Quantitative Models and Construction Methods 1. Model Name: Interest Rate Price-Volume Multi-Cycle Timing Strategy - **Model Construction Idea**: This strategy uses kernel regression algorithms to identify support and resistance lines in interest rate trends. It combines signals from long, medium, and short investment cycles to form a composite timing view[10][22] - **Model Construction Process**: 1. **Signal Generation**: - Use kernel regression to capture the shape of interest rate trends and identify breakout signals for long, medium, and short cycles[10] - Long-cycle signals switch monthly, medium-cycle signals switch bi-weekly, and short-cycle signals switch weekly[10] 2. **Portfolio Allocation Rules**: - If at least two cycles show downward breakouts and the trend is not upward, allocate fully to long-duration bonds - If at least two cycles show downward breakouts but the trend is upward, allocate 50% to medium-duration bonds and 50% to long-duration bonds - If at least two cycles show upward breakouts and the trend is not downward, allocate fully to short-duration bonds - If at least two cycles show upward breakouts but the trend is downward, allocate 50% to medium-duration bonds and 50% to short-duration bonds - In other cases, allocate equally across short, medium, and long durations[22] 3. **Benchmark**: Equal-weighted duration strategy (1/3 short, 1/3 medium, 1/3 long duration)[22] 4. **Stop-Loss Mechanism**: Adjust to equal-weight allocation if daily excess return falls below -0.5%[22] - **Model Evaluation**: The strategy demonstrates strong robustness with consistent positive returns and high win rates over an 18-year backtest period[22][23] --- Model Backtest Results 1. Interest Rate Price-Volume Multi-Cycle Timing Strategy - **Long-Term Performance (2007.12.31 to Latest Report Date)**: - Annualized Return: 6.15% - Maximum Drawdown: 1.52% - Return-to-Drawdown Ratio: 2.25 - Excess Annualized Return: 1.66% (relative to equal-weighted duration benchmark) - Excess Return-to-Drawdown Ratio: 1.17[22] - **Short-Term Performance (Since 2023 End)**: - Annualized Return: 6.93% - Maximum Drawdown: 1.52% - Return-to-Drawdown Ratio: 5.94 - Excess Annualized Return: 2.2% - Excess Return-to-Drawdown Ratio: 2.31[22][23] - **Win Rates (2007-2025)**: - Annual Absolute Return > 0: 100% - Annual Excess Return > 0: 100%[23] - **Yearly Performance Statistics**: - Example Years: - 2008: Absolute Return 17.08%, Excess Return 4.41% - 2014: Absolute Return 13.47%, Excess Return 2.67% - 2024: Absolute Return 9.35%, Excess Return 2.52%[26] --- Quantitative Factors and Construction Methods 1. Factor Name: Interest Rate Structure Indicators (Level, Slope, Convexity) - **Factor Construction Idea**: Transform yield-to-maturity (YTM) data of 1-10 year government bonds into structural indicators to analyze the interest rate market from a mean-reversion perspective[7][9] - **Factor Construction Process**: 1. **Level Structure**: Average YTM across all maturities 2. **Slope Structure**: Difference between long-term and short-term YTM 3. **Convexity Structure**: Second derivative of the yield curve to measure curvature[7][9] - **Factor Evaluation**: The current readings indicate a low level structure, low slope structure, and neutral-to-low convexity structure, suggesting a relatively bearish outlook for the interest rate market[9] --- Factor Backtest Results 1. Interest Rate Structure Indicators - **Current Readings**: - Level Structure: 1.6% (17th percentile over 3 years, 10th percentile over 5 years, 5th percentile over 10 years) - Slope Structure: 0.35% (18th percentile over 3 years, 11th percentile over 5 years, 14th percentile over 10 years) - Convexity Structure: 0.09% (32nd percentile over 3 years, 21st percentile over 5 years, 21st percentile over 10 years)[9]

证券研究报告 | 金融工程 2025 年 6 月 29 日 利率择时信号中性偏空 ——利率市场趋势定量跟踪 20250627 利率市场结构变化 - 10 年期国债到期收益率录得 1.65%，相对上周升高 0.66BP。当前 利率水平、期限和凸性结构读数分别为 1.51%、0.3%、0.02%，从 均值回归视角看，目前处于水平结构点位较低、期限结构点位偏 低、凸性结构点位偏低的状态。 梁雨辰 S1090523070008 liangyuchen2@cmschina.com.cn 敬请阅读末页的重要说明 利率价量周期择时信号：中性偏空 - 利率数据的多周期择时信号为：长周期向上突破、中周期无信号、 短周期向下突破。综合来看，当前合计下行突破 1 票、上行突破 1 票，由于 3 种周期下的同向突破总得票数未达 2/3，最终信号的综 合评分结果为中性震荡。同时，由于价量择时的最新趋势在 6 月 25 日转为看空，随后又转为中性震荡，但当前上行突破信号票数 仍大于等于下行突破信号票数，因此整体而言价量信号呈中性偏空 观点。 公募债基行为跟踪：久期提升、分歧微降 利率价量多周期择时策略表现 - 自 2023 年底以来，策 ...

