{"id":164784,"date":"2026-05-13T05:05:22","date_gmt":"2026-05-13T05:05:22","guid":{"rendered":"https:\/\/mycryptomania.com\/?p=164784"},"modified":"2026-05-13T05:05:22","modified_gmt":"2026-05-13T05:05:22","slug":"how-far-is-the-stock-market-from-a-bubble-breaking-down-the-real-risks-of-this-ai-bull-run","status":"publish","type":"post","link":"https:\/\/mycryptomania.com\/?p=164784","title":{"rendered":"How Far Is the Stock Market From a Bubble? Breaking Down the Real Risks of This AI Bull Run"},"content":{"rendered":"

Bitbaby Research<\/strong> | May 13, 2026 | 12 min\u00a0read<\/p>\n

How Does This Rally Compare Historically?<\/strong><\/p>\n

Dalio studied 10 major market bubbles. Average duration: 2.5 years. Average gain:\u00a0244%.<\/p>\n

This rally started in late 2022. We\u2019re in year three. S&P 500 up 79%. Nasdaq 100 up\u00a0130%.<\/p>\n

Duration: past the historical average. Magnitude: not there\u00a0yet.<\/p>\n

But one number has no historical precedent: the top five companies now account for nearly 30% of the S&P 500. One bad earnings report from any of them moves the entire\u00a0index.<\/p>\n

How Close Are We to\u00a02000?<\/strong><\/p>\n

Buffett Indicator 221%: measures total stock market cap relative to GDP. It has crossed 200% exactly once before\u200a\u2014\u200aearly 2000, right before the bubble burst. Now at 221%, an all-time\u00a0high.<\/p>\n

Shiller CAPE 39.7: inflation-adjusted P\/E using 10-year average earnings. In 150 years of data, only the dot-com peak in 2000 (44.2) has been higher. Currently the second-highest reading ever recorded.<\/p>\n

The difference from 2000: companies this time have real revenue and are investing from earnings, not debt. That\u2019s JPMorgan\u2019s argument for why this isn\u2019t a bubble. But the Buffett Indicator is already higher than it was in 2000. The Shiller CAPE is 4.5 points away from matching\u00a0it.<\/p>\n

Grantham (GMO) puts the probability of a bubble burst at \u201cclose to 100%,\u201d comparing AI to the 1840s railway bubble\u200a\u2014\u200arailways changed the world, but most railway investors lost everything. JPMorgan says not a bubble. Dalio puts it most precisely: AI euphoria is at roughly 80%<\/strong> of the levels seen before 1929 and 2000. He doesn\u2019t recommend selling, but warns to expect low\u00a0returns.<\/p>\n

Who Is Actually Winning This\u00a0Rally<\/strong><\/p>\n

The big winners in this rally aren\u2019t AI application companies, and they aren\u2019t the Big Tech companies spending the money, they\u2019re the infrastructure supply\u00a0chain.<\/p>\n

NVIDIA is up over 450% in two years. Broadcom, TSMC, and ASML followed. Power and cooling company Vertiv more than doubled. Data center REITs\u00a0surged.<\/p>\n

NVIDIA converts those purchase orders into earnings. The stocks going parabolic are AI infrastructure suppliers\u200a\u2014\u200anot AI\u00a0itself.<\/p>\n

The core risk: NVIDIA\u2019s 53% growth rate isn\u2019t something NVIDIA controls. It\u2019s determined by whether the four big buyers keep spending.<\/strong> If they pull back, the assumptions under a 43x P\/E are\u00a0gone.<\/p>\n

Why the Math Doesn\u2019t Work\u00a0Yet<\/strong><\/p>\n

Two specific calculations:<\/p>\n

Goldman Sachs:<\/strong> To maintain the returns on capital investors expect, these companies need to generate $1 trillion in annual profit from AI. Wall Street\u2019s current consensus estimate is $450 billion. The gap is more than\u00a0double.<\/p>\n

