First, let’s clarify the timeline. A-shares fell during the day on June 5th, mainly due to issues with their own high-flying tech stocks, financing constraints, and sector overcrowding; US stocks declined on the evening of June 5th, pressured by a combination of strong nonfarm reports, yield concerns, and chip stock expectations. The continued slide in A-shares on June 8th suggests further pricing for crowded trades after Friday’s pressure. The intra-day rebound in US stocks on June 8th only indicates that the AI hardware chain—which saw the most selling on the previous trading day—still has funds replenishing; this cannot be prematurely stated as a closing conclusion.
On A-shares, on June 5th, the SSE Composite Index
Up to June 8th, the pressure didn’t stop at “a single day of falling.” According to the closing figures from Daily Economy News, the Shanghai Index fell 1.7%, the Shenzhen Component Index fell 3.22%, the ChiNext Index fell 3.69%, and the STAR 50 Index fell 4.30%, with nearly 4,600 stocks closing lower. The Securities Times also reported on the same day that the three main markets (Shanghai, Shenzhen, and Beijing) transacted a combined total of about 2.82 trillion yuan, while the BEST 50 index rose 1.33% against the trend. On the market board, CPO and semiconductor chips continued to lead declines, while sectors like banking, oil & gas, coal, and robotics were relatively stronger. This combination was more akin to a structural rebalancing of trades than on Friday: high-flying technology stocks continued shedding excess gains, while low-lying or defensive assets absorbed some risk appetite.
In the US stock market, the decline on June 5th was more pronounced. According to AP’s closing data, the S&P 500 fell by 2.6%, the Dow Jones Industrial Average dropped about 1.3%, and the Nasdaq fell 4.2%. The BLS employment report released the same day showed that nonfarm payrolls increased by 172,000, and the unemployment rate remained at 4.3%. While this data was stronger than market expectations, the result wasn’t “good economy means good stocks,” but rather rising yields and delayed interest rate cut expectations, which caused a re-discounting of future cash flows for highly valued tech stocks. Axios described this day as the decline in the Nasdaq driven by chip stocks, while reports cited by Reuters mentioned that US chip companies lost over $1 trillion in market capitalization on that day.
However, by midday on June 8, 2026, Eastern Time, the market was not continuing in a one-directional decline. According to the chart tool’s data during the trading session around UTC 16:21, QQQ rose approximately 2.36%, SPY rose approximately 0.86%, and DIA rose approximately 0.24%; SOXX rose about 7.27%. Among individual stocks, Nvidia rose by approximately 2.26%, Broadcom rose by approximately 3.14%, AMD rose by approximately 5.27%, Marvell rose by approximately 13.95%, Micron rose by approximately 11.11%, and Taiwan Semiconductor ADR rose by approximately 3.73%. I am only analyzing these figures based on the midday reading, as US stocks have not closed yet; a midday rebound is not the same thing as confirmation of funds at closing.
The most easily misinterpreted statement here is, “Once the domestic market drops, followed by a drop in US stocks, a US rebound means AI is safe.” I do not view it that way.
On Friday, both sides shared pressures related to valuation and trading structure; on Monday, A-shares confirmed that crowded trades are still dissipating; and the intraday rebound of US stocks confirmed that there is still capital willing to make up losses in high-elasticity assets.
There is a correlation among the three, but they do not follow the same single causal line.
A-Shares Continue to Decongest
I will analyze the main drivers behind the A-share market over the last two days across three levels/perspectives.
The primary market observation is this: the sectors experiencing the largest declines, and contributing most to the index drag, were not niche, low-priced assets, but rather segments like semiconductors, storage, optical modules, computing power hardware, and sci-tech weights—sectors previously heavily concentrated by funds. Furthermore, the ChiNext Board and STAR 50 performing consistently weaker than the Shanghai Composite Index themselves indicate that growth stocks and technology beta are under selling pressure.
