In the seven trading days through June 25, the Dow Jones Industrial Average rose 0.5%, while the Nasdaq Composite fell 5%, triggering an extremely rare market statistical event since 1971. Mark Hulbert, columnist for MarketWatch and founder of Hulbert Ratings, said that whenever a divergence of this magnitude occurs, the probability of the U.S. stock market entering a bear market within the next three months is 66.9%.
Specific Data and Statistical Thresholds of the Market Divergence
Data for the seven trading days through June 25, 2026, are as follows:
Dow Jones Industrial Average: Cumulative increase of 0.5%
Nasdaq Composite: Cumulative decline of 5.0%
Spread between the two: 5.5 percentage points
Historical Frequency: Since 1971, a gap of this magnitude has been seen in only about 1% of trading days
Statistical Classification: Hulbert describes it as a statistical extreme event approaching "three sigma"
Same Statistical Characteristics Seen Before the 2000 Dot-Com Bubble
In his analysis, Hulbert provided a historical reference: In the 10 trading days before the Nasdaq peaked in March 2000, seven saw divergences between the Dow and Nasdaq of a magnitude comparable to or greater than the current one. The subsequent bear market saw the Nasdaq Composite fall nearly 80%.
Hulbert also noted that not all similar divergences directly trigger a bear market, but the 2000 case is the most typical historical precursor for this type of signal, highly similar in statistical characteristics to the current one.
Hulbert's Three-Month Bear Market Probability Statistics and Market Breadth Discussion
According to Hulbert's statistics on complete market data since 1971, after a divergence between the Dow and Nasdaq of a similar magnitude, the historical probability of the U.S. stock market entering a bear market within three months is 66.9%, nearly three times the historical average of 24.8%.
Hulbert pointed out that a healthy bull market should be driven by multiple sectors, not just a few traditional blue-chip stocks supporting the index. If tech stocks continue to weaken while the Dow remains strong, this divergence itself is a statistical signal of internal market weakness.
Hulbert also emphasized that historical statistics reflect probability, not certainty. The current signal indicates rising market risk, but it does not constitute a judgment that a bear market is inevitable.
Frequently Asked Questions
How rare is the current divergence between the Dow and Nasdaq statistically?
In the seven trading days through June 25, 2026, the Dow rose 0.5% and the Nasdaq fell 5.0%, creating a gap of 5.5 percentage points. Statistics from Hulbert Ratings show that a gap of this magnitude has occurred in only about 1% of trading days since 1971, with Hulbert classifying it as a statistical extreme event approaching "three sigma."
What data is Hulbert's 66.9% bear market probability based on?
Hulbert's statistics are based on complete market data since the Nasdaq's inception in 1971, calculating the frequency of bear markets occurring within three months after a divergence of similar magnitude. The historical average is 24.8%, while the probability after a similar divergence is 66.9%—nearly three times the average. Hulbert himself explicitly states that this is a statistical probability and does not constitute a judgment that a bear market is inevitable.
Under what conditions is the historical comparison to the 2000 dot-com bubble applicable?
Hulbert cites the 2000 case because its statistical characteristics are highly similar to the current signal: in the 10 trading days before the Nasdaq peaked, seven showed divergences of similar magnitude. Hulbert also notes in his analysis that not all similar divergences directly trigger a bear market; the historical comparison reflects statistical patterns, not an inevitable outcome.
