Guo Tai Jun An Qi Huo·2025-11-12 11:53Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - The essence of the US stock macro - strategy framework is the DDM model, with enterprise earnings, risk - free rate, and equity risk premium as the core elements [2][3]. - The position and direction of the profit cycle on the molecular end are the anchors for judging the US stock trend, and the continuous upward revision of EPS is the dominant factor driving the rise of US stocks [6][8]. - The US stock investor structure is mature, with institutional investors holding 60% of the positions, and passive investment is dominant [27]. - The current valuation of the overall US stock market is not cheap based on the next 12 - month consensus forecast PE [45]. - The performance of the US stock AI industry chain is realized from the upstream infrastructure layer to the downstream application software/media, and the upstream industry trend has strong certainty while the downstream is highly differentiated [104][106]. - The direction and degree of performance revision expectations are the core contradictions determining the three - stage market evolution of US stock AI [109][112]. Summary by Relevant Catalogs 1. US Stock Macro Strategy Framework: DDM Model 1.1 Essence of the Equity Investment Framework - The core of the market driving variables is the three elements of the DDM model: enterprise earnings (molecular end), risk - free rate, and equity risk premium (denominator end) [3][5]. 1.2 Molecular End - In the long run, the continuous upward revision of EPS on the molecular end is the dominant factor driving the rise of US stocks, and the position and direction of the profit cycle are the anchors for judging the US stock trend [6][8]. - Based on the Bloomberg style factor back - testing model, the factor representing profit growth ability has the highest winning rate in the US stock investment strategy framework [11]. - The ROE trend is strictly positively correlated with the US stock valuation in the long run [14]. - For cyclical assets, the core of the analysis framework is to grasp the position and direction of the macro - cycle, and the "soft data" of the US economy has a more significant guiding effect on US stock cyclical assets [15][18]. - For technology assets, the core of the analysis framework is to grasp the industrial prosperity/innovation cycle, and they may be desensitized from the macro - cycle under the guidance of the industrial trend [19]. - There are dynamic monitoring databases for the consensus forecast of EPS of US stock broad - based/key industries and the consensus forecast of Capex of the "Seven Sisters" in the US stock market, and the Capex of US technology giants is expected to continue to be revised upward in the next two years, with greater investment in the upstream AI segment [20][22]. 1.3 Denominator End - The US stock investor structure is mature, with institutional investors holding 60% of the positions, and passive investment is dominant, with some funds from actively managed mutual funds flowing into ETFs [27][29]. - In the long run, liquidity indicators are not strictly negatively correlated with the US stock valuation. The role of the 10Y US Treasury yield as a global asset pricing anchor has weakened, and the NFCI financial conditions index has a better effect in depicting the tightness of liquidity [32][37]. - To track US dollar liquidity from a quantitative and price perspective, one can focus on the Fed's asset purchase scale from the quantitative dimension and the repurchase market (SOFR - OIS spread), short - term/long - term financing markets (commercial paper spread/credit spread) from the price dimension [43]. 2. US Stock Special Valuation System 2.1 Future 12 - Month Consensus Forecast PE - Based on the future 12 - month consensus forecast PE, the current valuation of the overall US stock market is not cheap. This dynamic P/E ratio, which includes future profit expectations, is more suitable for evaluating high - growth industries [45][49]. - The PE TTM of the "Seven Sisters" in the US stock market is generally higher than the future 12 - month consensus forecast PE [57]. 2.2 ERP (Equity Risk Premium) - No detailed content provided other than the mention of the indicator [63]. 2.3 Global Stock Index Valuation vs ROE Dynamic Comparison - The strong cash - flow creation and profitability of US stock enterprises are the underlying logic supporting high valuations. Among US stock sectors, technology leaders represented by the "Seven Sisters" also have strong cash - flow creation and profitability to support high valuations [69][70]. 2.4 PEG - The PEG formula is P/E ratio divided by expected profit growth rate, which better measures the matching degree between stock valuation and growth. A PEG < 1 indicates a sector with low valuation and high growth. The PEG of the US stock technology sector is still lower than that of non - technology sectors [75][76]. 3. US Stock Trading Heat Tracking System 3.1 Trading - Level Indicators - For short - term timing, one can adopt reverse thinking when considering the trading volume concentration of popular US stock sectors, as buying in the downturn stage has higher cost - effectiveness than in the over - heated stage [82]. - The market breadth of US stocks has been deteriorating in the recent quarter, and the AAII bull - bear spread shows that the bullish sentiment of US stock investors has been weak during this round of the rise [92]. - Other indicators include the 14 - RSI and option sentiment of the S&P 500 and Nasdaq 100, as well as the net inflow of funds into different types of US asset ETFs [95][97][99]. 4. US Stock AI Three - Stage Investment Framework 4.1 Key Targets and Performance Realization in the US Stock AI Industry Chain - The report lists key targets in the US stock AI industry chain, including upstream infrastructure layer, mid - stream, and downstream application/software/end - side companies [103]. - The performance realization path of the US stock AI industry chain generally follows from the upstream infrastructure layer to the downstream application software/media. The upstream industry trend has strong certainty, while the downstream is highly differentiated, and most application - layer business models are still being verified [104][106]. 4.2 Three - Stage Investment Framework for US Stock AI - The direction and degree of performance revision expectations are the core contradictions determining the three - stage market evolution of US stock AI. Since 2023, the increase in different stages of the US stock AI industry chain has basically matched the degree of upward revision of performance expectations. The stock price performance of the three - stage US stock AI also follows the same pattern driven by the upward revision of EPS profit expectations [109][112]. - The commercialization of the advertising and marketing and audio - visual segments in the US stock AI application sector is the fastest, and the differentiation in EPS, revenue growth, and stock price increases among individual stocks in the application sector is well - matched [116][119]. 4.3 Concerns about the "AI Bubble" behind the Recent US Stock Risk - off - The recent borrowing boom of US technology companies has raised market concerns, which are initially reflected in the pricing of the bond market, but currently, it is more of a local and accidental risk pricing rather than a systematic risk pricing [123]. - Overall, US technology stocks have not significantly "over - invested" cash flow in Capex [124].