Speaking at the Forbes Global CEO Conference in Singapore on October 7, the Bridgewater Associates founder described AI as a “classic bubble” approaching a potential breaking point.

“I think we’re close to that,” Dalio said, according to Bloomberg’s report. His remarks were a warning about financial conditions, without a specific date for a crash.

Why borrowing matters

Technology companies are committing enormous sums to chips, data centers and computing infrastructure, increasingly using debt to fund expansion.

Higher rates make new borrowing and refinancing more expensive. Projects also need stronger returns to justify their financing costs, creating pressure when spending arrives well before revenue.

Dalio also pointed to the risk of investors needing to convert paper wealth into cash. Selling assets to meet those needs can intensify pressure on prices.

Related: The AI Boom Is Increasingly Being Financed by Debt.

The test is whether revenue catches up

A technology can prove useful while some investments in it fail to earn adequate returns. For AI companies, the financial test involves customer revenue, operating costs and the timing of debt repayments.

Companies with strong cash generation have more flexibility than businesses dependent on repeated fundraising to complete projects.

Dalio’s warning puts the financing behind the AI boom in focus: ambitious growth plans become harder to sustain when borrowing costs rise faster than cash flow.

Disclosure: This article does not represent investment advice. The content is for informational and educational purposes only.

The post Billionaire Ray Dalio Warns AI Bubble Could Soon Burst first appeared on Finblog.

Activity has accelerated especially for debt tied to Alphabet Inc. and Meta Platforms, with roughly $895 million and $687 million in outstanding contracts respectively. Trading tied to Oracle Corp. has also been active for months.

Analysts say the surge reflects growing concern that Big Tech borrowing could balloon as companies race to dominate artificial intelligence. Investors estimate global AI build-out costs could exceed $3 trillion, much of it financed through debt.

“This hyperscaler trend is enormous,” said Gregory Peters of PGIM Fixed Income, noting investors are increasingly reluctant to remain unhedged against potential credit deterioration.

Banks themselves are also buying protection. Institutions underwriting massive loans for data centers and AI infrastructure are hedging exposure while they distribute those loans, according to executives at Bank of America.

Borrowing is expected to accelerate. Morgan Stanley estimates hyperscaler debt issuance could reach $400 billion in 2026, up sharply from about $165 billion in 2025. Alphabet alone plans up to $185 billion in capital expenditures this year.

Still, not everyone sees danger. Some hedge funds, including those tied to Saba Capital Management, are selling credit protection instead, betting that trillion-dollar tech giants will remain stronger than the broader corporate credit market even in downturn scenarios.

Others remain cautious. Portfolio managers at Aegon Ltd. warn that the sheer scale of potential borrowing could eventually pressure credit quality if returns from AI investments fail to keep pace.

Wall Street is not abandoning the AI boom, but the rapid growth of derivatives tied to tech debt signals that investors are increasingly preparing for the possibility that the sector’s spending race may carry hidden financial risks.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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Silver Flash Crash 2026: Why Did Markets Lose $3.2T?

The post AI bubble fears are creating new derivatives first appeared on Finblog.

Asked late last year whether he worried about an AI bubble, Trump’s answer was blunt: “No. I love AI.”

Growth first, guardrails later

That confidence has translated into policy. Over the past year, the administration has cut red tape, eased rules for data center construction, expanded access to chips and power, and blocked states from writing their own AI regulations. The goal is simple: accelerate investment in what the White House sees as the strongest pillar of an otherwise fragile US economy.

The strategy got a boost when GDP data showed the economy growing at more than 4% annualized in the latest quarter. Kevin Hassett, head of the National Economic Council, called the numbers evidence of an AI driven boom, pointing to surging tech investment and soaring equity prices.

Stocks tied to AI infrastructure have powered the rally, with companies like Nvidia again helping push markets to record highs.

Economists see upside and risk

Not everyone is convinced the story is risk free. Many economists and technologists warn that AI could boost productivity while still cutting jobs, especially in white collar roles. Others worry about how the boom is being financed.

