430亿元！公募新年入市资金来了

Core Viewpoint - The article discusses the anticipated influx of public funds into the market in 2026, driven by new ETFs and actively managed equity funds, with a total expected scale exceeding 430 billion yuan by the end of 2025 [5]. Group 1: ETF Market Overview - As of December 31, 2025, six ETFs are set to launch in the first week of 2026, collectively bringing over 20 billion yuan in incremental funds to the A-share market [3]. - The total scale of the 16 ETFs expected to enter the market after New Year's is nearly 50 billion yuan [3]. - Individual investors dominate the ownership of these new ETFs, with personal holdings exceeding 90% in many cases [2][8]. Group 2: Actively Managed Equity Funds - By the end of 2025, 66 actively managed equity funds were established, with a total fundraising scale of approximately 387.35 billion yuan [4]. - The average return since inception for these newly established funds is 0.75%, indicating that a significant portion of the raised funds is yet to be deployed in the market [4]. - Notable funds include Guangfa Quality Preferred and E Fund Industry Preferred, each exceeding 30 billion yuan in scale [4]. Group 3: Potential for Increased Market Participation - There is a significant potential for "deposit migration" into the market, with estimates suggesting an additional 2 trillion to 4 trillion yuan could flow into non-deposit investment areas in 2026 [9]. - The total scale of ETFs reached over 6 trillion yuan by the end of 2025, with nearly 1 trillion yuan being new inflows during that year [7]. Group 4: Market Dynamics and Future Outlook - The market is expected to shift its driving factors from valuation to profitability, with anticipated recovery in earnings growth and return on equity (ROE) levels in 2026 [10]. - The technology investment landscape is projected to become more challenging in 2026, requiring precise industry timing and stock selection for excess returns [11]. - Key areas of focus in the AI sector include optical communication, storage chips, domestic computing power breakthroughs, and AI application implementation [11].