According to analysis, the first major market turning point of 2026 occurred in March, defined by the willingness to increase allocations to AI amidst external shocks including US-Iran tensions, high oil prices, and interest rate hike expectations.
On March 22nd, it was advised to look beyond exogenous variables such as geopolitical tensions and inflation expectations and focus on high-growth industry trends.
Subsequent discussions have covered factors like market crowding and inflation, which are variables outside core industry trends and fundamentals. The current market dynamic is characterized as a contest between the pace of EPS upgrades and the speed of rising interest rates.
Identifying the Next Crucial Juncture
Recently, market declines, particularly in technology assets, have exceeded expectations in both magnitude and speed. This is attributed to factors like overseas leveraged fund outflows, overly uniform market expectations around key events, and geopolitical conflicts.
At this juncture, an objective and rational assessment of the current market position and opportunities is essential. Based on the ongoing AI industry trend, the extent and duration of the recent correction, and incremental ETF fund flows, it is believed that a second pivotal market opportunity for the year is approaching.
Firstly, monitoring of broad-based ETF and major fund inflows this week indicates that current levels represent a secondary peak since the "9.24" period, only surpassed by the period during the equivalent tariff implementation in April 2025.
Assessing the Correction in the Tech Sector
Secondly, drawing on experience from both Chinese and US markets, the current adjustment in the technology sector appears sufficiently deep. Since late June, declines in the STAR and ChiNext indices have both exceeded 20%, driven primarily by liquidity shocks both domestically and internationally.
Historical patterns from past core industry cycles in both A-shares and US stocks suggest the adjustment in the A-share tech sector is ample in terms of price decline, though the duration of the adjustment is slightly shorter than historical precedents. Therefore, it is judged that the year's second major turning point is not far off.
Evaluating the Risk of a Bubble Peak
A third and critical question is whether the current environment could represent the peak of an industry cycle bubble. This is a crucial precondition for whether past experiences of阶段性 adjustments remain relevant. Previous analysis has been based on adjustments within an ongoing industry cycle.
However, if a fundamental judgment is made that an industry cycle has ended, then purely technical or liquidity-based analysis becomes futile. Extensive statistical experience from both A-share and US markets indicates that two key empirical values are central to judging an inflection point in growth momentum: 30% and -50%. Market performance deteriorates significantly when growth rates fall below 30% from a high level, or when the decline in the growth rate exceeds 50%.
Returning to industry fundamentals, the current low penetration rate and sustained capital expenditure suggest the AI industry trend remains ongoing. Objectively, however, due to differences in supply-demand structures and technological barriers, growth momentum within different segments of the AI industry is likely to diverge, placing higher demands on the granularity of subsequent research.
Short-Term Market Observations
In the short term, as risks from negative fund flow feedback have initially emerged, broad-based ETFs have once again shown significant net inflows. The magnitude of these net inflows has reached the third-highest level since the beginning of this bull market.
Historical data points include significant inflows during the period from September 24 to October 9, 2024, again from April 7 to April 9, 2025, and most recently from July 13 to July 18, 2026.
Lessons from A-Share Adjustments in Growth Sectors
Examining historical adjustments in A-share market leaders since 2012 reveals an average adjustment period of 21 trading days, with an average decline of 19%, roughly equivalent to five times the average monthly K-line size. Since late June, the declines in the STAR and ChiNext indices have exceeded 20%, driven by liquidity shocks. Compared to past A-share industry cycle adjustments, the price correction appears sufficient, though the adjustment time is slightly shorter.
Insights from US Market Tech Sector Adjustments
Since 2023, the US tech sector has experienced six relatively prolonged adjustments. On average, these lasted 40 trading days, with the S&P 500, Nasdaq, the "MAG7" group, and the Philadelphia Semiconductor Index declining by 8.8%, 12.0%, 13.4%, and 17.6% respectively.
Past adjustments were typically triggered by exogenous shocks related to discount rates, policy, or geopolitics. Catalysts for ending these adjustments have included policy shifts towards accommodation, the resolution of temporary shocks, or earnings data disproving bubble concerns. As long as the chain from "AI capital expenditure to profits" remains intact, corrections in the tech sector are controllable and tend to be followed by rapid recoveries led by tech stocks themselves.
Determining the Peak of an Industry Cycle
The final consideration is identifying a potential bubble peak in an industry cycle. Since the previous analysis is based on adjustments within an ongoing cycle, it becomes less relevant if a fundamental cycle is deemed to have ended. Discussion of industry cycles must return to positioning within the three stages of growth investing, with a core emphasis on marginal changes in growth momentum.
Marginal changes in momentum encompass two layers. The first is an inflection point in the rate of acceleration, which is relatively easier to identify by tracking changes in growth rates or expectations. The second, more critical layer is an inflection point in the growth cycle itself. This occurs when EPS growth slows or the rate of deceleration is so severe that the compression in the price-to-earnings ratio outweighs EPS growth.
The key to judging this inflection point lies in the two empirical values: 30% and -50%. Statistical evidence shows market performance deteriorates significantly when growth rates fall below 30%. Similarly, when the decline in the growth rate exceeds 50%, performance also weakens markedly. Notably, the market shows increased tolerance for deceleration in previously high-growth stocks. The application of the -50% rule therefore requires flexibility, with the core focus being on identifying a sustained downward inflection point in profits for a growth sector.
US market data over the long term shows a similar pattern of reduced returns when growth falls below 30%, though this relationship has weakened somewhat post-2010, possibly due to ample liquidity and share buybacks dampening volatility.
Returning to AI industry fundamentals, low penetration rates and ongoing capital expenditure indicate the trend is still in progress. According to a Microsoft report, global AI penetration reached 17.8% in Q1 2026. Historical patterns from industries like PCs and the internet suggest prolonged stock price stagnation may only occur after penetration reaches 40-50%. Current AI penetration, especially in production environments, remains relatively low.
Finally, objectively, due to differences in supply-demand structures and technological barriers, growth momentum within different AI segments is likely to diverge, requiring more granular research. Judging inflection points across different segments involves identifying primary profit sources and growth sustainability, then analyzing them against the growth stages indicated by the two empirical values. This historical framework provides a reference for tracking momentum across different AI industry layers, from high-visibility component makers to manufacturing-heavy segments, cyclical memory products, and early-stage applications driven more by expectations.
Risk Factors to Consider
Key risks include geopolitical conflicts exceeding expectations, leading to higher-than-anticipated global inflationary pressures; overseas inflation and US economic resilience prompting a faster global shift to monetary tightening; and domestic economic stabilization measures falling short of expectations, resulting in weak recovery and declining market risk appetite.
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