研究框架培训：AI投资框架

Summary of Key Points from Conference Call Records Industry or Company Involved - The focus is on the AI industry and its related sectors, particularly the TMT (Technology, Media, and Telecommunications) sector. Core Insights and Arguments 1. Timing for Investment in Technology Sector: On June 8, the technology sector was deemed ready for investment based on analysis of congestion, rolling yield differences, trading volume ratios, and calendar effects, with a specific recommendation to focus on the upstream computing power sector, which has been validated subsequently [4][1][2]. 2. Trends in AI Market: The AI market is currently experiencing three major trends: movement from upstream to downstream, diversification within the sector, and the transition from AI to AI-enhanced applications [3][1]. 3. Internal Differentiation in AI: There are two main differentiations within AI: between upstream and downstream sectors, and between North American and domestic computing power, primarily driven by performance [5][1]. 4. Early Stage of AI Market Expansion: The AI market is still in its early expansion phase, suggesting a strategic focus on the diffusion of domestic computing power into upstream semiconductor equipment and materials, as well as downstream applications in sectors like internet, gaming, and consumer electronics [6][1]. 5. AI Investment Framework: The AI investment framework includes key indicators such as timing indicators, calendar effects, internal rotation factors, sector comparisons, and historical references from the 2013-2015 internet boom [7][1]. 6. Trading Volume Analysis: Adjusted trading volume ratios show that in 2023, the ratio reached approximately 50%, compared to a maximum of 40% in 2019, indicating a more accurate market analysis [7][1]. 7. AI Rotation Intensity Indicator: This indicator tracks the performance of 50 major news directions in the AI industry, showing a significant inverse relationship with the AI index, suggesting that when internal rotation converges, the sector typically experiences an uptrend [9][1]. 8. Calendar Effects in TMT Sector: The TMT sector exhibits performance-related calendar effects, with high win-rate periods in February-March, May-June, and October-November, influenced by risk appetite, earnings releases, and consumption peaks [2][10][11]. 9. Factors Influencing AI Sector Rotation: The AI sector is divided into three main chains: upstream computing power, midstream algorithm technology, and downstream applications. The North American computing power chain has consistently outperformed the domestic chain since May 2025 [12][1]. 10. Historical Insights from 2013-2015: The historical performance of the TMT sector from 2013 to 2015 provides insights into current market dynamics, emphasizing the importance of earnings in driving stock performance [19][20]. Other Important but Potentially Overlooked Content 1. Potential for Downstream Sectors: There is significant potential for growth in downstream sectors such as cybersecurity, operating systems, and cloud computing, which are currently underrepresented in institutional portfolios [15][1]. 2. Market Sentiment and Trading Volume: Concerns about high trading volume ratios do not necessarily indicate an end to the market rally, as historical trends show that significant market shifts can occur despite high trading volumes [17][1][18]. 3. AI's Long-Term Impact: The transition from AI to AI-enhanced applications is expected to mirror past trends seen in the internet sector, with a broader impact across traditional industries [16][1]. 4. Investment Opportunities in Software Applications: Areas such as SaaS, online education, and digital marketing are highlighted as having substantial potential for performance improvement and investment opportunities [15][1].