Core Viewpoint - The stock market is experiencing significant growth, with the Shanghai Composite Index up 12.8% and the ChiNext Index up 22% in 2025, while the bond market is facing challenges, with a 30-year government bond ETF down over 2% year-to-date and a further decline of 4% since June [1][2] Group 1: Market Dynamics - The "see-saw effect" between stocks and bonds reflects a shift in market risk appetite, where funds flow into equities during bullish phases and retreat to bonds during bearish phases [1][2] - The primary determinants of bond market trends are economic fundamentals, including macroeconomic conditions, inflation, and monetary policy, rather than stock market performance [2][3] Group 2: Economic Indicators - Recent economic data indicates a weakening trend, with July's new loans showing negative growth for the first time since 2005 and a decline in social financing year-on-year [2][3] - Despite these indicators suggesting support for the bond market, the bond market continues to decline due to strong stock performance and policy disruptions, indicating a temporary disconnection from economic data [2][3] Group 3: Investment Strategies - In a bullish stock market, the bond market may not present high value, but there are opportunities for tactical trading, suggesting a strategy of buying low and selling high [4][5] - Monitoring the 10-year and 30-year government bond yields is crucial, as bond prices and yields move inversely; rising yields lead to falling bond prices and vice versa [4][5] Group 4: Historical Context - Over the past decade, the long-term trend in China's bond market has been a decline in yields, with the 10-year government bond yield currently around 1.76% and the 30-year yield at 2.06% [5][6] - Historical data shows that current yields are at a low point, but there is potential for further declines, indicating a long-term downward trend in interest rates [6][7] Group 5: Tactical Approaches - For short-term trading, flexibility is key; if yields rise, it presents buying opportunities, while falling yields may prompt profit-taking [6][7] - For long-term investments, considerations include duration selection, risk-return trade-offs, and alignment with market conditions, emphasizing the importance of rational decision-making [7]

Quantitative Models and Construction Methods 1. Model Name: Interest Rate Bond Expected Return Model - **Model Construction Idea**: This model decomposes the expected return of interest rate bonds into several components and uses Monte Carlo simulations to predict the expected return for bonds of any maturity over a one-year holding period [8] - **Model Construction Process**: The expected return of interest rate bonds is decomposed into the following components: - Coupon yield - Roll yield - Duration yield - Convexity yield The formula for the expected return is: $ R \approx r_{N} + roll~yield + Dur \cdot (-\Delta r) + \frac{1}{2} Cx \cdot \Delta r^{2} $ Where: - $ r_{N} $ represents the coupon yield - $ roll~yield $ represents the roll-down return - $ Dur $ represents the duration - $ \Delta r $ represents the change in interest rates - $ Cx $ represents the convexity Based on this, the "interest rate bond odds" is defined as: $ Interest~Rate~Bond~Odds = 10Y~Bond~Expected~Return - 1Y~Bond~Expected~Return $ As of July 18, the expected return difference between 10Y and 1Y bonds was -3.2%, indicating extremely low odds for 10Y bonds [8] 2. Model Name: Short-Term Momentum Model - **Model Construction Idea**: This model predicts the short-term (1-month) price movement of interest rate bonds based on three key characteristics of interest rate movements: mean reversion around the interest rate center, 1-month short-term momentum, and 12-month long-term momentum [14] - **Model Construction Process**: The formula for the short-term momentum model is: $ \Delta r_{t+1} = \beta_{1}(\mu - r_{t}) + \beta_{2}(r_{t} - r_{t-1}) + \beta_{3}(r_{t} - r_{t-12}) + \sigma \sqrt{r_{t}} \cdot \varepsilon $ Where: - $ \mu $ represents the interest rate center - $ r_{t} $ represents the current interest rate - $ r_{t-1} $ and $ r_{t-12} $ represent the interest rates 1 month and 12 months ago, respectively - $ \beta_{1}, \beta_{2}, \beta_{3} $ are coefficients - $ \sigma $ represents volatility - $ \varepsilon $ represents random noise The model suggests that the 10Y bond may face short-term downward pressure, and recommends defensive allocation to 1Y bonds [14] 3. Model Name: Trading Heat Monitoring Model - **Model Construction Idea**: This model uses turnover rate and transaction proportion to measure the trading heat of long-term bonds, identifying risks of overcrowded trading [17] - **Model Construction Process**: - Turnover rate = (Trading volume of bonds with maturity >10 years) / (Outstanding balance of bonds with maturity >10 years) - Transaction proportion = (Trading volume of bonds with maturity >10 years) / (Total trading volume of all bonds) Historical data shows that when these indicators exceed 2 standard deviations, the future 1-3 month returns of long-term bonds are negative. When they exceed 4 standard deviations, the risk of significant drawdowns increases [17][18] --- Model Backtesting Results 1. Interest Rate Bond Expected Return Model - **10Y-1Y Expected Return Difference**: -3.2% (as of July 18, 2025) [8] 2. Short-Term Momentum Model - **Annualized Return**: 6.6% - **Maximum Drawdown**: 2.3% - **Q1 Avoided Drawdown**: Approximately 2.2% [14] 3. Trading Heat Monitoring Model - **Turnover Rate**: 1.0 standard deviation - **Transaction Proportion**: 2.2 standard deviations [18]