A-share second half under continued AI main line: valuation restructuring and diversified strategies go hand in hand
Introduction
In the first half of 2026, the A-share market showed distinct structural characteristics: funds were highly concentrated in the AI industrial chain, and the performance gap between tech and non-tech sectors continued to widen. This phenomenon not only reflects the frontier direction of industrial change but also raises concerns about valuation bubbles and crowded trades. Entering the second half, market focus shifts to several questions: Can the AI rally continue? Will funds diffuse to manufacturing, healthcare, consumer, and financial sectors? Facing a highly differentiated market environment, how should investors construct effective investment strategies?
At the recent Navigator Institutional Strategy Meeting held by JP Morgan Asset Management, multiple fund managers and strategy experts delved into these topics, offering valuable insights for investment allocation in the second half.
AI remains the main line; investment shifts to earnings verification
Du Meng, Vice President and Investment Director of JP Morgan Asset Management China, pointed out that the current market is mainly pricing based on industry growth momentum, and AI remains the "greatest common divisor" of global tech industry. For second-half allocation, he clearly stated: first, grasp the AI main line, and on this basis, look for investment opportunities in energy, innovative drugs, and other areas based on growth momentum and valuation attractiveness.
Notably, Du Meng also gave forward-looking judgments on longer-term industry directions. He believes that commercial aerospace and embodied intelligence, while still in very early stages and lacking clear earnings or market demand validation in the short term, are worth allocating research resources to if viewed over two to three years or even longer.
In terms of specific industry chain evolution, overseas and domestic AI development show different characteristics. Overseas AI has moved from the concept fermentation and R&D investment phase to the substantive phase of computing power expansion, large model commercialization, and core supply chain profit release; while domestic AI is transitioning from technology catch-up and thematic trading to a new phase of domestic computing power chips, large model ecosystem construction, and supply chain earnings delivery.
Specifically regarding investment focus areas, optical communications, PCB, power supplies, liquid cooling, storage, advanced packaging, and semiconductor equipment and materials remain key sectors, while front-end AI, smart driving, and robotics can be closely watched. In terms of allocation strategy, Du Meng suggests distinguishing between stable core holdings, high-elasticity segments, and frontier themes, and dynamically adjusting based on valuation levels and changes in supply-demand dynamics.
Li Dehui, Senior Fund Manager at JP Morgan Asset Management China, is also optimistic about AI but emphasizes that we cannot just discuss the bubble; we need to observe real orders, capital expenditure scale, and whether a commercial closed loop has formed. Facing rapid rotation among sub-segments, he prefers to choose leading companies with high earnings certainty and reasonable valuations, while staying relatively restrained on price-inflated segments that the market has fully priced.
In Li Dehui's view, AI still has relative advantages at this stage, but increased volatility after excessive fund concentration is normal. As the market evolves further, it may gradually move toward equilibrium in the third quarter, when allocation value of cyclical and high-end manufacturing sectors may re-emerge.
Non-AI assets repricing: large manufacturing and undervalued growth attract attention
Under extreme market divergence, some fund managers are turning their attention to overlooked areas in search of potential investment opportunities.
Li Bo, Head of the Balanced Growth Group and Senior Fund Manager at JP Morgan Asset Management China, summarizes his investment framework as using PEG (Price/Earnings to Growth ratio) to constrain valuation and growth, focusing on companies with high future earnings growth and reasonable valuations. In his view, some companies' stock prices have fallen from the beginning of the year, but earnings expectations have not been significantly revised down; as earnings certainty improves, their expected returns have actually increased.
In the consumer sector, Li Bo focuses on sub-segments like snack vending, gaming, and frozen foods that have shown earnings growth validation; in the new energy sector, lithium batteries have dual logic of both sales growth and unit profit improvement. In high-end manufacturing, companies with global competitiveness, such as automobiles and construction machinery, are also worth investor attention.
Ni Quansheng, Senior Fund Manager of the Balanced and Value Group at JP Morgan Asset Management China, believes that the purpose of balanced investing is not diversification for diversification's sake, but to find assets that can "exchange time for space." He continues to favor the direction of manufacturing going overseas, believing that industries such as machinery, electrical equipment, ships, automobiles, nonferrous metals, and chemicals are transitioning from simple commodity exports to a comprehensive layout including overseas factory construction and building channels and service systems.
Ni observed that for some traditional manufacturing industries, the peak of capital expenditure has passed, free cash flow continues to improve, and coupled with an increase in global market share, these companies may become new core assets at this stage. He judges that among domestic asset classes, stocks still have strong appeal, but the definition of core assets is changing, with large manufacturing and some tech companies likely to replace traditional core assets.
