Don't believe the AI bubble theory too soon! Chen Guo: The biggest "upside surprises" in 2026 will all be in the Chinese market.

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What will truly drive the A-shares in 2026 is not bubbles or sentiment, but three major positive surprises: China's profitability, China's technology, and China's strength. Click for the replay→AI Bubble Concerns & Bull Market Playbook | 2026 Outlook·Issue 3

Core Viewpoints OverviewCurrently, AI is not on the eve of a bubble burst, as none of the three major conditions have been met. Valuations have not reached extreme levels, liquidity has not been continuously tightened, and technological iteration has not peaked—the bull market is still on the way, “no bull market without a bubble.”A-shares are unlikely to completely break away from overseas influence in the short term, but China’s own industry and internationalization are increasing independence. US stock valuation and liquidity volatility will still be transmitted, but the proportion of Chinese companies' overseas revenue continues to grow, and “global vision” will become key to A-share pricing.The three most important surprise factors for 2026: enterprise profit recovery, changes in the AI competitive landscape, and enhanced international cooperation. These surprise factors are clear in direction, but not yet fully priced by the market, and will be underlying drivers of next year’s market.The most overlooked surprise factor by the market: China’s AI applications may be the first to commercialize and to prove “economic efficiency.” Chinese AI has competitive advantage in cost efficiency, edge AI, application scenarios, and electricity costs, which could make its commercialization pace much faster than market expectations.Liquidity in 2026 may bring “positive surprises.” Mutual funds may shift from net redemption to net subscription, high-net-worth individuals may increase equity allocation, much time deposits maturing next year will release incremental funds, and foreign capital is also expected to return to net inflow.There is more than one main industry theme next year: AI (A), Biotech (B), Commodity (C)—three themes running in parallel. Computing power diffusing to applications, pharmaceutical innovation combined with AI efficiency, and commodities seeing structural opportunities under “tight supply + global easing.”

Q1: After volatility in leading US tech AI stocks, everyone asks: Has AI gone too far? Do you think AI is in a bubble now?

Chen Guo: I’ve always believed, “No bull market without a bubble.” If the market is always priced fully rationally, it’s hard for a true bull market to appear. The key is not whether there is a bubble, but—when does the bubble burst.

When I judge if the bubble in a tech bull market will burst, I use a formula with roughly three conditions:

First, valuations must be at “severe highs.” At present, the representative indices like the Magnificent Seven, NASDAQ, S&P still have restrained PE ratios, about 20-30 times. Compare to when the internet bubble burst, many companies had 100, 200x valuations; Cisco then was a bit like Nvidia now, Amazon was like today's OpenAI—no actual profit, so PE wasn’t applicable. If valuations are only moderately high, it’s hard to form a bubble burst.

Second, liquidity must be continuously tight. This includes ongoing rate hikes or notable tightening at the micro level. US stock downturns in 2000, 2007, or A-shares in 2015, a key factor was tightening liquidity combined with high valuations.

Third, technological iteration slows, or revenue growth shows a “predictable peak.” Not just this year's growth peaking, but the market can foresee growth peaking in the next year or two, then it's hard for valuations to keep rising.

Currently, none of these three conditions are met. So I think, “bubble forming” can be discussed, but “bubble burst” is far away.

If you use the strictest valuation metrics, of course you can say “this is a bubble”—for example, OpenAI is not profitable, you can’t even talk about PE. But I’ll say it again: No bubble, no bull market. And based on valuations, liquidity, and tech cycle, none of the conditions for a bubble burst are present.

Q2: Overseas fiscal stimulus, tech regulation, interest rate path are changing. How will these external risks transmit to domestic markets?

Chen Guo: As domestic market investors, we’d ideally hope for an “independent rally,” not affected by overseas conditions. But in reality, up to now, A-shares—especially tech, HK stocks, and US stocks—are still closely linked, and changing this paradigm takes time.

Logically, the core driving force for A-share gains now is still technology and internationalization. Globally, AI industries are highly concentrated, with the US still leading many sectors in AI. So it serves as a reference for industry judgement and valuation here, impacting us too. If US Fed actions and liquidity changes affect US tech stock valuation, it’s transmitted here as well.

We’ve actually enjoyed this benefit before: when overseas valuation soars, we get a matching boost. But when they adjust down, we’re not immune. In reality, A-shares don’t benefit enough, and react quicker on corrections. So, we need to seriously assess: where are the valuations of relevant Chinese sector companies, and how strong is market recognition? If a company's intrinsic value is strong enough, with safe valuation margins and strong market confidence, then in theory overseas liquidity/valuation swings have less impact on us. However, overall market confidence is not that strong yet.