Sequoia Capital:<\/strong> Take NVIDIA\u2019s revenue, double it for data center operating costs, double again for end-user profit margins. That\u2019s $600 billion\u200a\u2014\u200athe annual revenue the AI industry needs to justify current infrastructure spending. Total AI industry revenue right now? About $100 billion. A 6x\u00a0gap.<\/p>\n

What\u2019s driving continued investment isn\u2019t ROI\u200a\u2014\u200ait\u2019s FOMO. Fear that competitors will invest and you won\u2019t. Same psychology as the late-stage dot-com bubble: not investing because returns are visible, but because stopping feels more dangerous than continuing.<\/p>\n

Five Indicators Worth\u00a0Watching<\/strong><\/p>\n

Earnings Growth: Market is discounting it<\/strong><\/p>\n

NVIDIA\u2019s projected 53% annual growth makes 45x P\/E look reasonable. But the stock is up just 15% this year, vs. +450% over the prior two. The market is saying: growth is real, but the most profitable stretch is already priced\u00a0in.<\/p>\n

Earnings Quality: Diverging<\/strong><\/p>\n

Google Cloud: 48% growth, rewarded. Microsoft: $150B on infrastructure, market skeptical about utilization. Same AI narrative, opposite verdicts\u200a\u2014\u200aclassic late-cycle behavior.<\/p>\n

Valuations: One assumption holding it all\u00a0up<\/strong><\/p>\n

NVIDIA at 43x, below the semiconductor average of 46x\u200a\u2014\u200alooks fine. But it assumes Big Tech keeps spending at current rates. If growth slows from 53% to 30%, 43x gets expensive fast.<\/p>\n

Cash Flow: Yellow\u00a0flag<\/strong><\/p>\n

Amazon FCF down 71%. Meta projected down 90%. Earnings being consumed by buildout, not returned to shareholders. If AI revenue doesn\u2019t materially improve before 2027, spending cuts become inevitable.<\/p>\n

Interest Rates: Working against\u00a0them<\/strong><\/p>\n

The Fed says inflation hasn\u2019t come down enough. Rate cuts slower than expected. Higher rates increase the cost of every capex dollar being deployed.<\/p>\n

Fidelity\u2019s read: no systemic crash signals yet, but cash flow is flashing\u00a0yellow.<\/p>\n

Other Signals Flashing Simultaneously<\/strong><\/p>\n

Beyond Fidelity\u2019s framework, a string of independent indicators are lighting up at the same\u00a0time:<\/p>\n

Moody\u2019s AI recession model: 49%.<\/strong> Historically, crossing 50% means recession within 12 months. One point\u00a0awayVIX at 27.<\/strong> Nasdaq in correction territory. S&P 500 below 200-day moving\u00a0averageBank of England<\/strong> publicly warned of correction risk, naming AI stocks specificallyBIS<\/strong> warned AI amplifies the speed and complexity of financial stability risks, with concentration as the core\u00a0concernTop 5 companies = ~30% of S&P 500.<\/strong> Highest in half a century. One bad earnings report moves the entire\u00a0index<\/p>\n

None of these individually proves a crash. But the last time they all activated simultaneously was\u00a02000.<\/p>\n

If It Pops, How Does It\u00a0Pop?<\/strong><\/p>\n

Regulatory intervention.<\/strong> Governments restrict AI capital deployment or data usage, compressing growth expectations directly.<\/p>\n

Market saturation.<\/strong> Enterprises find AI produces little return and start cutting purchases. With 95% currently reporting zero ROI, this path has the highest probability if nothing\u00a0changes.<\/p>\n

Economic downturn.<\/strong> AI doesn\u2019t need to fail on its own merits. A broader recession means budget cuts, and the first thing to go is investment that hasn\u2019t produced returns\u00a0yet.<\/p>\n

One risk fewer people are talking about: NVIDIA sells chips to Microsoft, Microsoft invests in OpenAI, OpenAI runs on Azure, Meta and Google are simultaneously NVIDIA\u2019s largest customers. A problem at any one node propagates along the supply chain\u200a\u2014\u200athe same dependency structure that made 2008 so\u00a0severe.<\/p>\n

