The week of June 22, 2026, was supposed to be just a typical "data-intensive period" for Wall Street: GDP revisions, PCE inflation, and PMI reports were lined up, several tech giants and chip manufacturers were to release their earnings reports, and the Federal Reserve was most likely to remain "pat" during the June meeting, making only slight adjustments to the dot plot and forward guidance. However, this time the combination was different: on June 24, Micron's earnings report would provide the latest guidance on storage and AI data center demand; on June 25, the core PCE for May would reshape the market's belief in "higher rates for longer", while the approximately 4.5-fold increase in DRAM prices since Q3 2025 was pushing the costs of AI infrastructure to extreme levels. Bernstein even warned cloud vendors that they had to recalibrate their return on investment for AI data centers. Unlike most institutions focusing solely on whether a rate hike would occur, Nomura's Chief Macro Strategist Naka Matsuzawa believed that the market had overestimated the urgency of an immediate rate hike this year while significantly underestimating the depth and persistence of a long-term tightening path, directly marking this meeting as a "potential key turning point for the credit cycle and the AI boom's end." If this week represented a dual examination of the macro interest rate path and the AI cost curve, the question then became: when the vertical rise in AI hardware costs meets the reality of persistently high interest rates, will high-beta assets like BTC and ETH, which have historically fluctuated significantly alongside the Nasdaq during periods of rising interest rate expectations, face indiscriminate selling in this repricing process, or could they unexpectedly become the next vessel for funds seeking new leverage amidst profit-taking in AI stocks and narrative shifts?

Nomura: Pat but Tightening for Longer Cycles

In the framework of Nomura's Chief Macro Strategist Naka Matsuzawa, the real danger of the June FOMC meeting was not whether to raise rates immediately, but whether the Fed would take another step forward on the long-term path of "higher and longer." Nominal rates were likely to remain unchanged that day, in line with market consensus, but if the dot plot and forward guidance stretched the high-rate plateau further, it would gradually erase the quick rate cut space previously "imagined" by the market. Matsuzawa's judgment was straightforward: traders overestimated the urgency of an immediate rate hike this year but severely underestimated the depth and persistence of this high-rate path. This was not "hawkish shock," but instead indicated that the credit cycle was slowly locking in.

The shift in rate expectations from "swift hikes and swift cuts" to "fewer hikes or no hikes, but hard to lower rates for a long time" had a clear transmission chain: prolonged high rates would increase corporate medium- to long-term financing costs, US Treasury yields would remain high, credit spreads would be difficult to compress, and high valuation growth stocks' discount rates would be systematically raised. AI-themed stocks and cloud vendors, assets with extremely long cash flow durations, would be the first to bear the brunt, as each forward cash flow would need to be recalibrated with a higher discount rate. BTC and ETH, which have closely risen and fallen alongside the Nasdaq in recent years, would find it hard to enjoy the liquidity expectations brought by "first raising rates, then rapidly cutting rates" under this new interest rate path’s repricing. Historically, they have been highly sensitive to changes in actual US Treasury yields and the dollar index; once the market acknowledges that "high rates will be accompanied by rising AI costs for a longer cycle," cryptocurrencies would be categorized into the same basket as high-beta tech stocks, first facing a round of valuation compression due to the path correction, and then it would be up to funds to decide whether this is just a misallocation of peripheral chips or the main battlefield for a new macro trade.

Storage Prices Up 4.5 Times: AI Capital Expenditure Hits the Brakes

Since Q3 2025, traditional DRAM prices have risen cumulatively by about 4.5 times, with storage transforming from a "supporting role" to one of the most inflated components within AI hardware. Bernstein's report describes this round of price hikes as a "cost plague" that is spreading: first, consumer electronics were forced to raise prices or reduce configurations, and now it's time for AI infrastructure to foot the bill, as prices for high-bandwidth storage and other products continue to rise, while the total cost of each data center jumps despite unchanged computing power per unit. The question is not just about whether it's expensive, but when storage prices fluctuate as they would in a commodity bull market, the IRR and payback periods originally calculated by cloud vendors based on linear cost reductions and stable utilization rates could become entirely distorted.

