AI Revolution, Geopolitical Order Restructuring, Weakening Dollar Credibility—Why Are the "Three Major Narratives" Dominant?

In the traditional market analysis framework, we usually focus on three core driving factors: fundamentals (real macroeconomic conditions, industry cycles, corporate earnings, etc.), risk appetite (policy shifts, events, etc.), and liquidity (capital flow magnitude, structure, and crowdedness of trades). Among these, fundamentals have long remained at the core, as they directly impact the numerator side (corporate earnings expectations) and also the denominator side, influencing market sentiment and risk appetite, while also affecting the liquidity environment through monetary policy.

However, in the past two years, we have noticed that the market is increasingly dominated by narrative, exhibiting several distinct characteristics:

First, divergences between the market and fundamentals occur from time to time, and market volatility may far exceed the degree of change in fundamentals, or even move in the opposite direction;

Second, global capital reallocation tends to amplify the power of narratives, and capital flows often exhibit trends of convergence, easily leading to crowded trades;

Third, volatility increases significantly, and often displays nonlinear characteristics, whereby even minor events can trigger sharp market swings;

Fourth, the correlation between different asset classes changes; traditionally, stocks, bonds, commodities, and exchange rates have been driven by different factors, often with low or even negative correlations, but when narrative dominates the market, this low correlation between assets is broken, increasing the complexity of asset allocation and risk hedging.

Why has narrative become the major force in the market? We believe the key lies in the transmission chain of "AI revolution, reshaping of geopolitical order → narrative interpretation → AI-based dissemination & attention scarcity → influx of capital," which has created reflexivity in the AI era.

First, the current three major global narratives—AI revolution, reconstruction of the geopolitical order, and weakening of dollar credit

Narratives can be seen as minor or grand. History is full of minor narratives, such as the "Internet Plus" initiative around 2015, which affected some tech stocks, and the "new energy" theme in 2021, which boosted related sectors. The influence of minor narratives is usually limited to specific assets or local areas, and their effect is typically short-lived. Once the narrative weakens, it fades quickly. Currently, however, we are facing three super narratives whose scale and complexity are unprecedented.

(1) The AI revolution is a Kondratiev-wave-level mega cycle, enough to overshadow many smaller economic cycles, far beyond the explanatory domain of traditional economic cycles.

First, in terms of the current scale of investment, by 2025, the ratio of US technology companies' capital expenditures to GDP will have risen to about 1.9%, which may continue to rise above 2% by 2026, and globally, AI capital expenditure is on the rise;

Second, in terms of growth momentum, AI is not only a pure industrial contributor; through total factor productivity improvement, our previous report "AI: A New Technological Revolution Changing the World" (April 22, 2025) projects that, over the next decade, AI will contribute 0.5-1.5 percentage points to potential global GDP growth;

Third, from a macro paradigm perspective, AI is fundamentally different from previous technological revolutions; it is moving from merely assisting labor to actually replacing labor, an unprecedented depth and breadth of transformation;

Fourth, in terms of market performance, the AI revolution has brought drastic structural divergence, with the performance of the computation power/Capex beneficiaries far exceeding what traditional macroeconomics can explain.

It is foreseeable that the impact of the AI revolution will be significant, but the specific trajectory of AI transformation is still unpredictable—we do not know where the boundaries of AI development lie, what new business models will emerge, or what new scenarios and business forms will arise. The market is prone to price long-term and uncertain prospects into current asset prices.

(2) Geopolitical order reshuffling can only be deduced, not generalized.

The impact of the ongoing global restructuring of the geopolitical order is equally significant, but geopolitical information is also the hardest to predict. Our analysis of geopolitical events often relies on hypothetical deduction and is difficult to summarize into general conclusions, becoming a source of market volatility. Events such as Russia-Ukraine and US-Israel-Iran repeatedly prove the unpredictability of geopolitical incidents.

(3) Weakening dollar credit means global capital needs to find new directions for reallocation.

Additionally, narratives themselves can reinforce each other, and even minor narratives may strengthen the major ones. For instance, industries like new energy, chips, and rare earths have gained more strategic significance within the meta-narrative of geopolitical competition, rising from a simple industry cycle to a national strategic level, forming a more unified macro narrative. The integration of such narratives further strengthens market consensus.

Second, the production and dissemination of AI-era information.

In the 2015 bull market, new media accelerated information dissemination, fueling theme-driven trading; investors made investment decisions based on various opinions and stories circulating on new media, which diluted fundamental analysis.

Current AI technology has further revolutionized the way information spreads, enhancing narrative power, reducing content-creation cost, and accelerating dissemination speed. First, AI reduces the cost of content creation; in the past, writing a high-quality analytical article required significant time and effort, but now AI can produce a professional-looking analysis in minutes, causing explosive growth in market content. Second, AI can precisely deliver narratives according to algorithms and investor preferences, prioritizing the most engaging content. This, combined with new media, further accelerates information dissemination.

With information generation cost approaching zero and dissemination speed growing exponentially, grand narratives spread broader and faster, consensus forms more rapidly, and capital is driven quickly, making it easier to impact the market.

Third, investor attention is scarce.

In the era of information explosion, investor attention becomes the scarcest resource. Among thousands of stocks and countless macro pathways, what stands out must be the "grandest and most unified" narrative. Fundamentally, this forms an "information cocoon"—investors are guided by algorithms and their own preferences to only focus on certain topics and assets. Nevertheless, this scarcity and concentration of attention attracts large inflows of capital.

