S&P 500 bull run faces valuation and policy tests as 2026 rally hits turbulence

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S&P 500 bull run tests

Highlights

S&P 500 annualized total return for 2026 to date is nearly 23%, but post-May 14 trading failed to sustain momentum above 7,500.
Philadelphia Semiconductor ETF gained 20% since May 14 as Magnificent 7 fell 10%, reflecting a sharp split between capital spend beneficiaries and major computing buyers.
Shift under Fed Chairman Kevin Warsh to less policy guidance increases market uncertainty, with Fed balance sheet now at $6.7 trillion, down 25% from 2023 peak.

Market leadership and signs of strain

As reported by CNBC, the latest bout of volatility is raising fresh questions about whether the current bull market can keep relying on a narrow set of AI-linked winners while other parts of the market rotate in and out of favor. The S&P 500's annualized total return for 2026 to date is nearly 23%, matching the yearly pace of appreciation since the uptrend began in October 2022, but recent trading is showing less follow-through after new highs.

One focal point is May 14, when the index first moved above 7,500 and touched 7,517, before failing to build lasting momentum and closing Monday at 7,472. That same day also brought a burst of AI enthusiasm around the Cerebras IPO, which opened at $350 after being priced at $185 and later peaked at $386, while Cisco Systems rose 14% on quarterly results tied to AI demand.

Since then, performance inside technology has become more uneven. The Philadelphia Semiconductor ETF has gained 20% since May 14, while the Magnificent 7 group is down 10%, reflecting a sharp divide between capital spending beneficiaries such as memory and infrastructure chip suppliers and the large buyers of computing capacity, including hyperscalers and software companies.

Fed uncertainty and broader market implications

Another issue for investors is the shift in monetary-policy communication under new Federal Reserve Chairman Kevin Warsh, who is promising less transparency and less guidance on future policy moves. That approach is intended to leave more room for markets to price economic data independently, but it also revives debate over whether reduced Fed signaling could lift volatility and tighten financial conditions for a market already trading at elevated levels.

The article argues that some of the assumptions behind this strategy are open to challenge, because the Fed balance sheet has already shrunk to $6.7 trillion, down 25% in nominal terms from its 2023 peak. Relative to U.S. annual GDP it has returned to 2013 levels, and relative to total federal debt it is back to where it stood in late 2008, suggesting its footprint in the economy is materially smaller than in recent years.

Investor positioning adds another layer of risk. Goldman Sachs' Tony Pasquariello puts hedge fund clients at +8 on a scale from -10 to +10, household stock exposure remains high by historical standards, and put-call ratios indicate aggressive bullishness, even as Deutsche Bank's aggregate positioning gauge is neutral and survey data is less extreme.

At the same time, sell-side analysts are described as the most bullish they have been in the post-financial-crisis era, largely because strong corporate earnings continue to feed valuation models. That leaves the market confronting a central question for the second half of 2026, whether AI-related profits represent durable earnings power or an "earnings bubble" in which heavy equipment spending boosts suppliers immediately while the cost to buyers only appears gradually through depreciation.

In our earlier coverage of a global risk-off move, we noted that Nasdaq-led futures and AI-linked shares came under pressure as investors repriced the path of Fed rate hikes and worried that expensive, debt-financed AI spending could be harder to sustain. That piece highlighted the broader spillover into global assets and the strain on big tech names as higher borrowing costs collided with stretched valuations ahead of key U.S. economic data.

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