Another key point: lots of companies in A-shares have a significant proportion of overseas revenue. Main indices show about 20% overseas income, with profit proportion even higher; some sectors have profit ratios near or over half. So, if the US AI industry goes down, dragging US and global economies, it will affect these Chinese companies—even if they're not AI firms themselves, being part of an international environment, they're still impacted.

Thus, in this bull market, Chinese investors must have a global perspective—assessing: Where is global industry positioned? Where is the global bull market in its cycle? Of course, we hope that China will lead in some areas of AI, and won’t always be priced after the US. But I think this process will unfold gradually only after 2026.

Q3: You mentioned “three major surprise factors” for next year’s market in your report—Could you recap those quickly for us?

Chen Guo: From last year’s bottom, we’ve always been strategically optimistic. The market rose from over 2,600 points to near 4,000 this year, a big surge, not to mention some tech indices. So naturally, the market asks: Are all the positives “priced in,” what will drive growth going forward?

My view is: there are at least three directions that could outperform current mainstream expectation.

The first surprise factor is corporate profitability. From 2022 to 2024, listed company profits were notably below expectations, one main reason for that bear market. Major indices' corresponding company profits were basically negative growth—though GDP was ~5%, profits were negative.

This year is different: so far profits are positive and not below expectation. Market expectation for profits next year isn’t high; I think they could beat. Core reason isn’t just total demand recovery, but changing industry supply-demand: Most sectors' structure is improving, listed firms' capex is clearly down (even negative growth), construction in progress growth rate is near zero, fixed asset investment is markedly reined in. As long as revenue is growing, shrinking supply benefits leading firms, and ROE rises.

If this is supplemented with “anti-involution” and supply-side optimization policies, that's even better—but even without strong administrative pushes, many firms are reducing supply/stressing efficiency on their own, and this will show in profits next year and the year after.

The second surprise factor is the internationalization dividend for Chinese firms. Next year, China’s global expansion dividends may be more prominent. Major global economies are mostly in “easy money + easy fiscal” mode. US economy looks good this year, but a lot relies on AI capital expenditure, the other half is weak. If further rate cuts or fiscal support follow, there’s still rebound room.

In this environment, many Chinese firms continue to grow overseas market share. Fears of trade war haven’t reversed this trend. Even with a “Trump 2.0” raising tariffs, the levels vary, aren’t fully suppressive compared to some allies. Overall, China’s competitiveness in global trade is strengthening, ultimately reflecting in listed company profits.

The third surprise factor is the competitiveness of Chinese AI, as well as broader geopolitical issues. In 2024, people worried China would lag behind in AI; in 2025, there's growing confidence we can keep up; I think by 2026, there will be increasingly more evidence showing we are ahead in many respects.

If you look just at large model scores, some platforms' highest marks may still be US models, but Chinese large models are highly efficient—using a fraction or even several percent of the cost, achieving scores close to top US models. The future isn’t just about the model itself, but entering the phase of AI agents and various application scenarios—here China’s cost-efficiency advantage will emerge in commercialization.

In the end, business competition is about economics, not merely technical edge. Whether it's edge AI (AI phones, glasses, robots), or infrastructure like electricity supply, our cost and supply advantage can’t be easily matched by the US in the short/medium term. So in AI application commercialization, China's cost-performance advantage will become more prominent, and this edge will be gradually revalued in next year's market.

These factors are currently only vaguely felt in the market and are hard to price precisely—How much will profits beat? How far ahead will AI get? Which sectors will US-China expand cooperation? So they form a clear-direction but hard-to-quantify “surprise factor portfolio”, to be realized gradually in 2026, with the market constantly repricing during the process.

Q4: Of the three surprise factors, which do you think is most underpriced by the market right now?

Chen Guo: I think the most underpriced is China’s potential leadership in AI.

This circles back to our original topic—the current paradigm is still that the US absolutely leads in AI. When the US worries about an AI bubble, concerns about disproportionate returns, excessive capital expenditure, or slow business rollout, our stock prices drop too, since we default to “follower” status.

But if, in the future, the market gradually sees: China’s economic efficiency advantage in AI applications and faster commercialization, the narrative will change. For example: US AI capex doesn’t pay off, but Chinese AI application economics are much better and profitable; US releases profits slowly, but China’s are realized earlier.