Major tech firms have issued more than $120 billion in debt this year to build massive data centers. Analysts at Goldman Sachs say today’s AI surge rhymes with past bubbles, even if the companies involved are far stronger than dot com era startups.

Former Council of Economic Advisers chair Glenn Hubbard called AI a “game changer” for productivity, but cautioned that communities and workers may not be ready for the speed of change. Past tech shifts, he noted, left many people behind.

Jobs anxiety grows, especially for young workers

So far, there is no wave of AI driven layoffs in the official data. But cracks are forming.

• A New York Fed survey found firms adopting AI are slowing hiring, not firing.
• About one quarter of companies said they plan to reduce hiring for college educated roles.
• Research from Stanford shows workers aged 22 to 25 are among the most exposed in AI heavy industries.

The administration downplays these risks. Hassett argues AI will augment workers, acting as a “great coach”, not a replacement. Trade adviser Peter Navarro went further, suggesting displaced white collar workers consider blue collar jobs, including manufacturing.

The Fed is watching closely

At the Federal Reserve, AI is now a key variable in the inflation and labor outlook.

Governor Lisa Cook said productivity gains from AI could help fight inflation, but stressed that the Fed is closely monitoring labor impacts. Another governor, Christopher Waller, warned that disruptions come before benefits, a familiar pattern with new technologies.

History looms large. In the late 1990s, aggressive tech investment helped fuel growth before the dot com bubble burst, wiping out firms and triggering a downturn. Some economists see similar froth today, even if the fundamentals are stronger.

No bailout promise, but big stakes

Despite the risks, the White House shows little appetite for restraint. Officials say the biggest danger would be slowing AI with regulation, not letting it run.

When an executive at OpenAI floated the idea of a federal backstop if the sector stumbled, the response was swift. The administration publicly ruled out any bailout, arguing that if one AI firm fails, others will replace it.

Still, policy experts warn that if debt heavy data centers sit idle and tech giants stumble, the fallout could spread quickly through markets and the economy.

Why this matters now

The White House is all in on AI as a growth engine heading into 2026. Markets are cheering, investment is exploding, and regulation is being rolled back. But job anxiety, rising leverage, and bubble comparisons are growing louder.

As one analyst put it, no one knows they are in a bubble until it bursts. For now, Washington is betting that AI’s rewards arrive faster than its risks. Whether that gamble pays off may define the next phase of the US economy.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: How Big Tech Created the 2025 AI Boom on Debt

Stocks Split as Jobs Data and Trump’s Venezuela Oil Deal Take Spotlight

The post White House bets big on AI boom and shrugs off bubble and job fears first appeared on Finblog.

The S&P 500 came close to a tariff-driven bear market in April, only to stage a powerful rebound that carried the index to new records by summer. Behind the headline gains, however, investors faced extreme swings, rising concentration risks, and growing unease about valuations.

More about: 6 Charts That Show How Stock Markets Got Reshaped in 2025

Here is how the year unfolded, and why it mattered.

From Tariff Panic to AI Fueled Recovery

Markets entered 2025 on solid footing, but sentiment flipped sharply in April when sweeping US tariff plans triggered fears of a trade driven slowdown. The S&P 500 fell nearly 15 percent at its lows, and volatility surged.

The Cboe Volatility Index jumped above 50, a level seen only during the pandemic and the global financial crisis. That fear faded just as quickly after tariff delays were announced, sending volatility back below 20 by May.

By mid year, enthusiasm around artificial intelligence spending helped lift corporate profit expectations and reignite risk appetite. The S&P 500 is now up roughly 16 percent for the year, marking its third consecutive year of double digit gains.

“It was Trump 1.0 on steroids,” said Keith Lerner of Truist Advisory Services, pointing to the unusual influence of political decisions on market swings.

