The recent K-shaped divergence within domestic markets is heavily influenced by short-term narratives and capital flows, necessitating attention to the potential recovery of certain non-AI sectors once speculative fervor subsides.
Three Narrative Logics Underpin Three Layers of K-Shaped Divergence
The K-shaped divergence observed globally has been intensified by prevailing market narratives, which can be broken down into three key strands. The first is the global divergence between AI and non-AI sectors, amplified by a strong US dollar and interest rate hike expectations. This divergence, stemming from differing business cycles and thus varying sensitivity to interest rates, has a rational basis and is a common phenomenon worldwide. The second is a narrative unique to the A-share market, pitting "carbon-based" against "silicon-based" industries, which has caused A-share non-AI sectors to significantly underperform their international peers, even when operating similar global businesses. This underperformance is driven by the impact of weak domestic demand data on investor sentiment, leading domestic investors to scrutinize non-AI stocks with stricter criteria. The third strand, emerging since June, is the outperformance of domestic AI stocks relative to the global AI sector. This is not merely a spillover effect from the North American AI supply chain's strength but includes a valuation premium for domestic supply chain autonomy, a catch-up for previously lagging segments, and capital flows influenced by adjustments in quantitative and index-enhanced strategies.
Domestic AI's Independent Strength
This trend is driven by both industrial narratives and portfolio adjustments by quantitative strategies. Quantitative stock selection and index enhancement strategies are facing pressure from both performance and fund flows, necessitating portfolio adjustments. Data shows a significant decline in the average excess returns of such products in the first half of the year compared to the same period last year. This slump in excess returns creates redemption pressure, potentially forcing managers to adjust their strategies.
Accurately capturing excess returns in the current market requires exposure to a "ChiNext and STAR Market factor." The recent sustained correction in micro-cap stocks is one reason for the decline in excess returns for quantitative products. While the Wind Micro-cap Stock Index has fallen significantly since mid-May, the STAR ChiNext 50 Index has risen, creating challenges for strategies exposed to micro-caps. The extreme divergence across sectors means traditional broad-based quantitative factors could drag down performance.
Differences in holder structure mean that adjustments towards this "dual-innovation factor" have a more pronounced effect on the STAR Market. Institutional ownership is significantly higher in ChiNext index constituents compared to the STAR 50 index. ChiNext core stocks are held more stably by institutions like mutual funds, making their holdings "stickier." In contrast, the STAR Market has a higher proportion of retail investors and ETFs, leading to greater price elasticity from marginal fund inflows and stronger amplification of price movements by sentiment. This is reflected in higher turnover and volatility on the STAR Market. The outperformance of the STAR Market over ChiNext, and its clear outperformance over markets like South Korea and the US, narratively translates to the domestic AI supply chain significantly outperforming the North American AI chain.
Rising Proportion of Index-Enhanced Funds with Positive Excess Returns
Adjustments by quantitative strategies are gradually progressing. Analysis of a sample of public fund index-enhanced products shows that the pace of excess return accumulation was similar to last year until mid-April, after which it began to significantly underperform. This divergence point coincides with the intensification of the K-shaped split. The extreme AI/non-AI divergence weakened the effectiveness of traditional quantitative factors, impacting portfolio returns and forcing adjustments. However, since mid-May, the average cumulative excess return of these funds has gradually recovered, even surpassing its previous high for the year. Looking at monthly averages, the proportion of products achieving positive excess returns has increased from April through July. Overall, the absolute level of negative excess and the proportion of products affected are decreasing monthly, reflecting active portfolio adjustments by many funds, which in turn exacerbates the K-shaped divergence.
Post-Speculation Cooling Warrants Focus on Recovery in Some Non-AI Sectors
Since March, three narrative strands have fueled three layers of K-shaped divergence. While some divergence is rational and common globally, extra effects from sentiment and capital flows are also present. As more products complete their passive adjustments, the impact of sentiment and capital flows will diminish. After this speculative capital game cools down, attention should turn to the recovery potential of some non-AI sectors. Regarding specific allocations, within the AI sector, preference leans towards segments with strong supply constraints, lower valuations, and those偏向中下游, such as cloud providers, storage, servers, gas turbines, and diesel generator sets. For non-AI sectors, selections include certain base metals, new energy (awaiting digestion of negative industry sentiment and a return to objective performance), and chemicals. Furthermore, continued看好 is expressed for innovative drug companies with sustained overseas expansion logic and relatively cleared positioning. The recently updated national essential drug list could provide a significant positive catalyst. Undervalued securities firms remain看好, with headwinds like liquidity pressure expected to gradually ease in the second half. Short-term logic can focus on investment returns and mid-year earnings, while the long-term logic involves the overseas expansion and globalization of brokerage业务 driven by a broader wave of overseas investment and financing by Chinese enterprises.
Risk Factors
These include escalating Sino-US friction in technology, trade, and finance; domestic policy effectiveness or economic recovery falling short of expectations; unexpected tightening of domestic and international macro liquidity; further escalation of regional conflicts; and slower-than-expected digestion of China's real estate inventory.
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