盘点年内翻倍ETF:华宝创业板人工智能ETF规模超33亿,年内涨105%,重仓股覆盖算力至终端产业链
Xin Lang Cai Jing·2025-12-10 09:05

Core Viewpoint - The ETF market has seen a resurgence with five products achieving over 100% annual returns as of December 9, 2025, particularly in the technology sector, including communication equipment and artificial intelligence [1][8]. Group 1: ETF Performance - Five ETFs have surpassed 100% returns this year, with notable performances from communication and AI sectors [1][8]. - The top-performing ETFs include: - Guotai CSI All-Share Communication Equipment ETF with a return of 122.27% and a scale of 124.50 billion [2][9]. - Fuguo CSI Communication Equipment Theme ETF with a return of 111.21% and a scale of 10.41 billion [2][9]. - Southern Growth Enterprise Board AI ETF with a return of 110.15% and a scale of 25.73 billion [2][9]. - Huabao Growth Enterprise Board AI ETF with a return of 104.57% and a scale of 33.55 billion [2][9]. - Guotai Growth Enterprise Board AI ETF with a return of 100.38% and a scale of 5.51 billion [2][9]. Group 2: Huabao AI ETF Insights - The Huabao Growth Enterprise Board AI ETF, managed by Chen Jianhua and Cao Xucheng, has achieved a return of 104.57% since its inception on December 6, 2024, with a current scale of 33.55 billion [3][12]. - The fund's manager, Chen Jianhua, has delivered a return of 96.02% since the fund's establishment, with an annualized return of 94.60% [5][12]. - The fund's investment strategy focuses on the AI computing power industry chain, with major holdings in leading optical module companies, including Zhongji Xuchuang and Xinyi Sheng, which together represent a significant portion of the portfolio [5][12]. Group 3: Market Outlook - The fund's third-quarter adjustments were conservative, with increases in holdings ranging from 76% to 80% for most stocks [7][15]. - The fund managers expressed confidence in the sustained demand for AI, particularly in large models and computing power, which is expected to drive the performance of the AI sector [7][15]. - Future opportunities are anticipated in high-end computing cycles and new AI terminals, such as robotaxis and robots, which are at critical technological development stages [7][15].