ETF Flows Reveal the Turning Point

Investor behavior clearly split the year into two phases. April saw sharp equity ETF outflows, particularly from cyclical sectors, as investors reduced risk exposure.

The Nasdaq 100 tracking Invesco QQQ ETF recorded its first net outflow in seven months during that period. Once tariff pressure eased, those flows reversed quickly, with inflows accelerating again in May as tech stocks rebounded.

Strategists noted that the pace and intensity of flows reflected how sensitive markets had become to policy signals.

Wall Street Forecasts Were Whiplashed

2025 proved especially humbling for market forecasters. Nearly every major bank cut S&P 500 targets following the tariff shock, only to raise them again weeks later as conditions improved.

Unlike past corrections, where recoveries typically took four months, the market bounced back in roughly half that time.

“The speed of the recovery was extraordinary,” said Sam Stovall of CFRA, comparing the forecasting chaos to early 2020.

Bubble Anxiety Returns

Valuations became another major source of tension. Early in the year, veteran investor Howard Marks warned that markets were entering bubble territory. Those concerns intensified after the release of China’s DeepSeek AI model reignited fears of overinvestment and competition.

Some research firms flagged semiconductor stocks as meeting the formal criteria for a bubble. Others pushed back, arguing earnings growth expectations through 2027 still justify current prices.

The result was a market caught between conviction and caution.

Concentration Risk Reaches Extremes

One of the clearest structural shifts in 2025 was market concentration. The top 10 stocks now represent nearly 40 percent of the S&P 500, driven largely by the so called Magnificent Seven.

Critics warn that this level of concentration leaves the index vulnerable to sharp reversals if leadership falters.

“The S&P is doing a poor job of diversification right now,” said Macro Risk Advisors founder Dean Curnutt.

That concentration also made life difficult for active managers. Only 22 percent of actively managed large cap funds beat the index this year, the lowest share since 2016.

Global Markets Quietly Outperformed

Despite the S&P 500’s recovery, US stocks lagged international peers. Markets in Europe, Japan, and parts of Asia outperformed, helped by currency moves and less policy uncertainty.

Strategists described the underperformance as a self inflicted outcome tied to US trade and political risk, combined with years of prior US dominance finally unwinding.

What 2025 Leaves Behind

The lesson of 2025 is not just about returns, but about fragility.
Markets proved resilient, yet deeply sensitive to policy shocks, narrow leadership, and shifting narratives around AI.

As investors head into 2026, expectations remain optimistic. But the extremes of 2025 have left behind a market that looks stronger on the surface than it may be underneath.

Volatility, concentration, and valuation debates are unlikely to fade anytime soon.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Stocks Look Bullish Entering 2026 — But What Could Go Wrong?

FOMO vs. Bubble Angst Signals More Stock Volatility in 2026

How Big Tech Created the 2025 AI Boom on Debt

The post The Stock Market’s Wild 2025 Roller-Coaster Ride in Six Charts first appeared on Finblog.

The year began with optimism. Oracle surged after announcing the massive Stargate joint venture with OpenAI and SoftBank, committing up to $500 billion toward US AI infrastructure. The deal, unveiled at the White House in January, sent Oracle shares soaring and briefly pushed founder Larry Ellison to the top of global wealth rankings.

Momentum continued through midyear earnings as Oracle projected AI-driven cloud revenue reaching $166 billion by 2030. But by autumn, enthusiasm gave way to anxiety.

Debt became the turning point

Oracle issued nearly $26 billion in bonds in 2025, while total debt climbed 40% year over year to $124 billion. At the same time, cash outflows jumped sharply, and the company disclosed $248 billion in future lease commitments, mostly tied to data center expansion, that sit off the balance sheet.

That combination rattled investors.

Credit default swaps tied to Oracle surged to their highest levels since 2009, signaling growing concern about leverage across Big Tech’s AI buildout. Analysts note this trend is not isolated. CDS trading has recently emerged even for firms like Microsoft and Alphabet, reflecting broader unease about AI financing.