Within the current paradigm, this is obviously underpriced, and the upside for this surprise factor may be huge. Corporate profits may also beat, but that surprise might not be enough to change the whole story; whereas if the market truly recognizes and re-prices China’s AI application advantage, it can change the “main storyline” of the US-China bull market. So, I think this is the most important and easily overlooked surprise factor.

Q5: What micro-level liquidity changes are most worth watching for 2026?

Chen Guo: The core is still micro-level liquidity, that is, whether incremental funds are really flowing into stocks.

This year incremental funds did flow in, but not to an obvious degree. Reason: It’s the first year of the bull run, starting cautiously amid doubt. From asset allocation perspective, people’s mindsets take time to change. Historically, incremental funds often become obvious in year two of the bull market.

Also, China’s funding structure is layered, with a distinction between high-net-worth and middle-class. This year high-net-worth money did come in, but mainly via bank wealth management, “fixed income plus,” insurance, etc., not necessarily directly into stocks. The middle class was enthusiastic about mutual funds between 2019–2021, but now is hesitant and still in a “break-even” mindset: as soon as they break even, they redeem, so mutual funds are still in net redemption.

If the market continues steadily, with lucrative windows, and ongoing “beat expectations” events to bolster confidence, first step is mutual funds shifting from net redemption to net subscription. Looking at mutual fund indices, they’re still ~15% below historic highs; if another new high comes, the “break-even redemption” pressure evaporates and brings true net inflow.

For high-net-worth money, they don’t seek very high returns—they care about Sharpe ratio (return vs. volatility). Of major global assets this year, the Shanghai Composite has one of the highest Sharpe ratios: not the biggest gain, but very low volatility—very steady, unlike the sharp rallies of 2024. If you combine returns and volatility, Shanghai Composite is a better pick than gold, bonds, or many overseas indices. This will draw high-net-worth money to further increase equity allocations.

Another key time point: lots of time deposits mature in Q1 next year, and upon renewal, rates will be much lower, forcing funds to seek new allocation channels—so incremental fund flows into stocks have a foundation.

Finally, a “bonus” is foreign capital. Since 2022, foreign funds haven't clearly been net inflow. I think in 2026, there's a good chance net inflows will resume: profits shifting from “underperforming” to “on target” to “about to beat”; US-China relations are relatively stable; global AI investing should cover both US and China. Plus China’s latent advantage in AI applications—in theory, foreign capital will be motivated to increase China equity allocations. This variable is less certain, but overall, I’m optimistic that next year’s incremental money flow will bring real “surprises.”

Q6: Among the major themes like growth, cycles, consumption, which sectors should be tracked most closely?

Chen Guo: Firstly, I agree with your premise—there won’t be just one main line, many directions have opportunities.

From a capital angle, incremental funds have their own “taste.” Sector trends and price surges are highly tied to incremental funds’ preferences. In the past, money structure was more single-layered, but next year could include foreign, high-net-worth, middle-class, private funds, public funds, proprietary trading—many levels of funds entering, so market style will be more “diverse.” In such a setting, we need to look at both fundamentals and valuation.

Based on fundamentals, my allocation for next year can be summed up as three letters: A, B, C.

A for AI. AI remains the dominant industry clue; just the sector and stock “centers of gravity” are shifting. Previously the market focused on the computing end, like Nvidia; now gradually on the application layer, like Google, and this will keep evolving. The center of gravity will shift from computing to applications; the true “AI blue chip” may not be a conventional tech firm, but could be a traditional enterprise leveraging AI for much higher profit margins and market share—such companies could become the new core assets.

B is Biotech. In a rate-cutting cycle and China's accelerating internationalization, Biotech is another important theme besides AI. Globally, aside from tech companies, only large pharma companies reach trillion-dollar scale. China’s gap here is narrowing, and prospects are big. With AI boosting pharmaceutical and biotech R&D efficiency, China’s edge in cost, value, and efficiency will be obvious; this sector is also a key focus.

C is Commodity. On one hand, AI itself demands a lot of infrastructure investment; on the other, global stimulus and liquidity are loose, and supply for many commodities—especially niche metals—has been tight recently. So under “tight supply + easy money + new demand,” commodity-related sectors will have many opportunities.

Of course, in practice, next year’s market may be characterized by high rotation, strong divergence. You can’t rely totally on subjective guesses about which sector is strongest, you need lots of fundamental and quantitative data for dynamic adjustment. We ourselves use sector rotation models, maybe Q1 is A-style, Q2 is B-style, Q3 cycles back to an old style—this is likely.

If you can’t closely track sector rotation, the simplest approach: Pick some indices or representative firms from each of A, B, C for structured allocation—that’s a strategy I suggest for next year.

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