倍漾量化冯霁： 相信AI未来会取代传统量化基金经理

Core Viewpoint - The role of traditional quantitative investment fund managers is expected to be replaced by artificial intelligence (AI), as stated by Feng Ji, founder of Beiyang Quantitative [1][2]. Group 1: AI's Impact on Investment Management - AI is predicted to replace traditional quantitative investment fund managers, and institutions that do not adopt AI technology may be eliminated within the next 3 to 5 years [2]. - The introduction of AI in quantitative investment is likened to the historical adoption of personal computers and servers on Wall Street, emphasizing the necessity to embrace AI as a powerful modeling tool [2]. - The advantages of machines in market learning and pattern recognition will become increasingly evident as computational power, data, and model capabilities continue to improve [2]. Group 2: New Talent Requirements - The investment era driven by AI will require fund managers to be hybrid talents, possessing both investment research skills and the ability to translate these into AI-related problems [2]. - The focus of investment professionals will shift from traditional research tasks to maintaining and developing advanced AI systems, necessitating a higher understanding of AI technology [2]. Group 3: Beiyang's Unique Approach - Beiyang Quantitative views the traditional investment research process as a unified task of "machine learning," aiming to utilize AI technology for end-to-end modeling [3]. - The company employs a workforce primarily composed of engineers rather than finance professionals, consisting of computer scientists and algorithm competition winners [3]. - Beiyang Quantitative aims to replace expert experience with AI capabilities, asserting that AI can better extract factors from data [3]. Group 4: Competitive Advantages and Future Goals - Beiyang Quantitative's competitive edge lies in three areas: high talent density in AI, superior computational power compared to domestic universities, and a self-developed AI experimental platform for real-time modeling and trading tasks [3]. - The company aspires to evolve from a traditional quantitative private equity firm to an AI-native "computational company," with mid-term goals of becoming a global quantitative manager and long-term aspirations of being a leading computational firm [3][4].