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]

Quantitative Models and Construction Methods - **Model Name**: Multi-period interest rate timing strategy **Model Construction Idea**: The model uses multi-period resonance strategies to capture interest rate trends and generate timing signals based on shape recognition algorithms[10][22] **Model Construction Process**: 1. **Signal Generation**: Utilize kernel regression algorithms to identify support and resistance lines of interest rate data. Analyze the breakthrough patterns of interest rate trends across long, medium, and short cycles[10][22] 2. **Portfolio Construction**: - If at least two cycles show downward breakthroughs and the trend is not upward, allocate fully to long-duration bonds - If at least two cycles show downward breakthroughs but the trend is upward, allocate 50% to medium-duration bonds and 50% to long-duration bonds - If at least two cycles show upward breakthroughs and the trend is not downward, allocate fully to short-duration bonds - If at least two cycles show upward breakthroughs 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 - Stop-loss mechanism: Adjust holdings to equal-weighted allocation if daily excess returns fall below -0.5%[22] **Model Evaluation**: The strategy demonstrates strong performance with consistent positive returns and high excess return ratios over the long term[22][23] Model Backtesting Results - **Multi-period interest rate timing strategy**: - **Short-term annualized return**: 7.27%[4][22] - **Short-term maximum drawdown**: 1.56%[4][22] - **Short-term return-to-drawdown ratio**: 6.23[4][22] - **Short-term excess return**: 2.2%[4][23] - **Long-term annualized return**: 6.17%[22] - **Long-term maximum drawdown**: 1.52%[22] - **Long-term return-to-drawdown ratio**: 2.26[22] - **Long-term excess return**: 1.66%[22] - **Excess return-to-drawdown ratio**: 1.18[22] - **Annual absolute return win rate**: 100%[23] - **Annual excess return win rate**: 100%[23] Quantitative Factors and Construction Methods - **Factor Name**: Interest rate structure indicators (level, term, convexity) **Factor Construction Idea**: Transform yield-to-maturity (YTM) data of 1-10 year government bonds into structural indicators to analyze market trends from a mean-reversion perspective[7][9] **Factor Construction Process**: 1. Calculate the level structure indicator as the average YTM across maturities 2. Compute the term structure indicator as the difference between long-term and short-term YTM 3. Derive the convexity structure indicator based on the curvature of the yield curve[7][9] **Factor Evaluation**: The indicators provide insights into the current state of the interest rate market, showing low levels across all three structures[7][9] - **Factor Name**: Multi-period interest rate timing signals **Factor Construction Idea**: Use kernel regression algorithms to identify interest rate trends and generate timing signals based on breakthroughs across long, medium, and short cycles[10] **Factor Construction Process**: 1. Apply kernel regression to identify support and resistance lines for interest rate data 2. Analyze breakthrough patterns across different cycles (monthly for long-term, bi-weekly for medium-term, weekly for short-term)[10] **Factor Evaluation**: The signals are effective in capturing market trends, with the latest signals indicating a neutral-to-bearish stance[10] Factor Backtesting Results - **Interest rate structure indicators**: - **Level structure**: Current reading is 1.51%, positioned at 6%, 4%, and 2% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Term structure**: Current reading is 0.3%, positioned at 13%, 8%, and 10% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Convexity structure**: Current reading is 0.02%, positioned at 18%, 11%, and 11% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Multi-period interest rate timing signals**: - **Long-term signal**: Upward breakthrough[10] - **Medium-term signal**: No signal[10] - **Short-term signal**: Downward breakthrough[10] - **Overall signal**: Neutral-to-bearish[10]

