also be interpreted as a strategic signal. By committing to long-term financing, Alphabet demonstrates confidence in its ability to generate cash flows well into the next century.
It reinforces the company’s image as a durable, infrastructure-like enterprise rather than a volatile technology stock.
For investors such as pension funds and insurers, a 100-year instrument from a highly rated issuer can offer predictable returns in a world where long-term yield is scarce.
Cyclical
However, the move is not without shortcomings. Committing to fixed debt obligations over such an extended horizon reduces flexibility. While Alphabet currently enjoys strong balance sheet metrics, the technology sector is notoriously cyclical.
A century is an eternity in innovation terms. Business models, regulatory frameworks and geopolitical dynamics may shift dramatically.
Future generations of management will inherit the obligation, regardless of whether today’s AI investments deliver the expected returns.
More broadly, the bond feeds concern about a debt-fuelled AI arms race. As technology giants pour tens of billions into AI research, chip design and cloud infrastructure, borrowing is becoming an increasingly prominent tool.
If rivals respond with similar long-dated issuance, the sector’s leverage could rise meaningfully. In a downturn or if AI monetisation disappoints; heavy debt burdens could amplify financial strain.
Ultimately, Alphabet’s 100-year sterling bond embodies both ambition and risk. It underlines the immense capital demands of the AI revolution while raising questions about whether today’s competitive fervour is encouraging companies to stretch their balance sheets too far in pursuit of technological dominance.
Systemic anxiety
The deeper anxiety is systemic. With Oracle, Amazon, Microsoft and others also scaling up borrowing, total tech‑sector issuance is projected to hit $3 trillion over five years.
Some analysts warn this resembles a late‑cycle credit boom, where investors chase thematic excitement rather than sober fundamentals.
Alphabet’s century bond may be a masterstroke of timing — or a marker of excess.
Either way, it crystallises the tension at the heart of the AI revolution: extraordinary promise, financed by extraordinary debt.
Why a Sterling Bond?
Alphabet issued its 100‑year sterling bond to tap deep UK demand for ultra‑long‑dated assets, especially from pension funds seeking to match long‑term liabilities.
The sterling market offered strong appetite, with orders reportedly reaching nearly ten times the £1 billion on offer.
It also formed part of Alphabet’s broader multi‑currency fundraising drive to finance massive AI‑related capital spending, including data‑centre expansion.
Issuing in sterling diversified its investor base, reduced reliance on U.S. dollar markets, and signalled confidence in its long‑term stability as a quasi‑infrastructure‑scale business.
Japan’s Nikkei 225 has surged to a series of record highs, signalling a decisive shift in investor sentiment as political clarity, a weak yen, and global tech momentum converge.
The index has climbed well beyond its previous peaks, driven by strong demand for semiconductor and AI‑linked stocks, alongside renewed confidence in Japan’s economic direction.
The index is hitting repeated all‑time highs
The Nikkei has surged to fresh record levels — closing around 57,650 and even touching 57,760 in early trade. This marks consecutive days of record closes.
In previous intraday trading the Nikkei 225 touched 58,500.
The driver: the ‘Takaichi trade’
Markets are reacting strongly to Prime Minister Sanae Takaichi’s landslide election victory, which has created expectations of:
Looser economic policy
Increased fiscal stimulus
A more stable political environment
Investors are effectively pricing in a pro‑growth agenda with fewer legislative obstacles.
Much of the rally reflects expectations of a more expansionary policy environment. Investors are likely betting that the government will prioritise growth, support corporate investment, and maintain a stable backdrop for reform.
This has amplified interest in heavyweight exporters and technology firms, which stand to benefit both from global demand and the yen’s prolonged softness.
Weaker Yen?
The currency’s slide towards multi‑decade lows has been a double‑edged force: while it boosts overseas earnings for major manufacturers, it also raises the prospect of intervention from policymakers keen to avoid excessive volatility.
