On July 7, 2026, before the U.S. stock market opened, Nvidia delivered a significant warning to the entire “tech + crypto” risk chain: MSX.COM data showed a decline of about 2.3%, BIT(bit.com) about 2.21%. During the quiet period before the market opened, the market began rewriting the story of future profit margins for this AI computing powerhouse. Almost simultaneously, the report by Dutch Bank analyst Jan Frederik Slijkerman pointed directly to the crux — with major clients like Microsoft, Alphabet, and Amazon accelerating their self-developed customized AI chip projects, the ability of Nvidia to maintain high profit margins is uncertain; the Chinese startup DeepSeek, which launched its own AI inference chip project a year ago, is attempting to reduce dependence on Nvidia and Huawei through self-development, indicating that the era dominated by “general-purpose GPUs” is being eroded by diversified customized chips. Beyond the destabilization of the corporate moat narrative, a higher-level macro warning was also pressing down: Bank of England Governor Bailey reminded that the expansion of stock valuations is not limited to the optimistic sentiment related to artificial intelligence, and the stock market still faces a high risk of severe adjustment. When a benchmark like Nvidia is forced to confront a narrowing moat and the potential for valuation corrections, and central banks simultaneously signal that overall stock market valuations are too high, institutions are unlikely to only adjust models for single stocks; rather, they will examine the entire basket of “high-volatility tech growth risk assets”—which also includes BTC and ETH seen as tech growth risk assets within the allocation framework. The main thread of this article then unfolds: the repricing of expected returns and valuations for AI leaders, combined with macro risk signals from central banks, alters the risk premium and correlation trading structure, driving funds to re-select among AI stocks, crypto assets, and U.S. dollar-denominated assets.
Nvidia's Moat Narrows: Client Self-Development Chips Tear Apart the Profit Margin Myth
In Jan Frederik Slijkerman's report, the true alarm was not the 2% drop before the market opening on July 7, but the power shift behind the order structure: Nvidia's core buyers, such as Microsoft, Alphabet, and Amazon, are shifting the lifeblood of computing power from “outsource to GPU monopolists” to “self-develop customized AI chips,” with the aim not being sentiment, but cold hard budget sheets—lowering AI infrastructure costs and rewriting the long-term gross profit curve. About a year ago, DeepSeek launched its self-developed inference chip project, also choosing to cut into the high-frequency scenario of inference, aiming to reduce reliance on Nvidia and Huawei. The self-development project is still in its early stages, indicating that Nvidia's profit report will not collapse immediately, but the trend is clearly evident: shifting from “only able to buy Nvidia” to “comparing Nvidia with its own chip cost-performance ratio,” it is losing pricing power and bearing structural profit margin pressure.
For the U.S. tech sector, this pressure is not just the story of a single company but a rearrangement of the entire “AI infrastructure investment rhythm.” When giants begin to expand computing power with cost constraints, the market's expectations for AI capital expenditures in the coming years will inevitably be downgraded, repricing the overall expected returns and risk premiums of the sector—high valuations are no longer automatically matched with high and certain profit margins but seem more like a competitive bet in a crowded race. In the institutional narrative framework, BTC and ETH are placed in the same basket: both are high-volatility growth assets betting on a technological paradigm shift. Once Nvidia's profit margin myth is stripped away, the credibility of the narrative of “tech growth” is discounted, making funds more alert to any assets reliant on long-term high-growth assumptions, making positions in crypto assets more prone to shift from optimistic expansion to risk contraction in sync with AI leaders.
Bank of England Discusses Severe Adjustments: High-Valuation Tech Sector at the Core of Risks
Almost simultaneously with Nvidia under pressure, Bank of England Governor Bailey's public statement shifted the sentiment in this round of tech stocks from “optimistic” to “cautious.” Bailey did not confine the issue to a single AI hotspot but pointed out that: the expansion of stock valuations seems not limited to the optimistic sentiment related to artificial intelligence, and the stock market still faces a high risk of severe adjustments. This statement directs attention to the entire high-valuation growth sector—not just the computing power leaders, but all tech assets priced under the same logic. For institutions, this is not media commentary, but a risk management signal from central banks of major developed economies, indicating that the probability of a global risk asset correction has been reassessed from the regulator's perspective.
When macro regulators openly use terms like “severe adjustment,” traditional asset management and hedge fund trading actions often quickly follow: on one hand, lowering overall portfolio leverage, and on the other, reducing concentration in high-volatility tech growth baskets. In recent times, global tech stocks, especially AI-related ones, saw significant valuation increases driven by optimistic expectations. Now this narrative has been questioned by the central bank, and the correlation assumptions in risk control models regarding similar assets will be uniformly raised. Since BTC and ETH are typically viewed as high-volatility tech growth risk assets in institutional asset allocation frameworks, when tech stocks are labeled as “high valuation, easy severe adjustment,” crypto positions rarely remain unaffected: correlation trading will guide funds to reduce positions simultaneously, and the volatility premium of high beta assets will be repriced, ultimately requiring BTC and ETH to compete for continued institutional participation at lower prices or smaller position sizes under higher risk compensation requirements.
