BofA Warns AI Stock Bubble Nears Historic Dot-Com Extremes
0h ago|4 min readStandard
Fazen Markets Editorial Desk
Collective editorial team · methodology
ai-stocksstock-bubblemarket-sentimentdot-com-bubble
Fazen Markets Editorial Desk
Collective editorial team · methodology
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Bank of America's investment strategy team issued a warning on 24 May 2026 that the fervor around artificial intelligence stocks is approaching historic bubble measurements last seen during the 1999 dot-com era. The bank's proprietary Bull & Bear Indicator, which tracks market sentiment extremes, surged to 7.7 out of a maximum 10. This level is in the 93rd percentile of all readings since 1986, signaling extreme bullishness typically preceding market corrections. The indicator's rise was triggered by soaring flows into AI-focused equity funds and a high concentration of outperformance in a narrow cohort of mega-cap technology stocks.
The Bull & Bear Indicator’s current level matches the 7.7 reading from February 2020, just prior to the COVID-19 market crash. The last time it reached a higher level was in March 2013 at 8.1, following aggressive quantitative easing. The current macro backdrop features a 10-year Treasury yield at 4.2% and the Federal Reserve holding its benchmark rate at 5.25-5.50%, creating a high hurdle for speculative equity valuations. The catalyst for the extreme reading is a multi-month rally concentrated in AI-leveraged stocks, which has pushed the cumulative year-to-date performance of the "Magnificent 7" tech giants to over 30%, far outpacing the broader S&P 500's 8% gain. Investors are chasing growth narratives amid plateauing corporate earnings outside the AI supply chain.
The Bull & Bear Indicator comprises eight metrics, with four flashing clear warning signs. Fund flows into tech and growth equity funds hit $12.4 billion in the week ending 23 May, the largest weekly inflow since November 2021. The ratio of stocks trading above their 50-day moving average has exceeded 80% for five consecutive weeks. The market capitalization of the AI thematic universe, tracked by indices like the Global X Robotics & Artificial Intelligence ETF (BOTZ), ballooned to over $4 trillion, a 150% increase from its 2022 low. The average price-to-sales ratio for the top 10 AI-focused stocks now stands at 25, compared to a 20-year average of 8 for the technology sector.
| Metric | AI Stock Cohort | S&P 500 Index |
|---|---|---|
| YTD Return | +45% | +8% |
| Forward P/E Ratio | 38x | 20x |
| 30-Day Volatility | 32% | 15% |
The performance divergence is stark. While the S&P 500 Information Technology sector rose 28% year-to-date, the equal-weight version of the same index gained only 5%, highlighting the dominance of a few large-cap leaders.
The immediate second-order effect is a rotation pressure away from speculative AI software names and toward value and defensive sectors. Stocks like NVDA and AMD may see heightened volatility, while beneficiaries include consumer staples PG and utilities XLU, which offer stable dividends. Semiconductors with less pure AI exposure, such as INTC, could underperform their peers. A key risk to this analysis is that genuine, transformative AI productivity gains could justify current premiums over a longer horizon, invalidating bubble comparisons. Hedge fund positioning data shows a net short bias on the NYSE FANG+ Index while retail options flow remains heavily bullish on single-stock AI names, setting up a potential clash.
Key catalysts that could deflate or validate the AI rally include the Federal Reserve's policy decision on 18 June and Q2 2026 earnings season starting 14 July, where AI revenue guidance will be scrutinized. Technical levels to monitor include the 50-day moving average for the Nasdaq-100 Index at 18,500; a decisive break below could trigger systematic selling. The 10-year Treasury yield breaching 4.5% would pressure high-multiple growth stocks disproportionately. The market's reaction to any downward revision in AI chip demand forecasts from major foundries like TSMC will serve as a critical stress test for the sector's valuation foundation.
The 1999 bubble was characterized by retail investors flocking to unprofitable internet companies with no revenue, while today's AI rally is concentrated in large, profitable firms like Nvidia with massive actual sales. However, valuation metrics like price-to-sales ratios are reaching similar historic extremes. The 1999 Nasdaq Composite forward P/E peaked above 100, whereas today's AI leaders trade at a forward P/E near 40, suggesting froth but not the same level of speculative insanity.
For long-term investors, extreme sentiment readings historically signal poor near-term returns but do not negate a long-term thesis. The indicator is a timing and risk-management tool, not a fundamental sell signal. Historical data shows that after the indicator crosses 7.0, the S&P 500's average 12-month forward return is approximately 5%, below its long-term average of 10%. This suggests moderating return expectations and potentially rebalancing portfolios away from the most crowded trades.
The two most stretched metrics are hedge fund positioning, which shows them at their most net long in two years, and equity fund flows, which are at near-record levels. These are classic signs of capitulation by previously skeptical professional investors and peak enthusiasm by retail investors. Combined with elevated valuations, this creates a scenario where most bullish participants are already invested, leaving few new buyers to push prices higher.
Extreme market sentiment suggests the AI stock rally is maturing and faces a high risk of a significant correction.
Disclaimer: This article is for informational purposes only and does not constitute investment advice. CFD trading carries high risk of capital loss.
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