“Oracle has become the poster child for fears of an AI bubble,” tech analyst Cory Johnson said.

A major source of investor tension lies in Oracle’s exposure to OpenAI. The ChatGPT developer accounts for more than $300 billion of Oracle’s remaining performance obligations. That revelation triggered a sharp selloff as markets questioned whether OpenAI can realistically meet its aggressive revenue targets amid intensifying competition.

OpenAI’s own costs add to the concern. Infrastructure commitments linked to partners including Nvidia, AMD, and Broadcom could total over $1.4 trillion across eight years, raising doubts about long-term returns.

Execution risk is now front and center

Analysts warn Oracle has limited margin for error. Its free cash flow is tighter than that of larger hyperscalers, and profitability depends on customers monetizing AI faster than history suggests. Any delay in data center deployment or customer revenue could extend the payback period significantly.

Those worries have been compounded by reports of pushed-back data center timelines and a leadership shake-up, with Oracle appointing co-CEOs late in the year.

Still, not everyone is bearish.

Supporters argue Oracle has repeatedly delivered through past technology cycles and can repurpose AI infrastructure if demand shifts. Shares remain up 16% for the year, despite falling more than 40% from their peak.

For investors, Oracle now sits at the center of the AI dilemma: massive opportunity on one side, rising leverage and uncertain demand on the other. How that balance resolves may shape not just Oracle’s future, but sentiment toward the entire AI trade in 2026.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: How Big Tech Created the 2025 AI Boom on Debt

The post How Oracle Became a Test Case for AI Bubble Fears first appeared on Finblog.

AI dominance is masking underlying risk

Mega-cap tech and chip stocks continue to carry an outsized weight in the S&P 500. Their strong performance in 2025 helped offset weakness elsewhere in the market, keeping overall volatility lower than expected. But that balance is fragile.

Strategists warn that any stumble in major AI or semiconductor names could quickly ripple across the broader market and push volatility gauges sharply higher.

“2025 has generally been a year of rotation and narrow leadership, rather than broad risk on or risk off,” said a derivatives strategist at UBS, adding that this has left volatility prone to sudden spikes when macro risks re-enter the picture.

Fear of missing out clashes with bubble anxiety

A recent Bank of America survey shows that bubble risk is now the top concern among global fund managers. At the same time, fear of missing out remains powerful, especially if the AI trade continues to deliver gains into 2026.

This tension is why strategists expect volatility to stay elevated. Asset bubbles tend to become more unstable as they grow, increasing the likelihood of pullbacks larger than 10 percent. However, those declines may be followed by unusually fast rebounds as investors rush back in.

Volatility trades gain favor

At UBS, strategists argue that betting on higher volatility in tech-heavy benchmarks like the Nasdaq 100 could perform well whether AI continues to surge or begins to unwind. Some see buying Nasdaq volatility while selling S&P 500 volatility as one of the most compelling trades for 2026.

Meanwhile, JPMorgan Chase expects the VIX to average around 16 to 17 next year, but with frequent spikes during risk-off episodes driven by macroeconomic shocks, policy uncertainty, or earnings disappointments.

Dispersion and hedging stay in focus

The popular dispersion trade, which bets on higher volatility in individual stocks compared to the index, is expected to remain active, though some investors now warn it has become crowded. Others are adapting by refining stock selection and timing rather than abandoning the strategy altogether.

Across Wall Street, the message is consistent. 2026 is unlikely to be calm. Conflicting AI narratives, lingering FOMO, and growing concern about valuation extremes are creating a market environment where hedging and volatility strategies matter more than simple direction bets.

AI optimism may keep stocks supported, but bubble fears mean investors should expect bigger swings, faster reversals, and more frequent volatility shocks in 2026. Preparing for both upside and downside scenarios is increasingly seen as essential, not optional.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Trade, Tariffs, and Treasuries: The Hidden Cost of Trump’s Protectionism

Big Year for Old School Wall Street Trades Gets Lost in AI Hype

Markets Enter Final Stretch of 2025 With Santa Rally Hopes: What to watch

The post FOMO vs. Bubble Angst Signals More Stock Volatility in 2026 first appeared on Finblog.

