Recently, the S&P 500 index has repeatedly hit new all-time closing levels along the upward channel, with nine consecutive daily gains and a rare nine-week streak of weekly increases. Beneath the seemingly strong market performance, the internal structural divergence is reaching decades-high levels.
Relying on the momentum of AI industry prosperity and leading stocks forming concentrated positions, the market has experienced abnormal rises detached from most individual companies' fundamentals. Several major overseas institutions issued warnings from three dimensions: market breadth, sector differentiation, and historical valuation patterns—indicating that the extreme weighting of top stocks is unsustainable. Once the AI trend wanes, even if small and mid-cap stocks recover collectively, they will struggle to offset the downward pressure on the index. The current bull market's inflection point is most likely to occur in June.
From micro-level market data, the abnormal inversion of advancing and declining stocks has become a normalized feature of the current U.S. stock market. Data from Dow Jones shows that the S&P 500 has experienced six consecutive trading days of divergence—index closing higher while individual stocks mostly decline—with the number of declining stocks each day exceeding those advancing.
BTIG's Chief Market Technician Jonathan Krinsky’s analysis of historical data since 1996 indicates that in past bull cycles, such extreme divergence lasted at most three trading days. A six-day streak is unprecedented in market history, visually confirming that the index's rise has long been detached from overall market fundamentals and is fully driven by a handful of top-weighted stocks.
Rob Anderson, strategist at Ned Davis Research, further supports this view with social media statistics: the proportion of stocks outperforming the S&P 500 benchmark in the past two months hit the third-lowest level since 1972, indicating that the structural divergence in the U.S. stock market is among the most severe in half a century. Extreme concentration of holdings is a core factor behind the collapse of market breadth.
Currently, in the S&P 500, a few tech giants led by information technology have seen their weights surge to nearly 40%, setting a record since the index's inception. The top ten stocks now account for 40% of the total market capitalization, with ongoing capital inflows focusing on AI computing power and software leaders, squeezing other sectors’ allocation space due to the siphoning effect of existing funds.
Over the past five trading days, sector data clearly reveal divergence: only technology and energy sectors posted positive returns, with technology soaring 5.9% in a single cycle, becoming the sole pillar of the rally, while energy rose only slightly by 0.3%. Meanwhile, defensive sectors like real estate, utilities, and communication services all fell more than 3%, and many cyclical and consumer stocks continued to decline, creating a stark contrast between market prosperity and sector depression.
During the upward phase of the concentration rally, the market cap advantage of leading stocks can offset the drag from declines in small and mid-cap stocks, forming a unique pattern where a few stocks support the entire market index. However, this logic is inherently fragile.
Krinsky’s latest report warns that such highly concentrated holdings pose a risk of reverse triggering: if profit expectations for the AI sector cool down and funds start to exit, the leading stocks will end their unilateral rise, and a concentrated sell-off could break the index support. Unlike a diversified bull market, in this cycle, rebounds in small and mid-cap stocks are unlikely to offset losses from top stocks, increasing the risk of a divergence where “most stocks rise while the index falls.” June could be a critical window for a trend reversal.
Ignoring the AI industry’s benefits and the temporary disruptions caused by Middle East geopolitical conflicts, the S&P 500 has gained over 16% in the past two months, ranking among the fastest post-WWII rallies. Market analysis warns that historical data signals potential risks: only four periods in post-war history have seen similar gains, three of which occurred during economic recovery phases after recessions—such as the end of the 1970s oil crisis, the 2008 subprime crisis bottom, and the post-2020 COVID-19 recovery. The only rapid surge outside recession recovery was just before the 1987 Black Monday crash, with overlapping historical cycles raising valuation concerns.
Reviewing the 1987 crash environment, by late September, the S&P 500 had already gained 36.2% for the year, with rapid valuation bubbles forming. The Fed was in a rate-hiking cycle, compounded by U.S. trade and fiscal deficits, which heightened market risk appetite. Multiple negative factors triggered a single-day plunge.
In comparison, current fundamentals show that the Fed’s monetary policy path, global inflation fluctuations, and U.S. fiscal deficits continue to influence market pricing. The valuation premiums driven by AI concepts have diverged from some companies’ earnings, and the value of historical reference points remains high.
Looking at macro variables in June, historical patterns suggest that this month often sees many events—such as Fed meetings, key employment and inflation data, and quarterly guidance from leading companies—that can trigger a break in the current concentration. Many institutions believe that if the Fed delays rate cuts, high-valuation AI leaders will be the first to see valuation compression, causing the index rally supported by heavyweights to weaken rapidly. Even if small and mid-cap stocks benefit from low valuations and recover, limited overall market funds and the disproportionate weight of top stocks mean that local rebounds cannot reverse the overall downward trend.
From a global asset allocation perspective, the warning signals of this U.S. structural bull market extend beyond domestic markets. In an environment of converging global liquidity and increasing divergence in asset valuations, index overvaluation driven by sector concentration often harbors tail risks. Cross-border equity investors should abandon the mindset that “new highs mean a strong market,” look beyond index levels, and focus on three core indicators: market breadth, concentration of holdings, and earnings realization, remaining alert to systemic risks from AI sector corrections in June. $US500500

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