Has storage "risen to the top"?

Morgan Stanley believes the global memory chip industry is approaching a "peak rate of change," but this does not mean the end of the cycle.

According to news from the Chasing Wind Trading Desk, Morgan Stanley stated in a research report on July 6 that the three core controversies currently facing the memory chip market are: whether the price increase cycle has peaked, why long-term agreements (LTAs) have failed to drive a valuation revaluation, and whether this is a cycle top or a correction within a bull market. The core conclusion of the report can be summarized in one sentence: The rate of change of price increases is peaking, but the cycle itself is not yet over.

Morgan Stanley believes that as the largest AI computing buyers are reportedly starting to sell off idle computing power, and as enterprise demand for "token minimization" intensifies, the upward momentum in the memory sector is fading.

This means that ahead of the upcoming earnings season, related stocks will face short-term price weakness and extremely high volatility. The market is currently extremely crowded, and funds are preparing to rotate into lagging sectors. Morgan Stanley's bottom-line advice is: Long-term bullish (expected 35-40% earnings growth by 2027), but short-term caution on pullbacks.

Three Core Controversies: What is the Market Debating?

Morgan Stanley points out that three core controversies have repeatedly emerged in investor conversations over the past week, forming the key framework for understanding the current trajectory of the memory sector.

Controversy 1: Is computing power really oversupplied?

An unverified rumor is circulating in the market that one of the largest capital spenders in AI is reportedly holding surplus computing power available for sale. The bearish interpretation is that if hyperscalers have excess computing power, the entire AI infrastructure buildout could be oversupplied. However, Morgan Stanley offers an alternative interpretation: This is merely companies optimizing capital returns and monetizing idle infrastructure, which is not equivalent to a true oversupply of computing power.

The real verification moment will be the Q2 2026 earnings season — if hyperscalers maintain or raise their capex guidance, it will be a good buying opportunity for memory stocks; if they lower it, the oversupply narrative will persist.

Controversy 2: The "Maximization" vs. "Minimization" of Token Consumption

A new phenomenon has emerged in the process of AI application deployment: many enterprises previously encouraged employees to use AI to generate as many tokens as possible ("token maxing"), but this led to IT budget overruns, prompting companies to seek cheaper alternatives.

Specific manifestations include:

• Enterprises are increasingly adopting open-source large models (among which Chinese open-source LLMs perform notably well) for basic queries;
• Implementing an "orchestration layer" on top of frontier models, routing simple tasks to open-source models and calling frontier models only for complex tasks;
• Market focus is shifting to: how token providers will present this trend in earnings reports, and the guidance for the second half of 2026.

The bank's conclusion is that Q2 2026 (June quarter) is not a major issue for the AI supply chain, but concerns are shifting to the impact of cheaper tokens on second-half guidance.

Controversy 3: Why Haven't Stocks Revalued After LTA Signings?

The signing of long-term procurement agreements (LTAs) should have been a catalyst for valuation revaluation of memory stocks, but the market reaction has been muted. Morgan Stanley's explanation is: The market has a memory — past LTAs were either renegotiated or forced customers to take inventory they didn't need (analogous to the experience of analog semiconductor companies during COVID).

Of course, there are views that current memory LTAs are structurally meaningful (rather than cyclical), provided AI demand remains strong. But whether earnings expectations can continue to be revised upward remains the biggest uncertainty for investors — especially regarding when and by how much memory prices will continue to exceed expectations, thereby pushing 2028 EPS higher, with an extremely unclear timeline.

Peak Rate of Change: Peaking Across Three Dimensions

Morgan Stanley clearly states that the memory industry is approaching a "peak rate of change," reflected in three dimensions:

YoY pricing: The year-over-year increase in DRAM prices has significantly declined from the high in Q1, and the pace of increase is expected to continue narrowing in subsequent quarters;

Inventory changes: The improvement in the inventory cycle is leveling off;

EPS revision breadth: The breadth of earnings expectation revisions in the DRAM sector has reached historical highs (currently around 89%), with limited room for further upward revisions.

This signal of a "peak rate of change" is the core reason why memory stocks need a phased consolidation.

Notably, since the rise of generative AI in November 2022, the memory sector has already experienced three cyclical corrections (corresponding to the US-Iran conflict -15%, profit-taking after rapid gains -32%, the so-called "Tariff Day" -20%, and the current correction of approximately -17%). Morgan Stanley characterizes these corrections as normal adjustments within a structural bull market, not the start of a bear market.

At the same time, Morgan Stanley points out that the most immediate pressure on the memory sector comes from positioning levels, rather than a fundamental collapse.

Memory stocks are among the most concentrated positions in the market. The recent rise in volatility makes it increasingly difficult to maintain historically high net exposure — even against a backdrop of "spot prices rising and volatility increasing." Over the past week, multiple investors have expressed high sensitivity to this dynamic in conversations with Morgan Stanley and have shown strong interest in exploring "laggard opportunities" for rotation.

The recent weakness in hyperscaler stocks may be a leading indicator that memory stocks (as core beneficiaries of AI spending) are about to underperform the broader market. From a seasonal perspective, the current time window is also relatively difficult for the overall market.

Finally, Morgan Stanley explicitly states that at this stage, the earnings commentary from hyperscalers will have a greater impact on stock prices than management commentary from memory companies themselves — because memory companies are likely to maintain a relatively optimistic tone at this point in the cycle.

For AI spenders, the "token maximization" effect is expected to support Q2 2026 results, but whether Q3 2026 guidance falls short of market expectations will be the next major point of contention — token usage optimization, competition from low-cost open-source LLMs, and the impact of "chipflation" on margins are all potential downside risks.

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