正如社交媒体上的这句话所说："我们都在做多比特币，只是有些人自己还不知道。" 11月24日，Academy Securities知名策略师Peter Tchir在其最新报告中警告，随着"免费钱"（Free Money）时代的终结，这种隐秘的杠杆正在反噬市 场。过去两年中，企业仅凭宣布巨额支出计划就能换取股价数倍上涨的逻辑已然破灭，这一逆转正成为纳斯达克指数近期下挫的核心推手。 近期市场剧烈波动，纳斯达克100指数领跌超过3%，而在更具代表性的标普500等权重指数中，跌幅仅为0.9%。这种分化凸显了痛苦主要集中在科 技与高成长领域。 尤其是10月10日，比特币在美股收盘时段经历了从12.2万美元骤降至10.5万美元的剧烈抛售，这一"莫名其妙"的崩盘不仅重创了加密资产，更通过 ETF和相关上市公司的传导链条，对广泛的股票投资组合构成了直接的流动性压力。 这一现象揭示了当前市场结构中一个危险的信号：加密货币、人工智能基础设施建设与美股被动投资资金已经形成了高度关联的"铁索连江"之 势。随着被动投资规模超越主动投资，通过QQQ等ETF工具，数以亿计的退休金和避险资金实际上已与MicroStrategy等"数字资产储备 ...

Group 1: Market Dynamics - The core driver of the current rise in equity assets is not due to macro liquidity excess but rather a recovery in risk appetite since the "anti-involution" policy was implemented[5] - The market is primarily driven by internal fund reallocations and leverage rather than large-scale inflows from external funds[5] - The correlation between stocks and bonds has shifted to a "see-saw" effect, indicating that growth factor changes are now dominant, contrasting with the liquidity-driven environment of 2015[13] Group 2: Price Stabilization and PPI Insights - Price stabilization is expected to continue into Q4, supported by significant differentiation in pricing between domestic and external demand[5] - The Producer Price Index (PPI) is influenced by overseas inflation, with a notable divergence between Chinese and U.S. PPI trends[25] - The PPI gap between different industries, such as non-ferrous and ferrous metals, has reached 20%, a historically unprecedented level[25] Group 3: Fund Flows and Market Sentiment - As of September 14, 2025, new equity fund sales reached 42.85 billion units, a significant increase from less than 10 billion units at the beginning of 2024, although still below the peak levels seen in 2015 and 2021[18] - The margin ratio for internal funds reached 294.17% on August 24, 2025, nearing historical peak levels, indicating high leverage in the market[18] Group 4: Future Projections - If capacity utilization rises above 75%, a 1.35% increase is expected, with a corresponding price increase of approximately 1.5% due to the price elasticity of capacity utilization[40] - The stock market's upward trend since September 2024 is compared to the 1999 market rally, suggesting a potential further increase of around 30% if the current trajectory continues[55][58]

Core Viewpoint - The Federal Reserve is expected to announce its first interest rate cut of the year during the upcoming monetary policy meeting, indicating a shift towards a dovish stance in response to economic risks [1][3]. Group 1: Federal Reserve's Dovish Stance - Citi's analysis indicates that the current market pricing of the terminal interest rate is below levels suggested by inflation and growth indicators, reflecting a clear dovish policy stance from the Federal Reserve [1][2]. - The constructed Federal Reserve policy stance indicator is currently at a low level, suggesting that the market's pricing is "overly accommodative" relative to the fundamentals [2][3]. Group 2: Economic Risks and Labor Market - The dovish stance is based on concerns regarding future economic risks, particularly signs of weakness in the labor market, including rising unemployment rates and longer durations of unemployment [3]. Group 3: Gold and Risk Assets Correlation - In a policy-driven "fiscal dominance" environment, the correlation between gold and risk assets (such as the S&P 500 and Nikkei indices) is expected to become more positive than currently priced in by the market [5]. - There is a significant deviation between the implied correlation of gold and risk assets in the options market and the historical realized correlation during similar dovish environments, indicating that the market has not fully absorbed this shift [5]. Group 4: Gold as a Hedge - Gold is often misperceived as a traditional safe-haven asset; however, its relationship with bond yields is structurally unstable, which undermines its role as a pure hedge [7]. - In the current context of the Federal Reserve's accommodative stance to address potential economic risks, gold's properties make it likely to perform well, supporting the rationale for a "gold up + stocks up" combination [7].

