头部量化，最新发声！宽德投资冯鑫：不做伟大时代的旁观者！

Core Viewpoint - The integration of AI-driven investment strategies, particularly the Smart Beta approach, is seen as a pivotal development in the investment landscape, aiming to balance long-term value investment with quantitative methods [1][5][15] Group 1: Technological and Policy Context - The current era is marked by a convergence of technological evolution and institutional transformation, with generative AI significantly impacting various industries and facilitating the implementation of long-term investment philosophies [3][8] - AI is evolving from enhancing multi-step reasoning capabilities to developing AI Agents capable of executing complex tasks autonomously, marking 2025 as the "Year of AI Agents" [8][10] - National policies are increasingly promoting long-term investment, with new regulations encouraging the entry of long-term capital into the market and advocating for value investing [10][11] Group 2: Role of Quantitative Trading - Quantitative trading serves as both a "lubricant" and "stabilizer" in the market, enhancing resource allocation efficiency and providing liquidity and price discovery mechanisms [4][12] - The evolution of the Chinese market structure, including improved information disclosure and regulatory enforcement, supports a fundamental-driven market mechanism conducive to long-term investment [10][11] Group 3: Smart Beta Strategy - The Smart Beta strategy is positioned as a reliable tool for long-term institutional investors, focusing on systematic modeling of fundamental factors to create transparent and replicable investment tools [15][16] - This strategy emphasizes low turnover, reasonable fees, and high capacity, aligning with the goal of achieving "universal access" for long-term investors [16][15] Group 4: AI Exploration and Future Opportunities - The industry is witnessing a surge in AI research, categorized into academic-driven studies and industrial-level AI development, which involves significant investment and long-term planning [17][18] - Opportunities arising from AI can be divided into application-oriented chances and foundational capability explorations, both of which are crucial for enhancing industry efficiency and addressing fundamental questions about AI's potential [18][19] Group 5: Conclusion and Vision - The current environment presents both uncertainties and structural challenges, yet it also opens up new avenues for development through technological breakthroughs and collaborative efforts [20] - The establishment of AI laboratories, such as WILL, reflects a commitment to exploring the societal value of AI and fostering a culture of responsible innovation within the investment sector [19][20]