The second layer is the trading structure. During an after-hours interview conducted by the Twenty-First Century Business Report on June 5th, fund managers cited “multiple brokerage firms lowering the financing conversion ratio for leading semiconductor and AI companies” as a major catalyst. I treat this statement only as one market interpretation, not an official conclusion. However, it explains why high-flyer stocks fall more steeply: When a trade is too crowded, any variable affecting leverage, margin, conversion ratio, and financing capacity tends to be amplified more easily than usual.
The third layer is style rotation. The fact that not only tech stocks fell on June 8th, but nearly 4600 stocks closed lower indicates that risk appetite has broadened; however, the resilience of sectors like banking, oil/gas, coal, and the BEST 50 suggests that funds have not dumped all risk assets indiscriminately. Instead, it appears to be a withdrawal from the high-flyer tech grouping—with some capital shifting into defense plays, while another portion seeks relative strength (or momentum) in small caps and other themes.
Therefore, I prefer to call this A-share decline a concentrated unwinding of high-flyer tech stocks, rather than a comprehensive macro-level risk purge. This difference is crucial. The former implies divergence within sectors, while the latter suggests all risk assets must be treated as if they were undergoing a systemic crisis. The additional information as of June 8th is that the unwinding has not finished and has transitioned from being a “Friday single-day shock” to one that requires confirmation on subsequent trading days.
Mid-day Rebound in US Stocks Does Not Signal Cleansing Completion
The pressure on U.S. stocks this Friday feels like two buttons being pushed at the same time.
One issue is interest rates. The BLS’s non-farm data itself isn’t bad, but for high-valuation tech stocks, overly strong employment data makes the market worry that the Federal Reserve will find it harder to pivot toward easing. AI stocks are especially susceptible to this because much of their valuation comes from revenues and profits many years into the future. Even a slight increase in the discount rate will cut a significant chunk out of long-term stories.
Another factor is expectation. Broadcom’s official financial report is not a sign of failure for an underperforming company. It reported that its Q2 AI semiconductor revenue for fiscal year 2026 reached $10.8 billion, representing a 143% year-over-year increase, and guided total revenue for Q3 to approximately $29.4 billion. The issue is that AI chip stocks have already risen too much; the market doesn’t want “good,” it wants something that exceeds the already highly elevated expectations. When the earnings report cannot continue to raise that imagined curve, capital will start selling immediately.
The mid-day rebound on June 8th cannot be dismissed. The faster assets like SOXX, Marvell, Micron, and AMD rebound, the more it demonstrates that they remain cores of high volatility trading. Short-term capital tends to chase rebounds after a sharp decline, but what truly determines whether this withdrawal cycle has ended is not the mid-day gains, but rather whether the market can maintain stability at close; whether volume shifts from panic profit-taking to steady buying interest; and whether interest rate expectations will continue to suppress valuations.
This is the strangest thing about AI stocks: while industry trends remain strong, the stock can plummet severely; yet, after a sharp fall, it can rebound quickly. This is because stock trading isn’t about “whether AI has a future,” but rather how much future value has already been priced into this current price, and how many other people in the market are buying using the same rationale, leverage, and timeframe.
By consolidating the A-share data from June 5th and June 8th with the US stock intraday data from June 8th, what truly needs to be examined are not directional slogans or narratives, but these variables:
See three lines below
Moving forward, I will avoid an “either/or” judgment such as “buying the AI dip” or “avoiding AI.” AI remains one of the strongest core themes in capital expenditure and industrial upgrading over the next few years, but following drawdowns like those on June 5th and June 8th, the market will become more discerning.
The first point is whether the crowdedness has truly dispersed. For A-shares, we need to see if high-turnover individual stocks in semiconductors, optical modules, and computing power hardware continue falling on increased volume, or if they start stabilizing with decreased volume; we must also determine whether the strength seen in banking, oil/gas, coal, and small-cap themes is merely temporary safe-haven buying, or if funds are continuously reducing their tech allocation. For US stocks, we need to see if the Nasdaq, SOXX, and AI chip stocks can maintain their intraday rebound after market close, rather than basing our judgment solely on midday quotes.
