So far this year, the structural characteristics of the A-share market have been quite distinct. Sectors like optical modules and chips within the AI hardware technology track have shown sustained strength, while the commercial aerospace sector, also a high-growth technology area, has experienced a relatively divergent trend. After an initial surge, the sector has recently entered a phase of consolidation and adjustment. Addressing key investor concerns such as the divergent logic between these two popular technology tracks, valuation debates surrounding the AI sector, and the market outlook for the second half of the year, Great Wall Fund manager You Guoliang recently provided a professional and detailed analysis in a live broadcast.
In You Guoliang's view, the core reason for the significant divergence in performance between the AI hardware and commercial aerospace sectors lies in their different stages of industrial development, which directly leads to a fundamental difference in the pace of earnings realization. Since the launch of ChatGPT at the end of 2022, the AI industry has experienced nearly four years of rapid development, with its industrial scale continuously expanding. It is currently in a main upward phase driven by global capital expenditure, ample orders, and ongoing profit release, exhibiting relatively strong earnings certainty. In contrast, China's commercial aerospace industry is still at a critical inflection point for reusable rocket technology verification, belonging to the early stages of industrial development. The overall industry scale is relatively small, technological iteration faces setbacks, and it has not yet entered a profit release cycle. Its market performance is primarily driven by industrial expectations, resembling the overall development stage of the AI industry several years ago. Market capital naturally prefers targets with greater earnings certainty, thus forming the current pattern of divergent performance between the two technology tracks. This stage-specific difference is expected to change as the commercial aerospace industry gradually matures and delivers on its promises.
Regarding the current market divergence over AI sector valuations—where some investors believe core stocks' gradually realized earnings support valuations, while others see signs of crowded trading and emerging bubbles in certain segments—You Guoliang believes these views are not contradictory and accurately reflect the sector's current reality. From the perspective of core leading stocks, the industry continues to benefit from global investment in computing power capital expenditure, with ample orders and steadily releasing profits providing solid fundamental support for valuations. However, from the overall sector perspective, the prolonged strong performance has attracted massive capital inflows, leading to crowded trading in most segments, with localized valuation bubbles possibly already emerging. He pointed out that the core focus for observing the AI sector lies in judging the sustainability of the industry's high-speed profit growth, which will be key to its future performance trajectory.
Looking ahead to the second half of the year, You Guoliang believes that technology growth is still expected to be a core theme. Industry prosperity in key areas such as AI computing power, optical communication, and memory chips is likely to remain high. However, after sustained market performance, trading congestion has increased significantly, and the overall investment value proposition has notably decreased compared to the beginning of the year. Subsequently, the sector may move away from broad-based gains and enter a phase characterized by selective stock picking and increased volatility. He suggests that a spillover effect of AI-related capital may occur in the second half, with funds potentially gradually flowing from crowded, high-valuation AI infrastructure tracks towards the AI application end, as well as towards high-quality growth tracks that are at lower valuations and nearing intensive catalysts, such as commercial aerospace. Investors could focus on the upgrade opportunities as the AI industry deepens its implementation from the infrastructure end to the application end, as well as the opportunities for positioning in new quality productive force tracks like commercial aerospace at relatively low levels. Simultaneously, he also cautions investors to be vigilant regarding risks such as overseas liquidity and geopolitical disturbances, crowded trading in popular sectors, and changes in industrial narratives.
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