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I called Steve Hanke on the afternoon of July 14, days after he\u2019d flagged something he called a dual bubble forming in AI markets, and one day after IBM suffered the worst single-day stock crash in its 115-year history. The \u201cmoney doctor\u201d has been advising governments\u2014including the Treasury Department and the White House\u2014for decades and often writes as a senior contributing columnist for Fortune. He demurred on the mechanics of IBM\u2019s stock, saying he doesn\u2019t follow it closely, but he did say it fit into a large macroeconomic theme.<\/p>\n
\u201cDid you see the bank earnings?\u201d he asked me with astonishment.<\/p>\n
I had. JPMorgan had just posted net income of $21.2 billion\u2014the highest quarterly profit for any bank in U.S. history. Goldman Sachs reported an 84% jump in not earnings attributable to common shareholders, to $6.4 billion, with total revenues hitting $20.34 billion, up 39%. These hit the ticker the same day IBM cratered 25%, erasing roughly $40 billion in market value on a revenue miss that, in any other environment, would have been unremarkable.<\/p>\n
That juxtaposition\u2014banks minting money while IBM suffered a 115-year collapse on a 3.7% revenue miss\u2014is the puzzle at the center of what Hanke, a professor of applied economics at Johns Hopkins, thinks markets are getting dangerously wrong about the AI boom. For two years, investors have been debating whether AI stocks are too expensive. Hanke said that\u2019s true, but it\u2019s the wrong question. \u201cWe really have two bubbles in markets,\u201d he told me. One is a classic valuation bubble of price versus earnings, as exemplified by the famous CAPE Shiller index. But the more dangerous mispricing, he argued, isn\u2019t in valuations at all. It\u2019s in the earnings themselves.<\/p>\n
A modest miss, an unprecedented crash<\/p>\n
IBM\u2019s preliminary second-quarter numbers were unspectacular: revenue of $17.2 billion missed consensus of roughly $17.9 billion by about 3.7%, and adjusted EPS of $2.93 came in under the $3.02 expected. Still, IBM was growing, and this preliminary disclosure alerted investors that revenue has grown by 1%, instead of the 5% expected by the market. The reaction to this was a market selloff\u00a0steeper than Enron\u2019s collapse the day the SEC opened its accounting inquiry.<\/p>\n
IBM CEO Arvind Krishna knew it would be bad, writing an unusually candid letter being open about underperformance. Conditions in the market required \u201cour teams to execute perfectly,\u201d he wrote, \u201cand this quarter we faltered.\u201d His mea culpa offered \u201cnot excuses, but \u2026 realities.\u201d<\/p>\n
The New York Times\u2019 DealBook wondered if the IBM miss was a \u201ccanary in the tech coal mine\u201d and the Financial Times\u2018 west coast editor Richard Waters argued that it was a \u201cwarning to the IT sector,\u201d something like the actual manifestation of the \u201cSaaSpocalypse\u201d that spooked markets earlier this year. That was driven by the theoretical potential of AI to displace traditional software, but IBM\u2019s profit warning appeared to confirm that a secular shift is now under way.<\/p>\n
The thing to understand is that most bubbles throughout market history have been valuation bubbles: prices race ahead of earnings, leaving P\/E ratios that look obviously stretched, as in 2000. An earnings bubble is different and far less common\u2014it\u2019s the profits themselves that are inflated or unsustainable, which can make valuations look deceptively reasonable even while the market is dangerously mispriced. And that\u2019s what IBM seemed to suggest to the market \u2014\u00a0the beginning of the unwinding of the earnings boom.<\/p>\n
BCA Research\u2019s Peter Berezin has been arguing for months that today\u2019s AI trade is \u201cprimarily an earnings bubble rather than a valuation bubble,\u201d and that such bubbles have historically clustered in boom-bust industries: pre-2008 banks, pandemic-era work-from-home stocks, and cyclicals like natural resources, airlines, and semiconductors\u2014the last of which now sits at the center of the AI capex story.<\/p>\n
