--- title: "How to Identify the Bubble Peak of the AI Cycle?" type: "News" locale: "en" url: "https://longbridge.com/en/news/294034276.md" description: "GF Securities believes that identifying the bubble peak of industrial cycles such as AI requires returning to the earnings cycle, rather than relying on valuations or monetary conditions. Historical data shows that an earnings growth rate falling below 30% or a decline exceeding 50% is a key red line for identifying inflection points in prosperity. Currently, global AI penetration remains low and tech giants continue to expand CAPEX, indicating the industry's prosperity cycle is still ongoing, but differentiation within internal segments will intensify" datetime: "2026-07-28T08:38:37.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/294034276.md) - [en](https://longbridge.com/en/news/294034276.md) - [zh-HK](https://longbridge.com/zh-HK/news/294034276.md) --- # How to Identify the Bubble Peak of the AI Cycle? Amid growing controversy in the technology growth sector, a key question faces investors: Where does the current AI industry cycle stand, and how can we judge the arrival of a bubble peak? The answer from GF Securities' strategy team is that neither valuations nor monetary environments are effective signals for market tops; the true basis for judgment must return to the industry's own earnings cycle. In a report released on July 26, GF Securities strategy analysts Liu Chenming, Zheng Kai, and others pointed out that **there are two key empirical thresholds for identifying inflection points in prosperity: earnings growth falling below 30%, or a decline in growth rate exceeding 50%.** Once these "red lines" are touched, historical data shows that market returns will drop significantly. Regarding the current AI sector, the team's judgment is that global penetration remains low and tech giants' CAPEX continues to expand, meaning the AI industry prosperity cycle is still ongoing, but divergence in prosperity among different internal segments will become increasingly significant. The emergence of this conclusion coincides with a significant widening of divergence in the A-share technology growth sector. The second-quarter reports of public funds show that the allocation ratio in the electronics industry has risen to 43.7%, setting a new historical record, triggering widespread market discussion on "industrial cycle bubbles" and "style rebalancing." GF Securities' analysis provides investors with a framework of trackable indicators based on historical statistical patterns. ## Valuation and Monetary Environment: Two "Ineffective" Top Signals The GF Securities team first refuted two common methods for judging market tops. Regarding valuation, PE levels at the peaks of different sectors in history have ranged from dozens to hundreds of times, showing vast differences and making it difficult to serve as a unified reference. More importantly, valuation peaks usually appear earlier than stock price peaks, with special cases such as the 2015 A-share liquidity crisis being exceptions. Regarding the monetary environment, since the 1990s, capital markets have mostly continued to rise during multiple Fed hiking cycles, with 2022 being a notable exception. Tightening liquidity eventually transmits to corporate earnings, but there is a significant lag—the peak of the Dotcom Bubble in 2000 was about 1 year after the first rate hike, while the peaks in 2007 and 2018 were about 3 years after the first rate hike. **Therefore, the core conclusion of the report is: To judge the bubble peak of an industrial cycle, one must return to the industry's own earnings cycle, rather than relying on valuation levels or external monetary conditions.** **** ## 30% and -50%: Two "Red Lines" for Prosperity Inflection Points GF Securities distinguishes marginal changes in prosperity into two levels: one is the inflection point in the speed of growth acceleration (growth inflection point), which is easier to identify; the other is the inflection point in the upward prosperity cycle (prosperity inflection point), which corresponds to the true top area of stock prices. The appearance of a prosperity inflection point corresponds to two scenarios: **earnings growth falls below 30%, or the decline in growth rate exceeds 50%—at which point the compression of PE will exceed the contribution of EPS growth, putting pressure on stock prices.** These two thresholds are not subjectively set but come from large-sample statistical backtesting of A-shares from 2005 to the present. **The significance of 30% growth** is reflected in multiple dimensions: For stocks whose annual gains ranked in the top 10% of the market, the median growth rate of net profit deducting non-recurring items averaged about 30% from 2010 to 2026; 30% is also the watershed between value investing and prosperity investing—when growth exceeds 30%, the theoretical valuation level corresponding to the DCF pricing model is extremely high, valuation constraints basically fail, and the market prices mainly based on prosperity; once growth falls below 30%, valuation levels once again become a key factor affecting expected returns. **The significance of a -50% decline in growth** is equally clear: Statistical grouping of stocks with previous year growth exceeding 50% that are currently decelerating shows that targets with a growth decline of less than 50% can still maintain good performance, while those with a decline exceeding 50% see significantly lower returns. It is worth noting that the higher the base of previous growth (e.g., exceeding 100%), the higher the market's tolerance for deceleration, and the above threshold can be appropriately relaxed to 