For now, markets appear comfortable with the trade‑off, focusing instead on the competitive advantage it provides.
With global equity markets still heavily influenced by AI enthusiasm and shifting monetary expectations, Japan’s resurgence stands out.
The Nikkei’s latest ascent suggests investors are increasingly willing to treat Japan not as a defensive allocation, but as a genuine engine of growth in its own right.
The Dow Jones Industrial Average has surged beyond the 50,000 mark for the first time in its 130‑year history, capping a dramatic rebound after a turbulent week for global markets.
The blue‑chip index leapt more than 1,200 points on Friday 6th February 2026 to close at 50,115.
DJIA one-year chart
This climb was fuelled by renewed investor confidence and a sharp recovery in technology and cyclical stocks.
Friday’s rally followed several days of heavy selling across the tech sector, but optimism returned as chipmakers and industrial giants led a broad‑based climb.
Analysts say the move signals both the resilience of the current bull market and investors’ willingness to ‘buy the dip’ despite ongoing volatility.
Political reaction was swift, with President Donald Trump celebrating the milestone as a symbol of American economic strength.
Psychological 50,0000 barrier
Market commentators, meanwhile, emphasised the psychological significance of the 50,000 threshold, noting that the Dow has added 10,000 points in record time.
For traders on the floor of the New York Stock Exchange, the moment was marked by cheers, flashing screens, and a palpable sense of relief.
Whether the momentum continues remains to be seen, but for now, Wall Street is savouring a landmark moment decades in the making.
China’s Hong Kong‑listed tech stocks have slipped decisively into a bear market, with the Hang Seng Tech Index now more than 20% below its October 2025 peak.
The downturn is being driven by a potent mix of tax concerns and global anxiety over the disruptive pace of artificial intelligence.
China’s Hong Kong‑listed technology sector has entered a sharp reversal after last year’s rally, with the Hang Seng Tech Index falling and officially breaching bear‑market territory.
The decline reflects a broader shift in sentiment as investors reassess the risks facing the sector.
AI Disruption and Global Risk Aversion
While tax worries have been widely cited, the global ‘AI effect’ is proving equally influential. Investors are increasingly concerned that rapid advances in artificial intelligence could reshape competitive dynamics across the tech landscape.
Companies perceived as lagging in AI development face heightened scrutiny, while uncertainty over regulatory responses adds further pressure.
This has contributed to a wave of risk aversion, particularly toward Chinese firms already navigating geopolitical and policy headwinds.
Policy Anxiety and VAT Concerns
Fears of potential tax hikes — including a possible increase in value‑added tax on internet services — have amplified the sell‑off.
Recent VAT changes in telecom services have made markets more sensitive to policy signals, prompting investors to reassess earnings expectations for major platform companies.
A Reversal of Momentum
The speed of the downturn has surprised many, given the strong rebound seen in 2025. Yet the combination of AI‑driven uncertainty, shifting regulatory expectations, and global market caution has created a challenging backdrop for Chinese tech stocks.
With sentiment fragile, analysts warn that volatility may persist until investors gain clearer visibility on both policy direction and the sector’s ability to adapt to accelerating AI disruption.
Is it coming to western stocks – especially in the U.S.?
It’s certainly possible that a similar dynamic could wash across Western markets, though not necessarily in the same form.
The extraordinary concentration of returns in a handful of U.S. mega‑cap AI leaders has created a structural imbalance: if investors begin to doubt the durability of AI‑driven earnings, or if regulatory pressure intensifies, the correction could be sharp because so much capital is leaning in the same direction.
Europe, meanwhile, faces a different vulnerability — a chronic under‑representation in frontier AI, which could leave its tech sector exposed if global capital rotates aggressively toward firms with demonstrable AI scale.
None of this guarantees a bear market, but the ingredients are present: stretched valuations, high expectations, and a technology cycle moving faster than many business models can adapt.
U.S. software companies are gradually feeling the impact—how long before the U.S. AI sector experiences a correction?