Oliver Wyman quantified the worst case: an AI equity bubble burst could erase $33 trillion<\/strong> in market value. Over $1 trillion in AI-related debt sits in private credit\u200a\u2014\u200aopaque, off-balance-sheet structures where banks may be underestimating their exposure.<\/p>\n

Three Conditions to\u00a0Track<\/strong><\/p>\n

The top can\u2019t be predicted. But three preconditions can be tracked. When all three show up together, start paying attention:<\/p>\n

Big Tech starts cutting AI capex guidance.<\/strong> Currently: not happening. All four still increasingMoody\u2019s recession model crosses 50%.<\/strong> Currently: 49%AI companies begin failing at scale.<\/strong> Currently: isolated\u00a0cases<\/p>\n

Right now: somewhere between 0\/3 and\u00a01\/3.<\/p>\n

The distance between 49% and 50% might be one jobs\u00a0report.<\/p>\n

To track this yourself:<\/p>\n

Capex direction:<\/strong> Quarterly earnings capex guidance\u200a\u2014\u200afocus on Amazon and MicrosoftRecession probability:<\/strong> Moody\u2019s AI recession model, NY Fed probability modelValuation levels:<\/strong> Shiller CAPE, Buffett IndicatorMarket temperature:<\/strong> VIX, S&P 500 vs. 200-day moving\u00a0averageBTC linkage:<\/strong> BTC\u2013S&P 500 rolling correlation (above 0.6 = elevated spillover risk)<\/p>\n

This article does not constitute investment advice. All data from public\u00a0sources.<\/em><\/p>\n

Sources:<\/strong><\/p>\n

Goldman Sachs, Tracking Trillions<\/em> & Why AI Companies May Invest More than $500 Billion in\u00a02026<\/em>Goldman Sachs \/ Fortune, *FOMO has proven a stronger incentive than poor stock performance*, May\u00a02026Sequoia Capital, AI\u2019s $600 Billion\u00a0Question<\/em>GMO (Jeremy Grantham), *Valuing AI: Extreme Bubble, New Golden Era, or Both*, Jan\u00a02026Ray Dalio \/ Fortune, *AI is in the early stages of a bubble*, Jan\u00a02026Fidelity, *Is AI a bubble? 5 signs to watch for*,\u00a02026Yale SOM (Jeffrey Sonnenfeld), This Is How the AI Bubble\u00a0Bursts<\/em>Oliver Wyman, *How An AI Bubble Burst Could Shake Global Financial Markets*, Jan\u00a02026BIS, *The financial stability implications of artificial intelligence*, Jan\u00a02026CNBC, Tech AI spending approaches $700 billion<\/em> \/ Big Tech capex topping $1 trillion in\u00a02027<\/em>Bitfinex, AI, Repricing Risk and the Outlook for Bitcoin in\u00a02026<\/em>CME Group, Why is Bitcoin Moving in Tandem with Equities?<\/em>Phemex, Bitcoin-S&P 500 Correlation Hits\u00a094%<\/em>Master of Code, AI ROI: Why Only 5% of Enterprises See Real Returns in\u00a02026<\/em><\/p>\n

How Far Is the Stock Market From a Bubble? Breaking Down the Real Risks of This AI Bull Run<\/a> was originally published in Coinmonks<\/a> on Medium, where people are continuing the conversation by highlighting and responding to this story.<\/p>","protected":false},"excerpt":{"rendered":"

Bitbaby Research | May 13, 2026 | 12 min\u00a0read How Does This Rally Compare Historically? Dalio studied 10 major market bubbles. Average duration: 2.5 years. Average gain:\u00a0244%. This rally started in late 2022. We\u2019re in year three. S&P 500 up 79%. Nasdaq 100 up\u00a0130%. Duration: past the historical average. Magnitude: not there\u00a0yet. But one number […]<\/p>\n","protected":false},"author":0,"featured_media":164785,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-164784","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-interesting"],"_links":{"self":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/164784"}],"collection":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=164784"}],"version-history":[{"count":0,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/posts\/164784\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=\/wp\/v2\/media\/164785"}],"wp:attachment":[{"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=164784"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=164784"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mycryptomania.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=164784"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}