The above factors mutually reinforce, shaping the reflexivity of the AI era. The traditional Sorosian reflexivity refers to the bidirectional, cyclical interplay between market participants' perceptions and market reality—prices not only reflect fundamentals, but can also change fundamentals, keeping markets in a state of dynamic disequilibrium. In the age of AI, reflexivity has been amplified: narratives are cheaper, develop faster, and consensus forms more rapidly; capital inflow is more likely to create a positive feedback loop—the stronger the narrative, the more capital, the higher the price, and valuation and capital further strengthen consensus and narrative.

One case is the self-reinforcement of the AI narrative and the fundamentals of tech giants. The AI narrative drives capital into the tech sector, pushing up valuations of tech giants; high valuations enable more capital expenditures and better financing conditions, which in turn improve short-term fundamentals, further reinforcing the narrative and attracting more capital.

Another case is the prediction market Polymarket, where some participants’ trades generate probabilistic expectations, which, after being disseminated, influence market expectations and attract more related trading, thereby reinforcing market consensus.

The reflexivity in the AI era creates a powerful feedback loop, but also means that the deviation in market pricing could be greater, bringing potential risks.

First, do not mistake narrative for reality. By essence, narrative is about pricing the future, which inevitably creates divergence from current fundamentals. When the pace of real-world progress (such as energy and electricity shortages or investment return expectations) lags significantly behind narrative imagination, narrative can temporarily weaken. For instance, since the beginning of this year, the market no longer "rewards" capital expenditures of tech giants.

Second, avoid overly simplistic linear extrapolation. In a narrative-driven market, changes are often nonlinear: technology may encounter a "singularity moment" or experience diminishing returns; geopolitics can only be deduced, not generalized. These all weaken the efficacy of linear extrapolation.

Third, do not confuse short-term trading with long-term allocation. Some narratives are fundamentally correct, but that does not mean prices will rise continuously. Reflexivity amplifies price deviation; the market may have already priced in the best or worst possible scenarios, and high valuation and trade crowding become the biggest vulnerabilities. When there is a marginal change in the narrative, the positive feedback can swiftly turn negative, triggering greater liquidity shocks; buying at the peak of narrative-driven deviation may result in losses, or at least significant short-term risk.

How should investors respond to a narrative-driven market? Here are some thoughts:

First, establish a trading framework for the AI era. Do not only look at fundamental data ("the flag flutters in the wind"), but also pay attention to sentiment ("the wind moves" and "the mind moves"), which can sometimes be even more critical. A simple framework: (1) When fundamentals are weak and narrative is strong, focus more on trading opportunities; (2) when fundamentals are strong, narrative is weak, and crowdedness is low, expect a stealth bull market; (3) when both fundamentals and narrative are strong, and crowdedness is high, identify if and how much pricing deviates; (4) when both fundamentals and narrative are weak, look for opportunities elsewhere.

Second, know when to exit, or even to take the opposite side. Even if a grand narrative is correct in the long run, once consensus becomes excessive and capital overly crowded, beware the reflexivity peak. The important part is not predicting the precise top, but setting a clear exit rule. At this point, trading indicators such as valuation percentiles, capital flows, and trade structure become highly important. When trading is extremely crowded and the narrative can no longer attract incremental attention, even if fundamentals remain solid, caution is required. When valuation is digested and the long-term narrative holds, corrections may present opportunities to re-enter.

Third, keep tracking and adjusting. The key lies in marginal change; upon detecting a marginal shift in narrative, promptly adjust exposure. Key marginal changes can include: (1) policy signal changes (regulatory, industry, monetary policy adjustments); (2) significant industry information (capital expenditure verification, validation of physical bottlenecks, etc.); (3) evolving competitive landscape (new entrants, technological breakthroughs, disruptive applications, market share changes, etc.). In your tracking system, beyond market sentiment indicators like valuation, volatility, and trade structure, monitor changes in participation (are retail investors flooding in? Is the media landscape dominated by one topic?).

Fourth, narratives ultimately need fundamental validation, as fundamentals are still the long-term weighing machine and "anchor." Narratives are often not a one-shot game; usually, it's a process of "narrative - confirmation or falsification - narrative reinforcement or weakening - repeated verification." Periodic fundamental checks are key for narrative correction, and it remains crucial to monitor fundamental data. Meanwhile, apart from the AI and geopolitical narrative, always allocate a portion of your portfolio to verifiable profits and cash flows, focusing on non-narrative sectors with stable fundamentals, solid cash flow, and reasonable valuation as a hedge.

In sum, we are experiencing the overlay of the four major super narratives: the AI revolution, the reshaping of the geopolitical order, weakening of dollar credit, and China's shift between old and new growth drivers—these have become the core of our recent search for cognitive alpha. Narratives affect market sentiment and capital flows, magnifying asset price movements and even influencing fundamentals via reflexivity. In recent years, based on our judgment of the "shift between old and new drivers of growth," we concluded "bonds over equities"; now, facing the wave of the "AI revolution," we are optimistic about opportunities in technology growth. At the same time, reshaping of the geopolitical order points to national defense spending and strategic reserves, which benefit resource products and consumables, and also propel global central banks toward diversified foreign exchange reserves, benefiting precious metals.

In such an environment,

The Merrill Lynch clock framework—growth + inflation → monetary policy → asset prices—is no longer effective

Instead,

Grand narratives (the ones above) + paradigm shifts (efficiency gives way to security, monetary policy gives way to fiscal policy, etc.) + AI-era dissemination patterns → new "barbell" portfolios (world-changing technologies, non-renewable resources and consumables) + multi-asset rotation + cognitive alpha + positive correlation.

Source: Huatai Securities