Quantitative Models and Construction Methods 1. Factor Name: Beta Factor - **Construction Idea**: The Beta factor measures the sensitivity of a stock's returns to the overall market returns, indicating its systematic risk[29] - **Construction Process**: - Calculate the covariance between the stock's returns and the market returns - Divide this covariance by the variance of the market returns - Formula: $ \beta = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)} $ where $R_i$ is the return of the stock and $R_m$ is the return of the market[29] - **Evaluation**: The Beta factor is a widely used measure of risk, indicating how much a stock's price is expected to move relative to the market[29] 2. Factor Name: Liquidity Factor - **Construction Idea**: The Liquidity factor assesses the ease with which a stock can be traded without affecting its price, reflecting the market's depth and breadth[29] - **Construction Process**: - Measure the average daily trading volume - Calculate the bid-ask spread - Combine these metrics to form a composite liquidity score - Formula: $ \text{Liquidity} = \frac{\text{Average Daily Volume}}{\text{Bid-Ask Spread}} $[29] - **Evaluation**: The Liquidity factor is crucial for understanding the trading costs and potential price impact of large trades[29] 3. Factor Name: Profitability Quality Factor - **Construction Idea**: The Profitability Quality factor evaluates the financial health and earnings quality of a company, focusing on sustainable and high-quality earnings[29] - **Construction Process**: - Analyze various financial ratios such as return on equity (ROE), return on assets (ROA), and profit margins - Combine these ratios into a composite score - Formula: $ \text{Profitability Quality} = \frac{\text{ROE} + \text{ROA} + \text{Profit Margin}}{3} $[29] - **Evaluation**: This factor helps in identifying companies with strong and sustainable earnings, which are likely to perform well in the long term[29] Factor Backtesting Results 1. Beta Factor - **IR**: 0.45[29] - **Annualized Return**: 8.5%[29] - **Volatility**: 12.3%[29] 2. Liquidity Factor - **IR**: 0.38[29] - **Annualized Return**: 7.8%[29] - **Volatility**: 11.5%[29] 3. Profitability Quality Factor - **IR**: 0.52[29] - **Annualized Return**: 9.2%[29] - **Volatility**: 10.8%[29] Additional Factors and Their Performance 1. Factor Name: Skewness Factor - **Construction Idea**: The Skewness factor measures the asymmetry of the return distribution, indicating the potential for extreme positive or negative returns[33] - **Construction Process**: - Calculate the third moment of the return distribution - Normalize by the cube of the standard deviation - Formula: $ \text{Skewness} = \frac{E[(R - \mu)^3]}{\sigma^3} $ where $R$ is the return, $\mu$ is the mean return, and $\sigma$ is the standard deviation[33] - **Evaluation**: This factor is useful for understanding the tail risks and potential for extreme outcomes in the return distribution[33] 2. Factor Name: Position Change Factor - **Construction Idea**: The Position Change factor tracks changes in the holdings of large institutional investors, indicating their sentiment and market positioning[33] - **Construction Process**: - Monitor the quarterly filings of institutional investors - Calculate the net change in positions for each stock - Formula: $ \text{Position Change} = \frac{\text{Current Quarter Holdings} - \text{Previous Quarter Holdings}}{\text{Previous Quarter Holdings}} $[33] - **Evaluation**: This factor provides insights into the buying and selling activities of major market players, which can influence stock prices[33] Factor Backtesting Results 1. Skewness Factor - **IR**: 0.42[33] - **Annualized Return**: 8.1%[33] - **Volatility**: 11.9%[33] 2. Position Change Factor - **IR**: 0.47[33] - **Annualized Return**: 8.7%[33] - **Volatility**: 11.2%[33]