That's why this week's Micron earnings report is being watched unusually closely—what the market is looking for is not just revenue growth rates, but how management describes the price and demand curves for HBM and DRAM in AI data centers: if prices remain high and supply continues to be tight, it would imply that AI capital expenditure is unlikely to slow down in the short term, but profits would further concentrate among a few hardware suppliers; if cloud vendors begin to press prices through delayed launches and elongated construction cycles, it would mean that the narrative of "mindless expansion of AI data centers" has reached its zenith. Between 2023 and 2026, the valuations of mainstream AI-themed stocks in the US stock market largely depend on whether this round of high-intensity AI Capex can persist for years. Once ROI is recalculated and the slope of capital expenditure is revised downwards, the narrative around AI as the main investment narrative for global risk assets would recede, high-beta tech stocks would be the first to deflate, and the on-chain AI narrative tokens that are highly synchronized with them would also face fund withdrawals and valuation repricing. BTC and ETH would experience shocks on sentiment and risk appetite, with the core variable the market needs to observe being whether storage inflation will hard stop this AI investment highway that was previously smooth sailing.

High Rates Combined with AI Retreat: Bitcoin as a Resonant Risk

When the two curves of "higher for longer rates" and "out-of-control AI costs" intersect in the summer of 2026, high-beta global assets are faced not with a single downward trend but with a rhythmically synchronized dual resonance. Nomura’s macro team sees the June FOMC meeting as a potential turning point for the credit cycle and the AI boom, essentially saying: not only does the market need to pay for short-term rate inaction but it must also reprice for a steeper, more lasting interest rate path; meanwhile, since Q3 2025, DRAM prices have cumulatively surged by about 4.5 times, and Bernstein's report warns that storage price hikes are spreading from consumer electronics to AI infrastructure, forcing cloud vendors to recalculate the balances of AI data centers, solidifying the narrative that AI capital expenditures have "peaked." Rising rates compress valuations, and soaring costs squeeze profits; these two forces simultaneously point toward the same group of assets: high-valuation, high-growth tech stocks, as well as BTC and ETH, which are highly synchronized with them in terms of risk appetite.

In the past two years, multiple inflation surprises and changes in employment data have triggered not merely the volatility in one market but have caused synchronized adjustments between the Nasdaq, BTC, and ETH. AI-themed stocks and on-chain AI narrative tokens have exhibited "amplified" swings, underscoring that traditional markets and cryptocurrency markets are being traded as a basket of high-beta tech/AI combinations. If this week's PCE is stronger than expected, and the market is forced to further acknowledge "higher rates for longer," along with Micron's earnings potentially signaling a slowdown in AI storage demand or a contraction in capital expenditure, actively managed funds are more likely to choose to compress risk exposure altogether, rather than simply rotating from AI stocks to on-chain AI tokens or even BTC/ETH. High-leverage longs would passively deleverage via futures and options, making Bitcoin a "systemic factor" in this round of resonance rather than an independent asset. However, there is also the opposite path: if the data only promotes a moderate cooldown rather than a complete reversal, some funds that are already highly sensitive to AI stock valuations might choose to withdraw from hardware and cloud vendors—where the fundamentals are no longer dominant—toward BTC and ETH, which have better liquidity and stronger narrative flexibility, treating them as vehicles for retaining tech risk premiums while being relatively insulated from the earnings constraints of individual companies. The true decider of whether BTC will be miscalculated or narrative reshaped in this AI retreat is how the interest rate path, AI capital expenditure expectations, and cross-asset fund flows converge in this cycle.

PCE and Micron Earnings Week: A Volatility Window for Cryptos

The rhythm of this week is quite clear: Wednesday for Micron, Thursday for core PCE. Micron, as a supplier of storage and AI-related chips, is at the crossroads of a situation where DRAM prices have cumulatively risen by about 4.5 times since Q3 2025, and Bernstein has begun to question the ROI of AI infrastructure investment; its orders and guidance are viewed as real-time thermometers for AI data center demand and cost pressures. Meanwhile, the May core PCE on Thursday is the inflation anchor most valued by the Federal Reserve; any deviation from expectations would directly rewrite the pricing of the interest rate path, dollar index, and US Treasury yields. Traditional macro trading desks in such a "double testing" week would first adjust rate and Nasdaq exposures around the PCE, then use BTC and ETH futures and options for high-beta hedging: during the 24 hours before and after the inflation data release, leverage and options gamma often amplify price responses one to two levels; off-exchange funds may enter or exit early through stablecoin channels, often experiencing a slowdown in net inflows and heightened wait-and-see sentiment in the days leading up to the data release, followed by directional expansion afterward.

