Market Metrics Suggest the AI Bubble Has Not Reached Peak Stage

TLDR:

Table of Contents

Search trends show persistent fear around the AI bubble, which historically appears during early expansion phases.
Nasdaq returns and valuations remain far below dot-com extremes, signaling a cycle that has not reached mania.
Rising margin debt indicates leverage growth, a pattern seen before peaks rather than during collapses.
Market gains remain concentrated in mega-cap stocks, not broad participation typical of bubble finales.

The debate over an AI bubble has intensified as technology stocks continue to dominate market performance. New research shared by Bull Theory argues that current conditions do not match historical patterns seen at major market peaks.

Instead, indicators point to an expansion phase rather than an imminent collapse. The analysis draws on valuation metrics, liquidity trends, and long-term bubble cycles.

AI Bubble Signals Show Fear and Concentration, Not Euphoria

Bull Theory reports that search activity for the phrase “AI bubble” remains elevated on Google Trends. High search interest reflects widespread concern rather than widespread confidence.

Historical market cycles show that bubbles tend to peak when public attention fades and belief becomes absolute. Current search behavior suggests the opposite phase, where fear and skepticism remain dominant.

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— Bull Theory (@BullTheoryio) February 8, 2026

Nasdaq performance also differs from past mania periods. Over the last five years, the index has risen about 88 percent, far below the twelvefold surge recorded during the dot-com era.

Valuation data supports this comparison. Dot-com Nasdaq price-to-earnings ratios reached roughly 60, while today’s Nasdaq trades near 26, according to market datasets cited by Bull Theory.

Market breadth further weakens the bubble argument. The S&P 500 equal-weight index has gained only about 10 percent over the past year, showing that gains concentrate in a small group of mega-cap firms.

Nvidia, Apple, Microsoft, Google, and Amazon account for most of the rally. Previous bubble peaks required broad participation across sectors and stocks.

Volatility indicators also signal caution. VIX spikes accompany most market pullbacks, and options data shows consistent demand for downside protection.

These patterns reflect defensive positioning rather than the low-volatility environment typical of late-stage speculative peaks.

Liquidity and Leverage Data Point to Ongoing Expansion Phase

Margin debt has climbed to about $1.1 trillion, the highest level on record. Bull Theory notes that past bubbles burst only after leverage began to contract sharply.

At present, leverage continues to rise alongside market funding activity. This trend aligns with earlier phases of historical bubbles rather than final stages.

Macro liquidity conditions also remain supportive. Central bank actions in the United States, Japan, and China have injected capital into global markets, sustaining risk appetite.

U.S. fiscal projections show federal debt rising toward $50 trillion by the end of the decade. Large-scale spending typically increases liquidity across financial systems.

Sentiment indicators show division rather than certainty. Retail traders respond to every correction with increased put option activity, while institutional investors remain cautious.

Bull Theory links this environment to the period between early warnings and the eventual peak seen in prior cycles. During the dot-com era, warnings surfaced in 1997, while the market topped in 2000.

A similar pattern appeared before the housing crash, with alerts years ahead of the final breakdown. The firm places current AI-related warnings in a comparable timeline window.

Corporate earnings also support the present valuation structure. Revenue growth from firms like Nvidia and Microsoft continues to justify capital inflows tied to artificial intelligence infrastructure.

Data from Nasdaq, Google Trends, and margin accounts collectively show a market still building momentum. The research concludes that present conditions reflect acceleration rather than exhaustion.

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