E Fund AI ETF (03489.HK) Up 4.00% as Hong Kong AI Shares Rebound

NewTimeSpace News: As of 14:17 on November 10, E Fund AI ETF (03489.HK) rose 4.00% to a latest price of HK$10.660. The ETF has so far traded 547,400 units today, with turnover of HK$5.8089 million and an average price of HK$10.612; its turnover rate is 1.138%. It has gained 3.39% week to date. The net asset value per unit is HK$10.3716, and assets under management stand at HK$499 million. (Note: NAV and AUM are as of November 9; the week-to-date change is based on the close of HK$10.310 on November 6, the last trading day of the prior week.)

Hong Kong AI shares rebounded on November 10. At the midday close the Hang Seng Index was up 0.29% at 24,518.87 and the Hang Seng TECH Index up 0.70% at 4,069.03, with half-day turnover of HK$92.983 billion; gains extended in the afternoon, with the tech index at 4,090.38, up 1.23%, by 14:05. Within the sector, AI hardware and semiconductors led: Zhongji Innolight rose 10.73%, Cambridge Technology 6% and YOFC 4.95%. Large-model names advanced, with Zhipu up 11.89%, Tianshu Zhixin 9.06% and MINIMAX-W 7.06%; physical AI names gained, with Manycore Tech up 17.09%, RoboSense 6.34% and UBTech 5.62%; memory names Montage Technology rose 6.34% and GigaDevice 3.13%. Among heavyweights, Alibaba bucked the trend with a 3.44% decline. On the news front, Anthropic is pushing for an IPO next week, and Lenovo launched its Wanquan hybrid token factory brand, initially planning a 15,000-P heterogeneous computing cluster and a roughly 100MW intelligent computing centre.

E Fund AI ETF (03489.HK) is an ETF under E Fund Management (Hong Kong) tracking the FTSE Global AI Select Net Return Index. Its constituents are listed companies worldwide tied to the artificial intelligence theme, spanning AI chips and computing hardware, cloud platforms and data centres, and software and applications. The product listed on the Hong Kong Stock Exchange on September 26, 2025, with a management fee of 0.9% per year.

Kaiyuan Securities believes the acceleration of physical AI is driving expansion in AI servers and domestic computing power. Complex reasoning and agent tasks add sustained computing consumption, pushing server demand from training clusters to high-concurrency inference; domestic chipmakers are scaling deployments through hardware-software adaptation, cluster delivery and customer use cases, with procurement shifting from testing and validation to actual deployment.