From a trading structure perspective, these 48 hours can break down into several scenarios: if the PCE is above expectations and Micron's earnings "blow away" estimates, the market would recognize both "higher for longer rates" and "AI prosperity is not yet at its peak," causing both nominal rates and AI valuations to rise; high-beta tech stocks would experience sharp volatility, with BTC and ETH typically amplifying the market's correction pace driven by futures—AI narrative tokens might initially surge alongside Micron's positive news before being slammed back to square one under rate pressures due to profit-taking; if the PCE shows a clear decline but Micron provides weak guidance, it would form a "rate cooling + AI cycle cooling" dual cooldown combination, applying short-term pressure on tech stocks, but once the shadow of high rates alleviates, some funds that withdrew from AI stocks might flow back on-chain via stablecoins, treating BTC and ETH as a "tech risk portfolio free from single-company risk," with AI concept coins initially experiencing miscalculations before rebound elasticity supported by easing expectations and narrative imagination; the most extreme scenario would be a divergence between inflation and AI narratives—if PCE is hot while Micron weakens, it represents a dual negative for the crypto space regarding both rates and narratives, leading BTC, ETH, and AI tokens to be more prone to amplification downward under high-leverage structures, whereas if PCE cools but Micron continues to advance strongly, it would represent a macro and AI aligned positive, elevating risk appetite, and pushing up BTC/ETH and AI narrative tokens alongside the collaborative effects of options implied volatility and stablecoin net inflows; the ultimate test during this window would be determining who can read the dissonance between inflation and AI guidance most swiftly and complete positional adjustments in advance.

If the AI Bubble Peaks, How Will Crypto Reshape the Narrative

This week's Fed signals combined with the AI cost inflection point actually present two completely different multiple-choice questions for crypto pricing: if the core PCE is hot, validating Nomura's assertion of "higher for longer rates," and simultaneously Micron's earnings report and rising storage prices further verify Bernstein's warning regarding rising AI infrastructure costs, the narrative that AI capital expenditure has peaked would suppress the previously singular mainline narrative of the past two years, with high-beta assets being forced to de-leverage and reprice overall; BTC and ETH would find it easier in this environment to revert from narratives of "tech growth β" back to the old narrative of "currency and sovereign risk hedge," with prices under short-term pressure, but once the stress from the credit cycle spills out, it might actually welcome hedge buying ahead of AI stocks in the passive selling of other risk assets; conversely, if the PCE indicates controlled inflation and a gentle interest rate path, while Micron and other AI upstream firms continue to tell tales of high growth and high price, prolonging AI prosperity, the mainline narrative of crypto would be closer to "riding the liquidity coattails of AI and growth stocks," with BTC, ETH, and AI concept tokens continuing to be treated as high-elasticity parts of the tech chain, with trading structures revolving around risk appetite elevation and options leverage. For traders, the real priority is to monitor changes in the shape of the interest rate curve, AI capital expenditure signals released by cloud vendors and chip manufacturers in their earnings reports and guidance, and the rotation rhythms of funds between AI stocks and crypto, rather than being led by isolated on-chain data, as it is the convergence of the interest rate path, AI investment intensity, and cross-asset fund flows that determines whether crypto gets miscalculated or narratives are reshaped in this round of the AI storm.

Join our community to discuss and grow stronger together!
AiCoin exclusive Hyperliquid benefit: https://app.hyperliquid.xyz/join/AICOIN88
AiCoin exclusive Aster benefit: https://www.asterdex.com/zh-CN/referral/9C50e2
On-chain Telegram community: https://t.me/AiCoinWhaleData
On-chain community: https://www.aicoin.com/link/chat?cid=N6OVMor5g
AiCoin on-chain Twitter: https://x.com/aicoinwhaledata

免责声明：本文章仅代表作者个人观点，不代表本平台的立场和观点。本文章仅供信息分享，不构成对任何人的任何投资建议。用户与作者之间的任何争议，与本平台无关。如网页中刊载的文章或图片涉及侵权，请提供相关的权利证明和身份证明发送邮件到support@aicoin.com，本平台相关工作人员将会进行核查。