The S&P 500 rebounded 0.8% this week, snapping a four day losing streak, while the Nasdaq 100 and big tech stocks led gains after softer inflation data improved expectations for future rate cuts. Historically, markets tend to perform well at this time. Since 1928, the S&P 500 has risen 75% of the time in the final two weeks of December, with an average gain of about 1.3%, according to Citadel Securities data.

At Goldman Sachs, traders say seasonal trends, easing volatility, and cleaner positioning favor upside into year end, even if gains are modest. They argue that without a major shock, it is difficult to fight the positive year end setup.

Options markets support that view. Investors have been buying call spreads on Nvidia, Micron, Broadcom, and tech ETFs, while selling downside protection on mega cap stocks. Citadel Securities notes that retail investors have been net buyers of call options for 32 of the past 33 weeks, reflecting sustained confidence.

Broader flows also remain supportive. About $100 billion has flowed into US equities over the past nine weeks, and investor sentiment tracked by Goldman is at its most bullish level since April. Institutional investors have also increased exposure, branching beyond Big Tech into industrials, real estate, and other cyclical sectors.

While skepticism around AI returns and the Fed’s 2026 rate path persists, many strategists believe cooling inflation, lower volatility, and strong seasonal patterns still provide a credible foundation for a Santa rally, even after an uneven start to December.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: How Big Tech Created the 2025 AI Boom on Debt

The post Why Wall Street Still Believes in a Santa Rally first appeared on Finblog.

Speaking on the Google DeepMind Podcast, Hassabis said some startups are securing tens of billions of dollars in valuation before they have even properly launched, questioning whether such pricing is sustainable. “My guess is probably not,” he said.

He drew a clear line between early AI startups and Big Tech, arguing that companies like Google are investing heavily in AI infrastructure backed by real revenue and business fundamentals.

Hassabis described AI as overhyped in the short term but underappreciated in the long term, adding that major technological shifts often swing from skepticism to obsession, creating bubbles along the way. He said an “over-correction” is likely, calling it a natural response after years of underestimating AI’s potential.

His comments come as scrutiny grows around sky-high AI startup valuations, with young founders raising hundreds of millions of dollars despite limited track records. Veteran investors have echoed similar concerns, warning that many investors are chasing moonshot ideas with no revenues or profits.

Despite the hype, Hassabis said his focus remains on building frontier AI models at DeepMind, rather than worrying about whether the sector is in a bubble.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

Related: Morgan: AI Bubble Or The Start Of A New Tech Era?

Google CEO Sundar Pichai Warns: “No Company Is Immune” If the AI Bubble Bursts

Is Big Tech’s AI Spending Creating a Bubble?

The post Google DeepMind CEO Warns AI Startup Bubble Is Forming first appeared on Finblog.

Oklo’s market value stands at roughly 14 billion dollars despite having zero revenue, an unapproved reactor design, and a recently filed 3.5 billion dollar shelf offering that could heavily dilute shareholders. The company’s application to the Nuclear Regulatory Commission (NRC) was previously denied, and its 1,350 megawatt pipeline remains years away from generating real income.

From Altman Aura to Financial Reality

Oklo’s rise has been fueled largely by two narratives: the global rush for clean energy to power data centers and the Altman premium tied to its high profile backer Sam Altman, who also leads OpenAI. That narrative has now collided with harsh numbers.

After trading as high as 193 dollars in October, the stock has plunged to around 90 dollars following the dilution announcement and weak third quarter results. Investors who once saw Oklo as the AI grid solution are now questioning whether it is closer to a venture experiment than an energy company.

“Oklo has a beautiful concept but no working reactor,” analysts at Trefis wrote. “You are buying a design, not a power plant.”

