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六成私募“满仓豪赌”,科技主线全线爆发,芯片ETF天弘(159310)、科创综指ETF天弘(589860)涨超2%!
Xin Lang Cai Jing·2025-09-30 06:57

Core Insights - The chip ETF Tianhong (159310) has seen a significant increase of 2.29% with a trading volume of 23.1 million yuan, driven by strong performances from constituent stocks such as Jiangbolong (301308) and Baiwei Storage (688525) [3] - In the past two weeks, the chip ETF Tianhong (159310) has experienced a growth of 19.6 million yuan, indicating robust investor interest [3] - The technology sector is gaining traction among private equity firms, with over 65% planning to maintain high positions in technology growth areas, particularly in AI and semiconductors [5] Fund Performance - The chip ETF Tianhong (159310) has recorded a net inflow of 90.48 million yuan over four out of the last five trading days, reflecting strong market interest [4] - The Sci-Tech Innovation Index ETF Tianhong (589860) has also shown positive momentum, with a peak increase of over 2% and a trading volume of 90.74 million yuan [4] Product Highlights - The chip ETF Tianhong (159310) tracks the CSI Chip Industry Index, with top holdings including SMIC, Northern Huachuang, and Cambrian [5] - The Sci-Tech Innovation Index ETF Tianhong (589860) covers 97% of the Sci-Tech Innovation Board's market value, focusing on strategic emerging industries such as semiconductors and AI [5] Industry Developments - Alibaba Cloud has launched the new generation of AI servers, the Panjiu 128, which boasts high-density design and significant performance improvements, attracting industry attention [6] - The IPO of domestic AI chip company Moer Thread has been approved in a record time of less than three months, highlighting the efficiency of the new listing standards for tech firms [6] Institutional Perspectives - CITIC Securities anticipates steady growth in the computer industry for Q3 2025, with a focus on AI applications and computing power [7] - Jinyuan Securities notes Alibaba Cloud's comprehensive strategy in computing power and platform development, which is expected to accelerate the application of domestic AI hardware [7]