Wang Rui, Fund Manager at JP Morgan Asset Management China, summarized this year's market as a rare "K-shaped divergence" between AI and non-AI sectors. In her view, fund structure, interest rate expectations, and AI industry trends together amplified the suction effect, but the expectation of "new industries replacing old ones" is often overly linear extrapolated by the market.
In sectors such as brokerages, insurance, and consumer, some companies have seen a divergence between fundamentals and stock prices. As selling pressure eases and pessimistic expectations are fully priced in, low-valuation assets in finance and consumer sectors may see repair opportunities. Wang emphasized that consumer demand will not disappear, and future investment opportunities will shift more toward service consumption, corporate going overseas, and high-value consumption.
From balanced to quantitative: multiple strategies to cope with high divergence
In a highly divergent market environment, how to reduce exposure risk from a single asset became another main thread discussed at the strategy meeting.
Hou Jie, Head of Multi-Asset Hybrid Investment at JP Morgan Asset Management China, believes that investment methods will change as market maturity increases. Investment strategies that rely solely on valuation advantages, information advantages, or high-frequency marginal changes may decline in long-term effectiveness. In his view, the future is more about returning to common sense and the company itself, pricing companies through business model analysis, corporate governance assessment, competitive barrier judgment, and long-term operational capability evaluation.
At the current stage, Hou Jie emphasizes that stock selection has become even more important. With increasing divergence among companies within industries, even in the same sector, different business models, brand channels, and operational capabilities can lead to completely different long-term returns. Therefore, his portfolio framework still includes multiple dimensions such as timing, allocation, stock selection, and concentration management, but in the current environment, stock selection ability is particularly critical.
Hu Di, Head of Index and Quantitative Investment at JP Morgan Asset Management China, stated that public fund quantitative investing is moving from a supplementary strategy in the past to a more important allocation tool. On one hand, the strengthening of performance benchmark constraints has attracted increasing attention to transparent, stable, and evaluable quantitative systems; on the other hand, quantitative strategies can improve overall investment performance by leveraging the mutual reinforcement of beta returns from growth sectors and alpha from stock selection.
In terms of large model applications, Hu Di believes that AI technology can expand the use of unstructured data and alternative factors, but cannot replace human judgment. Quantitative teams still need to use rich investment research experience to constrain models, reduce noise interference and overfitting risk, and achieve an organic combination of human experience and machine computing power.
In terms of ETFs, Bi Xue, Head of ETF and Index Business at JP Morgan Asset Management China, pointed out that ETFs are not just passive tracking tools but a trading framework that can carry different assets and multiple strategies. The growth in credit bond ETF scale also reflects a trend of some institutional allocation needs migrating from primary market and OTC products to on-exchange tools.
Xu Yin, Head of ETF and Index R&D at JP Morgan Asset Management China, stated that low-volatility dividend products are more suitable as the base and "stabilizer" of a portfolio. Meanwhile, actively managed ETFs combine active management capabilities with ETF advantages in liquidity, transparency, and cost, and may become an important innovation direction for the domestic ETF market in the future.
Conclusion
Overall, the A-share market in the second half of 2026 will continue to show high divergence. AI as the industrial main line is unlikely to be toppled in the short term, but the investment logic has gradually shifted from concept-driven to earnings verification. Meanwhile, non-AI assets long overlooked by the market, especially large manufacturing sectors with global competitiveness and valuation advantages, as well as consumer and financial sectors where fundamentals and stock prices have diverged, may see repricing opportunities.
In the current complex and changing market environment, investors need to abandon simple sector rotation thinking and adopt diversified investment strategies. Whether through balanced allocation to diversify risk, using quantitative tools to improve efficiency, or using ETFs and other tools to optimize trading structures, the core goal is to effectively control volatility risk while grasping industry trends.
With its investment philosophy combining global vision and local practice, JP Morgan Asset Management strives to offer investors more forward-looking and robust investment choices. Currently, JP Morgan Fund's active equity investment team covers growth, balanced growth, and balanced and value styles. As of the end of April 2026, JP Morgan Fund's stock investment ability has received five-star ratings from Guotai Haitong Securities for three-year, five-year, and ten-year periods. Wind data shows that as of the end of May 2026, 12 of JP Morgan Fund's active equity funds have achieved annualized returns exceeding 10% over the past ten years, achieving "double-digit" performance through bull and bear markets, providing investors with reference long-term allocation examples.