Behind the Curve

Competitors are moving faster. NuScale Power (NYSE: SMR) already has NRC approval for its VOYGR design. X-energy, backed by Amazon, has secured construction partnerships with Dow Chemical and Energy Northwest. Kairos Power, supported by Google, holds a federal permit for its Hermes demonstration reactor in Tennessee.

By comparison, Oklo’s progress is mostly theoretical. Its agreements with Switch and Equinix are non binding, meaning there are no firm construction commitments.

“The moat here is just Altman’s fame,” said one analyst. “In nuclear energy, fame does not split atoms.”

Regulatory and Financial Pressures

Oklo’s design, called the Aurora reactor, uses liquid metal cooling and recycled fuel, a novel approach that faces stricter licensing hurdles. The NRC denied Oklo’s first application in 2022 for missing information, and while the company has since begun a new pre application process, approval could still take years.

Meanwhile, the company burned 36 million dollars last quarter, with no revenue stream to offset expenses. Its partnership with Siemens Energy to provide turbines offers validation but not cash flow.

Adding to investor anxiety, both CEO Jacob DeWitte and COO sold shares in November, shortly before the new offering. Altman, who previously served as chairman, also stepped down earlier this year.

The Competitive Landscape

• NuScale (SMR) – NRC approved, commercial supply chain in motion
• X-energy – 500 million dollar Amazon investment, firm sites and contracts
• Kairos Power – Google partnership, active construction permit
• Oklo (OKLO) – No revenue, no permit, pending design approval

The Verdict

Oklo remains a visionary company with bold ambitions but faces steep odds. Analysts argue that investors are paying 2030 prices for 2025 execution risk.

“The nuclear renaissance is real,” Trefis concluded. “But Oklo may not be the vehicle to ride it. Buy the companies owning the atoms, not the PowerPoint.”

Stocks to Watch:

• Constellation Energy (NASDAQ: CEG) – profitable nuclear operator powering AI grids
• Cameco (NYSE: CCJ) – uranium producer benefiting from long term demand
• NuScale (NYSE: SMR) – only SMR firm with NRC design approval

Oklo’s vision of powering the AI revolution with mini reactors remains compelling. But until it replaces renderings with reactors, the market seems to be treating it as exactly what Forbes called it, a paper reactor.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

The post Is Oklo A $14 Billion “Paper Reactor” Bubble? first appeared on Finblog.

Related: How Big Tech Created the 2025 AI Boom on Debt

Pichai compared AI to the early internet. There was too much money and hype, but the technology itself was real and changed the world. He says AI looks similar today. There is both logic and madness at the same time.

Worries are growing because investment is running far ahead of revenue. JPMorgan estimates that big tech companies could spend around 5 trillion dollars on AI data centers by 2030. To justify that, annual revenues would need to reach around 650 billion dollars. Right now they are closer to 50 billion dollars. OpenAI alone has signed almost 1.4 trillion dollars of long term infrastructure deals, while expected revenue for 2025 is only about 20 billion dollars.

At the same time, debt is rising fast. Data center debt has jumped more than 18 times since 2022. Some investors, like Michael Burry, say AI infrastructure is being overbuilt and valuations are too high. Others, like Tom Leighton of Akamai, say it feels a bit like the late 1990s internet boom, with real innovation but also inflated prices that will later correct.

JPMorgan is more positive. The bank points out that this time most AI spending is coming from profitable, cash rich companies, not from weak, loss making startups. Tech free cash flow margins are near 20 percent, more than double the dot com era. AI spending is also already turning into real demand for chips, cloud services and software.

In short, many experts think this is not a fake story that will vanish. AI may still have a painful correction in prices and weak players, but the money going into chips, data and models is likely building the base of a new digital economy. The risk for investors is not only that AI is a bubble, but also that they pick the wrong companies in a very big, very real shift.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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The post Morgan: AI Bubble Or The Start Of A New Tech Era? first appeared on Finblog.