Group 1 - The report analyzes the cognitive differences between AI, analysts, and traders in response to the extreme situation of the US tightening chip export controls on October 17, 2023, highlighting their complementary roles in asset pricing rather than a replacement relationship [2][4][24] - AI processes information at millisecond speed, focusing on keywords and historical patterns, while analysts delve into regulatory details and industry research to understand policy intentions and supply-demand dynamics, and traders monitor market liquidity and emotional responses [2][8][12] - The report emphasizes that AI cannot replace human judgment due to its inability to recognize structural breaks, lack of second-order thinking, and difficulty in understanding soft information and context [3][25][26] Group 2 - The case of Nvidia illustrates the differences in response to the chip ban, where AI reacted mechanically based on historical data, while analysts and traders provided nuanced interpretations based on market conditions and regulatory context [5][12][24] - The report outlines three key dimensions where AI falls short compared to human analysts: handling structural breaks, lacking second-order thinking, and struggling with soft information [24][25][26] - The future competitive advantage lies in the collaboration between AI, analysts, and traders, where AI enhances information density, analysts provide structural insights, and traders offer real-time feedback [3][29][30] Group 3 - The report suggests that analysts should leverage AI as a super assistant, outsourcing mechanical tasks to focus on complex decision-making and value assessment [30][31] - Analysts need to transition from information transmitters to opinion monetizers, providing clear, logical conclusions based on known facts and market sentiment [30][31] - The ability to integrate knowledge across disciplines will be crucial for analysts to maintain a competitive edge in the AI era [31][33]
AI 赋能资产配置(二十八):AI、分析师与交易员:殊途同归与优势互补