The AI chip rally is exhibiting historic market spreads, surpassing infamous bubbles like the 1720 Mississippi Bubble and the 2000 dot-com crash, according to Bank of America strategists. While some economists warn of a trillion-dollar bubble, others argue that such ‘bubbles’ are often a necessary phase for transformative technologies, pointing to strong, materializing cloud revenues from tech giants like Alphabet, Amazon, and Microsoft. However, concerns persist about increasing market concentration in AI stocks, suggesting a potentially narrow base for broader equity gains.
The artificial intelligence rally has reached historic proportions, prompting comparisons to some of history's most infamous financial bubbles. According to Michael Hartnett, a strategist at Bank of America, the SOX semiconductor index's peak price currently stands 62% above its 200-day moving average. This spread is more than double that seen in the Dow Jones Industrial Average prior to Black Monday in 1987 and Black Tuesday in 1929.
The current spread closely mirrors the Nasdaq's 55% margin preceding the dot-com crash in 2000, a period defined by skyrocketing valuations for companies with unproven paths to profitability. Remarkably, the AI chip surge even approaches the 73% spread observed in the French CAC All Tradable index before the bursting of the Mississippi Bubble in 1720, an event that saw the problematic French colonial Mississippi Company's shares used as legal tender, leading to a doubling of France's money supply.
Hartnett mused on the current market environment: "Exponential price action, market concentration, collapsing vol, stocks bossing bond yields higher, why melt-up everyone's new base case … Here we go." Since late March, AI stocks, including chipmakers like Micron, Advanced Micro Devices, SK Hynix, Marvell, and Intel, have exhibited unusual "parabolic" price chart contours.
Many economists are convinced that the massive investment flowing into AI, which multiple Wall Street banks predict will exceed $1 trillion next year, signifies a bubble. Ann Pettifor, director of the Policy Research in Macroeconomics organization, noted to CNBC that "Having to amass more than a trillion dollars in cash to support the investment … has led to what everybody talks about as a bubble."
However, not all commentators are equally alarmed by the scale of the AI build-out. Robin Wigglesworth of the Financial Times likened it to "a tiny little gnat on the arse of an elephant compared to the railway boom" of the 1860s. He highlighted that when adjusted for inflation and scaled to GDP, the railway boom involved bond issuance equivalent to $10 trillion today, far surpassing current total AI debt, as per a JPMorgan analysis.
Other experts acknowledge the likelihood of a bubble without undue concern, framing it as a natural phase for transformative technologies. Author Derek Thompson, in a column referenced by Oaktree Capital Management co-founder Howard Marks, wrote, "The railroads were a bubble and they transformed America. Electricity was a bubble, and it transformed America. The broadband build-out of the late-1990s was a bubble that transformed America." He added, "It's unlikely that AI will be the first transformative technology that isn't overbuilt and doesn't incur a brief painful correction."
Despite the substantial debt and complex conduit financing methods used to keep it off balance sheets, actual AI revenues are indeed materializing. Alphabet reported a 63% annual jump in first-quarter cloud revenue, while Amazon's AWS cloud unit achieved 28% revenue growth, reaching $37.59 billion. Microsoft's cloud revenue increased by 40%, with its Azure-inclusive division reporting $34.68 billion. These strong figures provide some reassurance to the broader equity market.
Nevertheless, market gains are becoming increasingly concentrated in semiconductors and AI infrastructure stocks, potentially indicating a weak foundation for the overall equity boom. Piper Sandler noted a "stark divergence" in the advance-decline line as the S&P 500 reaches record highs, signaling that leadership has become more concentrated, primarily in technology, according to Craig Johnson.