证券研究报告 | 金融工程 2025 年 5 月 25 日 利率择时信号维持看空 ——利率市场趋势定量跟踪 20250523 利率市场结构变化 - 10 年期国债到期收益率录得 1.72%，相对上周升高 4.15BP。当前 利率水平、期限和凸性结构读数分别为 1.58%、0.27%、-0.04%， 从均值回归视角看，目前处于水平结构点位较低、期限结构点位 较低、凸性结构点位较低的状态。 利率价量周期择时信号：看空 - 利率数据的多周期择时信号为：长周期无信号、中周期向上突破、 短周期向上突破。综合来看，当前合计下行突破 0 票、上行突破 2 票，由于 3 种周期下的同向突破总得票数达到 2/3，最终信号的综 合评分结果为看空。 公募债基行为跟踪：久期微降、分歧微降 利率价量多周期择时策略表现 - 自 2023 年底以来，策略的短期年化收益率为 7.5%，最大回撤为 1.61%，收益回撤比为 6.43，相对业绩基准的超额收益率为 2.35%。 过去的 18 年内，策略逐年绝对收益大于 0 的胜率为 100%，逐年超 额收益大于 0 的胜率为 100%。 - 公募基金最新久期（计入杠杆后）中位数读数为 3.09 ...

Quantitative Models and Construction Methods 1. Model Name: Interest Rate Price-Volume Multi-Cycle Timing Strategy - **Model Construction Idea**: This model uses kernel regression algorithms to identify the trend patterns of interest rates, capturing support and resistance levels. It integrates signals from long, medium, and short investment cycles to form a composite timing strategy[11][23] - **Model Construction Process**: 1. **Signal Generation**: - Use kernel regression to identify support and resistance levels for interest rate data across different cycles (long, medium, short)[11] - Signals are generated based on whether the interest rate breaks through these levels in an upward or downward direction[11] 2. **Cycle Frequency**: - Long cycle: Monthly signal switching - Medium cycle: Bi-weekly signal switching - Short cycle: Weekly signal switching[11] 3. **Composite Signal Scoring**: - If at least two out of three cycles show a downward breakthrough, the signal is "bullish" - If at least two out of three cycles show an upward breakthrough, the signal is "bearish"[11][23] 4. **Portfolio Construction**: - Full allocation to long-duration bonds when at least two cycles show a downward breakthrough and the trend is not upward - 50% allocation to medium-duration bonds and 50% to long-duration bonds when at least two cycles show a downward breakthrough but the trend is upward - Full allocation to short-duration bonds when at least two cycles show an upward breakthrough and the trend is not downward - 50% allocation to medium-duration bonds and 50% to short-duration bonds when at least two cycles show an upward breakthrough but the trend is downward - Equal allocation across short, medium, and long durations in other cases[23] 5. **Stop-Loss Mechanism**: - Adjust holdings to equal allocation when the daily excess return of the portfolio falls below -0.5%[23] 6. **Benchmark**: - Equal-duration strategy: 1/3 allocation to short, medium, and long durations[23] 2. Model Name: Public Bond Fund Duration and Divergence Tracking - **Model Construction Idea**: This model uses an improved regression model to dynamically track the weekly changes in the duration and divergence of public bond funds[13] - **Model Construction Process**: 1. **Duration Calculation**: - Median, 4-week moving average, and mean values of the duration (including leverage) of medium- and long-term pure bond funds are calculated[13][20] 2. **Divergence Measurement**: - Cross-sectional standard deviation of fund durations is used to measure divergence[14] 3. **Yield-to-Maturity (YTM) Analysis**: - Median, 4-week moving average, and mean values of YTM (including leverage) are calculated for the funds[20] --- Model Backtesting Results 1. Interest Rate Price-Volume Multi-Cycle Timing Strategy - **Long-Term Performance (2007.12.31 to Latest Report Date)**: - Annualized Return: 6.3% - Maximum Drawdown: 1.55% - Return-to-Drawdown Ratio: 2 - Excess Return: 1.78% - Excess Return-to-Drawdown Ratio: 0.92[23][24] - **Short-Term Performance (Since 2023 Year-End)**: - Annualized Return: 8.05% - Maximum Drawdown: 1.62% - Return-to-Drawdown Ratio: 6.91 - Excess Return: 2.78% - Excess Return-to-Drawdown Ratio: 2.85[4][23][24] - **Historical Success Rates (18 Years)**: - Absolute Return > 0: 100% - Excess Return > 0: 100%[24] 2. Public Bond Fund Duration and Divergence Tracking - **Duration Metrics**: - Median Duration: 3.13 years - 4-Week Moving Average: 3.19 years - Mean Duration: 3.4 years - Historical 5-Year Percentile: 91.51%[13][14] - **Divergence Metrics**: - Cross-Sectional Standard Deviation: 2.03 years - Historical 5-Year Percentile: 98.46%[14] - **YTM Metrics**: - Median YTM: 1.99% - 4-Week Moving Average: 2.12% - Mean YTM: 2.1%[20]