The sense of unease rippling through global markets has grown steadily louder, and now several veteran analysts reportedly argue that the rally of 2025 may be running out of steam.
Their warning is stark: the ‘historical clock is ticking’, and the conditions that typically precede a broad market correction are increasingly visible.
Throughout 2025, equities surged with remarkable momentum, fuelled by resilient corporate earnings, strong consumer spending, and a wave of optimism surrounding technological innovation.
Weakening
Yet beneath the surface, the foundations of this rally have begun to look less secure. Analysts reportedly highlighted that geopolitical risks are approaching an inflection point, creating a fragile backdrop in which even a modest shock could tip markets into correction territory.
One of the most pressing concerns is valuation. After a year of exceptional gains, many global indices now appear stretched relative to historical norms.
When markets price in near‑perfect conditions, they leave little margin for error. Any deterioration in earnings, policy stability, or global trade dynamics could prompt a swift reassessment of risk.
This is precisely the scenario experts fear as 2026 unfolds.
Geopolitics
Geopolitics adds another layer of complexity. Rising tensions across key regions, shifting alliances, and unpredictable policy decisions have created an environment where sentiment can turn rapidly.
Some strategists emphasise that these pressures are converging at a moment when markets are already vulnerable, increasing the likelihood of a meaningful pullback.
Technical indicators also point towards late‑cycle behaviour. Extended periods of low volatility, accelerating sector rotations, and narrowing market leadership are all hallmarks of a maturing bull run.
While none of these signals guarantee a correction, together they form a pattern that seasoned investors recognise from previous cycles.
Don’t panic?
Despite the warnings, experts are not advocating panic. Corrections, they argue, are a natural and even healthy part of market dynamics.
They reset valuations, curb excesses, and create opportunities for disciplined investors. The key is preparation: reassessing risk exposure, diversifying across sectors and geographies, and avoiding over‑concentration in the most speculative corners of the market.
As 2026 begins, the message from analysts is clear. The rally of 2025 was impressive, but it may also have been the calm before a necessary storm.
Whether the correction arrives swiftly or unfolds gradually, the prudent approach is to stay alert, stay balanced, and recognise that even the strongest markets cannot outrun history forever.
At the same time, experts argue that enthusiasm for AI stocks has pushed prices far beyond what current earnings can justify, raising the risk of a sharp pullback if sentiment turns or growth expectations soften.
AI reckoning
A number of commentators even outline scenarios for a broader ‘AI reckoning’, where inflated expectations collide with the slower, more incremental reality of enterprise adoption.
This doesn’t guarantee a crash, but it does suggest that the market is vulnerable to any disappointment in revenue growth, chip demand, or data‑centre utilisation.
However, not all analysts believe a dramatic collapse is inevitable. Some argue that while valuations are undeniably high, the scale of investment may still be justified by long‑term structural demand for compute, automation, and agentic AI systems.
Survey
A recent survey of 40 industry leaders shows a split: many fear a bubble, but others maintain that heavy capital expenditure is necessary to meet future AI workloads and that the sector could experience a period of deflation or consolidation rather than a full‑scale crash.
A more moderate scenario—favoured by several economists—is a multi‑quarter pullback as markets digest rapid gains, capital costs normalise, and companies shift from hype‑driven spending to proving real returns.
In this view, AI’s long‑term trajectory remains intact, but the near‑term path is likely to be bumpier and more disciplined than the exuberance of the past two years.
Are we in an AI bubble? Here is my conclusion
The latest commentary suggests we’re still in a highly speculative phase of the AI boom, with massive infrastructure spending and concentrated market gains creating bubble‑like conditions.
So, the safest summary is this: valuations are stretched, expectations are overheated, and investment is flowing faster than proven revenue.
Yet unlike past bubbles the underlying technology is delivering real adoption and measurable productivity gains, meaning we may be in an overhyped surge rather than a classic doomed bubble.
A deflation effect of some sort is likely and soon.
