A sharp retreat in global technology shares and rising concern over the debt supporting artificial intelligence infrastructure have created a more fragile backdrop for risk assets, including major cryptocurrencies. Goldman Sachs estimated that technology, media and telecommunications stocks recorded about $20 billion in net selling over the past two weeks, a pace approaching the $23 billion sector outflow seen during July’s market drawdown.
The selling has yet to push the Nasdaq 100 decisively below its established range, but technical support is drawing closer. Nasdaq 100 futures were holding near 29,000, while the index’s 200-day moving average sat around 28,500, according to the market levels cited in Goldman’s analysis. A sustained break below that zone would place greater attention on whether a technology-sector correction is becoming a broader reduction in appetite for high-growth and highly leveraged assets.
Goldman said the intensity of recent selling reached minus 3.3 standard deviations, an unusually severe reading. Its risk-appetite indicator also suffered one of its largest one-day declines on record and fell to its lowest level since April 2025. TMT fundamental net exposure dropped to a year-to-date low, while overall exposure remained at the 63rd percentile, suggesting that some positioning has been reduced but has not been broadly eliminated.
Ai financing costs add pressure to technology valuations
JPMorgan has tied the market’s unease to the rapidly expanding financing needs of AI infrastructure. The bank said debt financing absorbed by AI infrastructure projects this year has exceeded $500 billion, while financing costs for hyperscale cloud providers have risen by roughly 120 basis points.
That combination places pressure on a segment of the market whose valuations have often depended on expectations of sustained spending on data centers, chips, networking equipment and power capacity. Higher interest expenses can reduce the financial flexibility of cloud companies and their customers, particularly if projected AI-related revenue takes longer to arrive than capital spending.
JPMorgan also flagged credit transmission risk in the AI supply chain. Funding relationships between Nvidia and some customers purchasing graphics processing units could create feedback loops: if operators face tighter financing conditions, their equipment purchases may slow, affecting semiconductor suppliers further up the chain.
The Philadelphia Semiconductor Index, or SOX, was testing its own 200-day moving average, according to the supplied market data. That makes upcoming results from major cloud providers and chipmakers more consequential than a routine quarterly earnings season. Markets will be watching whether reported demand converts into recognized revenue, whether customers maintain capital-expenditure budgets and how those budgets will be financed.
Google, Microsoft and Amazon were identified as the next immediate earnings catalysts. Their spending plans matter beyond their own shares because they are among the largest buyers of AI computing capacity, servers and networking equipment.
Volatility signals a technology-specific risk repricing
Goldman found that options markets have begun assigning a larger risk premium to the Nasdaq 100 than to the broader S&P 500. The bank estimated that the spread between Nasdaq 100 and S&P 500 implied volatility widened to the 98th percentile of its five-year range. The one-day widening last Thursday was the second-largest such move over that period.
The divergence suggests traders are becoming more concerned about concentrated technology exposure than about the entire U.S. equity market. The S&P 500 had fallen around 2.4% during the current move, compared with a 3.4% decline in July, while TMT outflows were already nearing the scale of that earlier episode.
Credit markets have reinforced the caution. JPMorgan said credit default swap spreads tied to AI-related companies had widened, alongside a larger gap between CDS pricing and cash bonds. CDS contracts function as insurance against a borrower defaulting; higher spreads generally signal that market participants are demanding more protection against credit risk.
Crypto faces a tougher risk environment, not a direct mechanical link
Cryptocurrency markets often respond quickly when liquidity conditions tighten and traders reduce exposure to volatile assets. A deeper technology selloff, particularly one driven by higher funding costs and concern over AI capital spending, could therefore weigh on digital assets through the same risk-off channels that affect other speculative markets.
The connection is more indirect than a simple one-to-one relationship. Bitcoin, Ether and smaller tokens trade around the clock and can react to crypto-specific developments such as regulatory decisions, stablecoin flows, protocol activity and large liquidations. Yet a technology-led decline can weaken sentiment, reduce available leverage and increase demand for cash or short-duration government securities across financial markets.
Claims that a slowdown in technology spending would automatically depress token prices through competition for electricity require more evidence than the available figures provide. Power demand is relevant to Bitcoin mining and data-center development, especially in regions with constrained grids, but AI capital expenditure, mining economics and cryptocurrency prices are shaped by separate revenue models and operating conditions.
The more immediate issue for crypto traders is financing. Rising borrowing costs tend to make leveraged positions more expensive to carry and can accelerate liquidations when prices fall. Smaller digital assets with thinner liquidity are generally more exposed to rapid moves when leverage is unwound.
Positioning and earnings could determine the next move
JPMorgan said an early-November buying window could emerge if several conditions align: further clearing of crowded positions, confirmation of hyperscalers’ capital-expenditure direction, resilient semiconductor earnings and narrower credit spreads. Those conditions would indicate that the market has absorbed some of the financing concerns rather than simply postponing them.
Until then, the technology sector remains caught between high expectations for AI revenue and a less accommodating credit environment. For cryptocurrency markets, that leaves the near-term focus on the same variables driving technology risk: borrowing costs, volatility, equity-market support levels and the ability of major AI spenders to justify their expanding infrastructure bills.
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