Core Viewpoint - The end of the "free money" era is leading to significant market volatility, particularly affecting the Nasdaq index and technology sectors, as companies can no longer rely on announced spending plans to drive stock prices higher [1][4]. Group 1: Market Dynamics - The Nasdaq 100 index has recently dropped over 3%, while the S&P 500 has only seen a decline of 0.9%, indicating that the pain is concentrated in technology and high-growth sectors [1]. - Bitcoin experienced a dramatic sell-off from $122,000 to $105,000, impacting not only crypto assets but also creating liquidity pressures across broader stock portfolios [1]. - The correlation between cryptocurrencies, AI infrastructure, and passive investment funds in the U.S. stock market has intensified, creating a precarious situation for investors [3]. Group 2: Investment Behavior - Investors are increasingly viewing Bitcoin's performance as a barometer for future risk appetite, with many believing that a recovery in Bitcoin could signal a rebound in the stock market by year-end [4][12]. - The "free money" effect previously allowed companies to create shareholder wealth by simply announcing spending, particularly in AI and data center construction, but this is no longer translating into stock price increases [4]. - Digital asset reserve companies (DATs) like MicroStrategy (MSTR) have seen their valuations decline as the market questions the returns on their significant investments in cryptocurrencies [5]. Group 3: Passive Investment Impact - The rise of passive investment has complicated the market landscape, with a significant portion of funds flowing into a few companies, including MSTR, which is heavily held by major passive investment firms [6]. - The potential inclusion of DATs in major stock indices like MSCI could either prevent forced selling or trigger significant sell-offs depending on the decision made [8]. Group 4: Wealth Effect and Liquidity - Bitcoin's market cap has fallen from approximately $2.5 trillion to $1.85 trillion, resulting in a loss of $650 billion in wealth, which is negatively impacting the "wealth effect" in the market [9]. - The correlation between crypto assets and traditional stocks has increased, leading to a situation where declines in crypto necessitate selling off liquid assets like tech stocks to raise cash [9]. Group 5: Macroeconomic Considerations - The Federal Reserve faces uncertainty regarding its policy path, with market expectations for interest rate cuts fluctuating significantly [10]. - The end of the "free money" era may lead to a slowdown in AI data center spending, potentially cooling the economy and providing the Fed with justification for rate cuts [10]. - If cryptocurrencies do not stabilize, the resulting liquidity tightening and wealth reduction could adversely affect not only tech stocks but also broader economic growth [10].

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]