What is Yardeni Research’s latest assessment of the AI market?
Yardeni Research has identified bubble-like conditions in artificial intelligence-related equities but says the financial factors that have preceded previous market downturns are not yet sufficiently widespread to indicate an imminent reversal.
The firm’s assessment is based on a newly developed AI Bubble Meter, created using Anthropic’s Claude Fable 5.1 model.
The indicator compares current market conditions with historical episodes of speculative investment, including the technology boom that ended in 2000 and the US housing expansion that reversed in 2006–2007.
According to Yardeni Research, the tool currently indicates that a bubble exists, although the factors associated with its potential collapse remain comparatively limited.
What does the new AI Bubble Meter measure?
The model separates market conditions into two categories.
The first, Conditions, evaluates whether the characteristics associated with previous financial bubbles are present.
The second, Triggers, examines developments that could bring a speculative expansion to an end, particularly rising financing costs and excessive credit growth.
Yardeni Research reported a Conditions score of 83 out of 100, compared with a Triggers score of 34.
The difference between the readings suggests that although AI-related market valuations display characteristics associated with previous bubbles, the broader financial pressures that contributed to earlier downturns are not yet fully established.
Which financial risks have started to emerge?
One development identified by the firm is the increase in the yield on the two-year US Treasury note.
The yield has risen 115 basis points from its December low, indicating higher short-term borrowing costs.
Yardeni Research is comparing that increase with the rises of approximately 200 to 350 basis points recorded before the reversals associated with the technology bubble in 2000 and the housing bubble in 2006.
The firm also noted that credit conditions outside AI-related activities have not shown the same degree of expansion associated with previous speculative cycles.
“The preconditions of a bubble are in place and have been for a while, but the forces that ended past booms are only partially present,” Yardeni Research said.
What does the historical evidence show?
Yardeni Research examined market data dating back to 1965 to assess the relationship between its indicators and subsequent S&P 500 performance.
When Conditions readings were high but Triggers readings remained low, a bear market followed within two years in 9% of the historical periods examined.
The S&P 500 recorded a median inflation-adjusted return of 18.3% over the following two years during those periods.
When both indicators were elevated, the historical incidence of a bear market within two years increased to 42%.
Those periods were also associated with a median inflation-adjusted market decline of 12.5%.
The findings illustrate how the model distinguishes between speculative market conditions and the financial developments that have historically accompanied significant corrections. They do not establish the probability of a future downturn.
Why is the Triggers reading particularly important?
Yardeni Research considers the Triggers indicator relevant to assessing whether current conditions are becoming more similar to those observed before earlier market reversals.
The firm said:
“But the Triggers dial is the one to watch: If it starts rising toward High, so do the risks.”
Further increases in Treasury yields, particularly alongside signs of excessive credit expansion, could affect the indicator’s assessment.
The current Triggers score of 34 remains below the Conditions reading of 83, indicating a difference between the presence of bubble characteristics and the development of potential catalysts for a correction.
What role will upcoming AI company earnings play?
Yardeni Research also intends to review third-quarter financial reports from major hyperscale computing companies for indications of unused infrastructure capacity.
The analysis will focus on whether investment in AI computing facilities is being matched by demand for the services those facilities provide.
Evidence of excess capacity could become relevant to assessments of the sustainability of capital spending across the sector.
For the time being, the firm’s AI Bubble Meter identifies elevated speculative conditions without showing the same level of financial triggers associated with previous major market downturns.
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