China Galaxy Securities: Domestic AI bubble risk can be controlled, recommend focusing on Hong Kong Stock Technology Giants and AI application chain.
It is recommended to focus on the continuous increase of AI investments in Hong Kong stocks related to core Internet assets, as well as on AI applications and related sub-sectors that are continuously deepening AI empowerment.
China Galaxy Securities released a research report stating that the current artificial intelligence wave is not the "irrational bubble" of the internet era, but rather the result of the multi-dimensional effects of national strategic planning, enterprise development layout, and market sentiment driving. Compared to the rapid expansion of capital spending by overseas technology giants, domestic companies face restrictions on imported resources such as computing power, creating domestic demand for alternatives. With the support of the vast domestic market, the bank believes that the risk of an AI bubble in China is more controllable. It is recommended to focus on increasing investment in core assets of Hong Kong-listed Internet companies and related sub-sectors of the AI application and industry chain where AI empowerment is deepening.
Key points from China Galaxy Securities:
Comparison of artificial intelligence and internet waves: Focus on mature companies, commercialization gradually opening for validation
During the internet bubble period, the IPO market was exceptionally prosperous, with some companies' valuations seriously disconnected from their fundamentals. Many unprofitable or even zero-revenue companies received high valuations, with the valuation system seriously detached from the fundamentals. In this current AI wave, AI startups rely more on abundant private financing, while market funds focus on a few mature companies with good operating conditions, making risks relatively controllable.
Higher visibility of business models in the AI wave
The visibility of business models in the current AI wave far exceeds that of the internet bubble, mainly because there has been a significant change in the supply-demand structure. From the supply side, in the internet era, the concept of supply was lacking in solid barriers and was highly speculative, leading to serious excess capacity and later collapse. In this wave of AI, the supply comes from top technology giants with a certain capital, the best talents, and solid technological capabilities, providing high and scarce technological barriers. From the demand side, the internet era had a broadband penetration rate of less than 19% and e-commerce accounted for only 0.5% of the entire retail industry, with a significant mismatch between supply and actual demand; In the AI era, there are three advantages: 1) Enterprise-level users are the main demand force; 2) Demand is concentrated in fields with relatively sufficient capital; 3) Through the digitalization process of the past 20 years, various industries have generated a significant demand for data processing, forming relatively complete business models. AI can quickly empower enterprise production and operations, thereby achieving rapid value realization.
Accelerating scale expansion, cloud business constructing performance support for AI
Since 2020, the four major US internet giants have continued to increase their capital spending and research and development investment in the AI field, focusing on infrastructure construction and technological innovation; Chinese leading technology companies have also followed the AI industry trend and accelerated their related layout under policy support. Compared to the high capex growth rate of US giants, the overall capital expenditure growth of Chinese companies is more restrained, reflecting the complexity of the Chinese market environment and the flexibility of enterprise strategic adjustments. The rapid growth since 2024 marks the entry of the Chinese AI industry into the stage of scale investment.
Risk warning: Risks of increased external uncertainties, short-term adjustment risks of market sentiment and capital flows, and risks of AI technology and application development falling short of expectations.
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