The second focus area is monitoring how cash flow from AI investments is realized. In the hardware chain, the most valuable asset is not simply having “AI” in your name, but rather whether orders can translate into revenue, revenue into gross profit, and gross profit into free cash flow. For many A-share companies mapping this sector, it is more crucial to examine customer concentration, delivery pace, expansion capital expenditure (CapEx), and accounts receivable; while for US stocks, the focus should be on whether cloud vendors’ CapEx has slowed down, and if guidance from Nvidia, Broadcom, AMD, storage, and optical communication chains continues to be revised upwards.
The third factor is whether valuation remains sensitive to interest rates. If US employment and inflation data continue to push back rate cut expectations, highly valued AI stocks will repeatedly face pressure from the discount rate. This pressure might not change the industry trend, but it will change the stock rhythm: previously the market was willing to pay for 2028 profits; now, it may only be willing to pay for visible orders in 2026 and 2027.
This consequently leads me to categorize the AI stocks into three types when analyzing them, rather than grouping them all together (or: putting them all in one basket).
One type consists of infrastructure companies that truly possess pricing power, strong cash flow, and a locked-in customer base. They will also decline, but once they bottom out, it will be easier for the market to re-evaluate them.
One type consists of companies with high elasticity, supported by industry chain mapping and order expectations. While their gains are rapid, they also experience larger drawdowns, and they are particularly susceptible to funding constraints, disappointing performance results, and rumors of customers cutting orders.
There is another category: companies that rely purely on concept diffusion. In a bull market, they appear the most speculative, and during drawdowns, it is also hardest to find fundamental support points. Following June 5th and June 8th, this type requires a higher risk discount because the market has begun shifting from “narrative tolerance” to “realization scrutiny.”
My conclusion is limited: this pullback does not represent the end of the AI industry trend, but it is highly likely a reminder regarding how AI stocks are valued. Going forward, when looking at AI, we cannot simply ask, “Is it AI?” We must instead ask: what part of the money spent on AI capital expenditures (CapEx) will this company actually capture? Can they maintain their gross margins? When will cash flow return? And has the current valuation already priced in the good news from the next two or three years?
If these questions cannot be answered, a dip might not necessarily be cheap; but if they can be answered, a large drop will merely wash out trend-following funds. What is more difficult now is that the mid-day rebound in US stocks gives people a false sense of “everything is fine,” while the A-share close on June 8th reminds us that when crowded trades truly dissipate, it is usually not so graceful.
This article only presents a market review and personal observations, and does not constitute any investment advice. The data parameters for single-day and intra-day market movements may vary slightly depending on the exchange, charting software, or media statistical methods. Specifically, the US stock data for June 8th was not at the closing price/official close when this text was written. Specific trading decisions should always be based on one’s own account constraints, risk tolerance, and officially disclosed information.
References
Artificial Intelligence Machine Learning
- Data Mining
- Deep Learning
- Neural Network
Original Prompt
$blog-writer Last Friday, China's A-share market experienced a sharp drop. Analyze the main reasons for the decline. On Friday night, US stocks also plummeted. What is the outlook for AI-related stocks afterward?
This Update’s Prompts
Today is June 9th. Based on the A-share market data from June 8th, and the current gain/loss percentage of US stocks (not yet closed), I'm updating the article "07-AI-After Stock Pullback - First Look at How Overcrowded Trades Dissipate".
Summary of Writing Ideas
This update maintains the original core judgment: A-shares and US stocks cannot be forced into a single causal narrative, but both exposed issues regarding AI trade crowding, interest rate sensitivity, and earnings realization pressure. The newly added A-share data for June 8 shifts the focus from “single-day drawdown on Friday” to “potential continued overtrading/crowding on the following trading day”; meanwhile, the newly added intraday US market data reminds readers not to treat the midday rebound in semiconductor stocks as if the cleansing process is complete.
I have omitted individual A-share stock gains/losses and intraday trading advice because such content tends to turn a retrospective analysis into short-term instructions. The main body only retains indices, sectors, trading volume, and intraday US market fluctuations that can support the judgment, while repeatedly marking the boundary of “US stocks not yet closed” in relevant paragraphs.