Two bearish narratives that drove semiconductor stocks into a correction are unraveling, fueling a 5.2% rally in the Philadelphia Semiconductor Index.
Two bearish narratives that drove semiconductor stocks into a correction are unraveling, fueling a 5.2% rally in the Philadelphia Semiconductor Index.
Two bearish narratives that drove semiconductor stocks into a correction are unraveling, fueling a 5.2% rally in the Philadelphia Semiconductor Index.
The Philadelphia Semiconductor Index surged 5.2% in its second consecutive advance, as investors concluded that data center construction delays and open-source AI model competition pose less risk to hardware spending than feared.
"Investors are really buying back in to the semis ahead of earnings because they have fear of missing out," Lindsey Bell, chief investment strategist at 248 Ventures, said. "The numbers are going to be really good, but the stocks are also priced for perfection."
The SOX closed Friday more than 20% below its late-June record high before rebounding. Memory-chip makers led the rally, with Micron Technology advancing 12.2%, Sandisk rising 14.3% and Western Digital gaining 12.5%. The S&P 500 added 0.89% to 7,509.20, while the Nasdaq Composite climbed 1.29% to 25,837.21. The information technology sector led the S&P 500's 11 major industry groups with a 2.35% gain.
The rebound tests whether the market's worst fears about AI infrastructure spending were overdone. Morgan Stanley estimates 2026 AI capital expenditure at $877 billion, with roughly $156 billion in data center projects canceled or delayed in 2025 and about $130 billion affected in the first quarter of 2026. If those delays represent redesigns rather than cancellations, the demand floor for advanced chips remains intact.
Local opposition to data center construction has emerged as a real constraint. Morgan Stanley, citing third-party data, identified roughly $156 billion in projects canceled or delayed in 2025, with about $130 billion more affected in the first quarter of 2026. The bank flagged risks from grid constraints, construction moratoriums and stricter power-and-water regulations.
Yet the strategic imperative behind AI investment suggests these delays are more likely to result in redesigns than outright cancellations. Operators can boost computing output within existing footprints by replacing inefficient servers, increasing rack density and deploying advanced cooling systems. On-site power generation, battery storage and grid-support services offer alternative paths around transmission bottlenecks. These constraints may accelerate replacement demand for newer chips, memory modules and cooling hardware — a dynamic that benefits semiconductor suppliers even if total megawatt build-out slows. The net effect could be a shift in spending composition rather than a reduction in total chip procurement.
The second bearish narrative — that cheaper open-source AI models reduce hardware demand — also appears overstated. China's Kimi K3 model requires substantial high-bandwidth memory capacity and numerous accelerators per service instance, according to reports. While the model can complete individual tasks with less compute, its total memory demand remains significant.
Bank of America research argues that falling Chinese API prices reflect architecture efficiency gains, lower electricity and labor costs, and aggressive market-share competition — not a structural collapse in semiconductor hardware costs. More importantly, the proliferation of open-source models may expand the total addressable market for chips. Closed models concentrate hardware in a few cloud facilities; open models can be downloaded and deployed independently by enterprises, governments and sovereign clouds, creating incremental demand for HBM, DRAM and NAND storage at each deployment node. This "distributed inference" thesis suggests that open models could broaden the semiconductor customer base beyond the handful of hyperscale cloud providers that dominate closed-model deployments.
The semiconductor index remains up nearly 75% year-to-date despite the correction. Nvidia, AMD and TSMC — the primary beneficiaries of AI infrastructure spending — have seen their shares recover alongside the SOX. But with the index still trading at elevated multiples, the sustainability of this rally depends on whether upcoming earnings from Intel, Texas Instruments and Alphabet confirm that end-demand is accelerating rather than plateauing. If the data center delay narrative continues to soften and open-source models prove additive to chip demand, the current rebound may extend beyond a technical oversold bounce. Bell cautioned that sharp pre-earnings rallies make it harder for stocks to run on results, noting that "when stocks rally sharply ahead of earnings, it makes it more difficult for them to run in response to earnings."
This article is for informational purposes only and does not constitute investment advice.