宽德投资冯鑫：AI时代的指数化投资——量化投资与长期价值投资的融合

Core Viewpoint - The integration of AI-driven investment transformation, long-term policy orientation, and the responsibility of the domestic quantitative investment industry presents both challenges and opportunities for institutional managers who adhere to a long-term perspective [2][4]. Group 1: Era Background - The current era is characterized by a convergence of technological evolution and institutional transformation, with generative AI significantly altering various industries and providing new tools for long-term value investment [4]. - AI is evolving from enhancing multi-step reasoning capabilities (L2) to developing AI Agents (L3) that possess "perception-planning-execution" closed-loop capabilities, marking 2025 as the "Year of AI Agents" [4]. Group 2: Market Dynamics - In overseas markets, AI-assisted research has become mainstream, with hedge fund managers leading the adoption of large models to optimize investment research processes [5]. - National policies are reinforcing a long-term orientation, with new guidelines encouraging long-term capital entry into the market and advocating for value investment [5]. - The A-share market is undergoing positive structural changes, with continuous optimization in information disclosure, regulatory enforcement, and investor structure, creating a foundation for sustained long-term investment [5][6]. Group 3: Quantitative Investment Strategies - The Smart Beta strategy is positioned to meet the needs of long-term institutional capital, aiming to provide a reliable long-term allocation tool that combines long-termism with a tool-oriented approach [12][13]. - Smart Beta strategies emphasize a tool-oriented approach, focusing on systematic modeling of fundamental factors to create understandable, replicable, and assessable allocation tools [13]. - The design principles of Smart Beta strategies include high capacity, low turnover, and reasonable fees, supporting institutional investors in achieving long-term allocations [13]. Group 4: AI Development and Research - The industry is embracing AI, with research categorized into interest-driven academic AI studies and more challenging industrial-grade AI development, which requires significant investment and long-term planning [17][18]. - The establishment of the Wizard Intelligence Learning Lab (WILL) reflects the commitment to exploring the future of intelligence, emphasizing the importance of AI's social value [19]. Group 5: Conclusion and Call to Action - The current environment presents both uncertainty and structural challenges, but also opens up opportunities for innovation and development [22]. - The emphasis is on participation and construction rather than observation, highlighting the belief that worthwhile endeavors are often based on long-term faith and practice [22][23].