That rarity matters because earnings bubbles carry a detection problem that valuation bubbles don\u2019t. Analysts typically only cut profit estimates after stocks have already fallen, meaning there\u2019s little early warning. And when they burst, they tend to leave behind real excess capacity\u2014data centers, chip fabs, server farms\u2014rather than just erasing paper gains. Berezin noted in late May that Wall Street analysts are \u201cnot particularly good at predicting when earnings bubbles will burst\u201d because stocks begin falling before profit estimates do.<\/p>\n
IBM\u2019s own earnings reaction bore out that exact detection lag. BofA and UBS both trimmed estimates, but only after the stock had already cratered 25%, with BofA cutting its price target to $280 from $330 and UBS holding its target at $236 while still lowering 2026 EPS forecasts \u2014 reactive moves, not predictive ones. Yet even after the selloff, the Street split sharply on what it meant: BofA kept a Buy rating, arguing IBM remained \u201cwell positioned\u201d once execution issues cleared, while HSBC downgraded to Reduce and Goldman warned the results would \u201cfully validate the software bear case scenario.\u201d<\/p>\n
Which brings Hanke back to the bank earnings. His point wasn\u2019t that JPMorgan\u2019s profits are suspicious\u2014it\u2019s that they are unusual reveal the monetary mechanism that most investors misunderstand. It\u2019s not the Federal Reserve creating the money fueling what he sees as two bubbles; it\u2019s private banks.<\/p>\n
I responded that it reminds me of a famous quote by the great midcentury economist John Kenneth Galbraith: \u201cThe process by which banks create money is so simple that the mind is repelled.\u201d Hanke laughed, while recalling that he only met Galbraith once and agreeing that was what he meant. \u201cAlthough my orientation is not the same as Galbraith\u2019s, I thought he was a great man and had many admirable qualities,\u201d he added. <\/p>\n
I asked him: are record bank profits evidence that credit is still flowing freely through the system, simultaneously inflating asset prices and the reported earnings that justify those prices\u2014right up until something snaps. \u201cWhat you\u2019re saying,\u201d he responded, repeating a phrase that he\u2019s been saying a lot recently, \u201cis that markets are getting mugged by reality.\u201d<\/p>\n
Even JPMorgan CEO Jamie Dimon seems to agree, crowing that the earnings were \u201cclose to as good as it gets\u201d on a call with analysts on Tuesday, before expressing concern at too much \u201cexuberance\u201d in markets. Like Hanke, Dimon has been saying for months that markets may be a bit too exuberant. <\/p>\n
The misdiagnosis<\/p>\n
If Hanke and Berezin are right, the market has spent two years watching the wrong gauge. The bull case has rested on the observation that today\u2019s AI leaders\u2014Nvidia, Alphabet\u2014generate real cash flow, unlike the profitless dot-com names of 2000, with S&P 500 valuations near 22x forward earnings, below the 25x-plus threshold usually associated with true bubbles. That defense addresses the valuation side. It says nothing about whether the earnings themselves\u2014swelled by capex cycles, circular AI investment and easy money from private banks\u2014are sustainable.<\/p>\n
IBM\u2019s crash may be the first visible crack not in valuations but in the earnings story underneath them: a company whose numbers weren\u2019t that bad still got punished as if the market suddenly stopped believing the profit growth narrative altogether. Whether that\u2019s a single-stock anomaly or a signal that the market has quietly repriced its tolerance for earnings disappointment across the sector is the question the rest of earnings season will start to answer.<\/p>\n
For now, the more dangerous question may have been hiding in plain sight the entire time\u2014not whether AI stocks are too expensive, but whether the earnings behind them were ever as real as they looked.<\/p>\n
IBM shares were down 2% in intraday trading as of press time.<\/p>\n
#IBM #suffered #worst #stock #crash #timeand #markets #dual #bubble<\/p>\n","protected":false},"excerpt":{"rendered":"
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