As AI Stocks Fluctuate: Capital's Hedge and Game in the Crypto World
When Nvidia recorded a decline of over 2% before the market opened on July 7, the data from MSX.COM and BIT(bit.com) materialized this retracement into figures; what was truly shaken was the risk budget of the holders. For institutions treating BTC, ETH, and AI leaders as part of the same tech risk asset basket, Nvidia's price drop as the core of computing power, combined with the business model uncertainties brought by self-developed chips from players like DeepSeek, means the entire “high beta tech exposure” will be uniformly scrutinized: some funds will choose to reduce positions in AI and growth stocks on the U.S. stock front, while others will compress BTC and ETH's risk exposure on the crypto side, temporarily consolidating positions into dollar-denominated on-chain assets to complete defensive rebalancing within the same asset category.
In a scenario where risk appetites fall, the typical on-chain behavior in the crypto market often presents a similar script: liquidity-rich high-beta tokens are sold off first, used to hedge the overall risk exposure brought by tech stock corrections; subsequently, some institutions and crypto native funds halve their “tech narrative” positions, parking more chips temporarily in dollar-denominated positions, waiting for benchmarks like Nvidia to stabilize or for macro warnings to dull before reallocating to BTC, ETH, and higher-risk thematic tokens. It should be emphasized that this briefing does not provide any specific on-chain capital flows or dollar asset increases or decreases data; this section can only outline potential hedging paths and reallocation rhythms in the crypto world when Nvidia is under pressure, based on prevalent patterns of capital behavior during historically similar risk events.
Correlation Trading of BTC/ETH with U.S. Tech Rekindled
Within the institutional asset allocation framework, BTC and ETH are no longer “alternative corners” but have been stuffed into the basket of “high-volatility tech growth risk assets” alongside tech giants like Nvidia. When the drop of about 2.3% (MSX.COM) and 2.21% (BIT(bit.com)) for Nvidia was recorded before the market opened on July 7, these two numbers themselves became immediate price signals for global risk assets: expectations for AI leaders downgraded, their moat questioned, coupled with Bailey's public warning of the risks of severe adjustments in the stock market, institutions naturally view “reducing tech risk” and “reducing crypto risk” as actions on the same decision-making chain, examining them together on a unified risk budget sheet.
Under this narrative, correlation trading typically unfolds along two paths: one is a simple and crude synchronous de-risking — reducing long positions in Nvidia and its peer AI tech stocks, along with cutting back on high-volatility exposures like BTC and ETH, thereby lowering the entire tech growth factor; the other is a more refined cross-asset hedge — trading desks utilize tech stock futures and individual stock options to cover Nvidia's correction risk while adjusting the overall volatility level of the portfolio through futures and options on BTC and ETH, balancing equity-side risk exposure with crypto's long and short positions. At times when the macro narrative from the Bank of England about “severe adjustments to high risk” resonates with specific price signals like Nvidia's pre-market drop, whether BTC and ETH continue to be treated as “risk factors extending from tech stocks” for correlation trading becomes a key observation point determining the forthcoming volatility structure in the crypto market.
From Nvidia to the Crypto Market: Watching for Moat Contraction or Emotional Collapse
From Nvidia's pre-market drop of about 2.3%/2.21%, to Jan Frederik Slijkerman's report incorporating the wave of self-developed chips into profit margin uncertainty, and then to Bailey's public warning of “severe adjustments at high risks,” these clues point to the same set of macro variables being simultaneously rewritten: tech stock valuation premiums are compressed, overall preference for risk assets cools, and the market's imagination of future profit trajectories for AI leaders begins to shrink. The self-developed chips from Microsoft, Alphabet, Amazon, and DeepSeek push the computing power market from a “single high-margin supplier” to “multi-polar competition,” and Nvidia's moat is no longer seen as an unconditional safe premium, leading to a repricing of the discount rates for tech growth stocks. Against the backdrop of central banks raising the cautionary line for the stock market, funds migrating from high beta growth tech to defensive sectors or cash-like assets tend to examine positions in BTC and ETH, classified as “high-volatility tech growth risk assets” within institutional frameworks. Position reductions and volatility hedging under correlation trading may occur even before fundamental narratives unfold. What is worth paying attention to next is whether Nvidia's upcoming financial reports can repair the profit margin narrative, whether its major clients and players like DeepSeek can dilute the single computing power premium further, whether Bailey-style central bank risk talk is a one-time warning or a sustained signal, and whether the crypto market can carve out an independent trend or partially decouple from the risk pricing path of the U.S. tech sector under the pressure of this round of tech valuation reassessments.
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