60%. ## Four Types of Sectors: Different Logics for Identifying Top Signals GF Securities points out that 30% and -50% are probabilistic laws in a statistical sense, and judging the peak of specific sectors requires combining the dominant pricing models of each segment. The report categorizes historical prosperity sectors into four types. **Prosperity Realization Type** takes the weakening of earnings momentum from strong to weak as the core signal, focusing on tracking g (earnings growth rate) and Δg (rate of change in growth). Typical cases include power batteries from 2020 to 2022 and semiconductor design from 2019 to 2020—CATL's forward valuation peaked before its stock price, with earnings growth halving closely following the stock price top; GigaDevice showed characteristics where earnings growth halved, and the stock price top and valuation top were basically synchronized. **Capacity Reversal Type** also focuses on Δg, but high supply elasticity means earnings may present a double-top structure. Taking Tongwei Shares as an example, the first significant slowdown in growth was followed by a valuation top, but earnings subsequently accelerated again, sending the stock price back up; it was not until the second continuous decline in growth that the trend turned into a clear correction. For such sectors, a single trigger of halving growth does not necessarily mean the end of the rally. **Space Pricing Type** has a top signal where long-term expectations stop being revised upward. Current earnings in these sectors are insufficient to reflect long-term value, and the market mainly trades on user growth, order space, and long-term earnings, with stock price tops synchronizing with Forward PE highs. Mobile internet and semiconductor equipment are typical cases—stock price tops for Naura Technology and Hithink RoyalFlush synchronized with forward valuation tops, while the decline in current earnings growth lagged significantly. **Stable Compound Interest Type** peaks usually accompany a simultaneous slowdown in earnings growth expectations and valuation contraction, requiring comprehensive judgment rather than reliance on a single indicator. Taking the Mao Index in 2021 as an example, both the valuation top and the growth deceleration slightly led the stock price top. ## US Stock Review: Rate Hikes Are Not Scary, But Prosperity Inflection Laws Still Apply By systematically reviewing four historical cases of US stocks, GF Securities verified the cross-market applicability of the above laws and distilled three conclusions. The **1980 US Energy Bubble** was a typical case of prosperity investing: The EPS growth peaks of companies like ExxonMobil and Chevron led stock price tops by about 2 to 3 quarters, with stock prices continuing to rise during the period of high growth oscillation, until the trend ended only after rapid growth decline (falling below 30% or halving). The **1989 Japanese Real Estate and Semiconductor Bubble** presented another form: Sharp policy U-turns (continuous rate hikes, loan restrictions, land value tax, etc.) combined with external shocks caused the stock price highs of listed companies like Sumitomo Mitsui Financial Group and Mitsubishi Estate to basically synchronize with earnings highs. This is similar to the situations in A-shares in 2015 and Korea in 2026—exogenous shocks may cause stock price tops to appear earlier than or simultaneously with growth tops. The common features of the **2000 Dotcom Bubble and the 2008 Subprime Mortgage Crisis** were: Stock prices of companies like Cisco, Lucent, and Microsoft continued to rise during periods of high earnings growth oscillation, with continuous rate hikes finally bursting the bubble; earnings growth of companies like Bank of America and PROLOGIS REIT also peaked before stock prices, but continuous monetary tightening was the true terminator. The report concludes that rate hikes themselves are not scary, but caution is needed in the middle to late stages of hiking cycles, because one of the common factors in every bubble burst is that continuous rate hikes ultimately lead to a turnaround in the macro environment and corporate earnings. The US stock market also exhibits statistical laws regarding prosperity inflection points: Returns drop significantly when growth falls below 30%, but this law has weakened since 2010—possibly due to abundant macro and market liquidity in recent years, and share buybacks by listed companies smoothing out some volatility. ## Current AI Sector: Prosperity Is Ongoing, But Differentiation Will Intensify Returning to the core question of the current market: Where does the AI sector stand? **GF Securities' judgment is that the AI industry prosperity cycle is still ongoing.** According to a Microsoft report, global AI penetration in the first quarter of 2026 was 17.8%, with 31% in the US, 31% in Germany, and 16% in China. Referring to the development laws of the PC and internet industries, penetration needs to reach 40% to 50% to potentially trigger a prolonged stagnation in stock prices; current overall penetration remains significantly low—especially in terms of formal deployment into production environments. Meanwhile, tech giants' CAPEX expansion continues. The team further pointed out that even if core AI assets experience a marginal slowdown in the second derivative of earnings growth (corresponding to phase-based highs in apparent valuations), it does not mean the appearance of a prosperity inflection point; industry strength and penetration will continue to support EPS and stock prices. This means that the required granularity of research on the AI sector is increasing. 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