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 support and resistance levels in interest rate trends. It integrates signals from long, medium, and short investment cycles to form a composite timing strategy[10][23]. - **Model Construction Process**: 1. **Signal Identification**: - Use kernel regression to capture the shape of interest rate trends and identify support and resistance levels[10]. - Classify signals into long-cycle (monthly frequency), medium-cycle (bi-weekly frequency), and short-cycle (weekly frequency)[10]. 2. **Signal Aggregation**: - Count the number of upward and downward breakthroughs across the three cycles. - If at least two cycles show the same directional breakthrough, the composite signal is determined based on the majority[10]. 3. **Portfolio Construction**: - Allocate assets based on the composite signal: - Full allocation to long-duration bonds if at least two cycles show downward breakthroughs and the trend is not upward. - Equal allocation to medium- and long-duration bonds if at least two cycles show downward breakthroughs but the trend is upward. - Full allocation to short-duration bonds if at least two cycles show upward breakthroughs and the trend is not downward. - Equal allocation to medium- and short-duration bonds if at least two cycles show upward breakthroughs but the trend is downward. - Equal allocation across short-, medium-, and long-duration bonds in other cases[23]. 4. **Stop-Loss Mechanism**: - Adjust holdings to equal allocation if the daily excess return of the portfolio falls below -0.5%[23]. 5. **Benchmark**: - The benchmark is an equal-duration strategy with one-third allocation to short-, medium-, and long-duration bonds[23]. - **Model Evaluation**: The model effectively captures multi-cycle resonance in interest rate trends and provides a systematic approach to timing strategies[23]. --- Model Backtesting Results 1. Interest Rate Price-Volume Multi-Cycle Timing Strategy - **Long-Term Performance (2007.12.31 to Latest Report Date)**: - Annualized Return: 6.19% - Maximum Drawdown: 1.53% - Return-to-Drawdown Ratio: 2.26 - Excess Annualized Return: 1.67% - Excess Return-to-Drawdown Ratio: 1.18[23][24] - **Short-Term Performance (Since 2023 Year-End)**: - Annualized Return: 7.5% - Maximum Drawdown: 1.61% - Return-to-Drawdown Ratio: 6.43 - Excess Annualized Return: 2.35% - Excess Return-to-Drawdown Ratio: 2.47[23][24] - **Historical Success Rates (18 Years)**: - Absolute Return > 0: 100% - Excess Return > 0: 100%[24] - **Year-by-Year Performance**: - 2008: Absolute Return 17.08%, Excess Return 4.41% - 2009: Absolute Return 1.03%, Excess Return 1.20% - 2010: Absolute Return 4.59%, Excess Return 2.49% - 2011: Absolute Return 7.25%, Excess Return 2.10% - 2012: Absolute Return 4.33%, Excess Return 0.68% - 2013: Absolute Return 0.91%, Excess Return 1.67% - 2014: Absolute Return 13.47%, Excess Return 2.67% - 2015: Absolute Return 11.14%, Excess Return 2.31% - 2016: Absolute Return 3.20%, Excess Return 1.76% - 2017: Absolute Return 1.11%, Excess Return 1.38% - 2018: Absolute Return 11.16%, Excess Return 2.36% - 2019: Absolute Return 6.24%, Excess Return 1.44% - 2020: Absolute Return 3.46%, Excess Return 0.47% - 2021: Absolute Return 5.40%, Excess Return 0.33% - 2022: Absolute Return 3.62%, Excess Return 0.47% - 2023: Absolute Return 4.81%, Excess Return 0.46% - 2024: Absolute Return 9.35%, Excess Return 2.52% - 2025: Absolute Return 1.14%, Excess Return 0.75%[24][27] --- Quantitative Factors and Construction Methods 1. Factor Name: Interest Rate Structural Indicators (Level, Term, Convexity) - **Factor Construction Idea**: These factors decompose the yield-to-maturity (YTM) data of government bonds into three structural dimensions: level, term, and convexity. The factors are analyzed from a mean-reversion perspective[7][9]. - **Factor Construction Process**: 1. **Data Transformation**: - Convert the YTM data of 1- to 10-year government bonds into three structural indicators: - **Level**: Average YTM across all maturities - **Term**: Difference between long-term and short-term YTM - **Convexity**: Curvature of the yield curve[7]. 2. **Historical Percentile Analysis**: - Calculate the rolling 3-, 5-, and 10-year percentiles for each structural indicator to assess their relative positions[8][9]. - **Factor Evaluation**: These factors provide insights into the current state of the interest rate market and its deviation from historical norms[7][9]. --- Factor Backtesting Results 1. Interest Rate Structural Indicators - **Level**: - Current Value: 1.58% - Weekly Change: -0.24BP - Historical Percentiles: 10% (3-Year), 6% (5-Year), 3% (10-Year)[9] - **Term**: - Current Value: 0.27% - Weekly Change: +4.42BP - Historical Percentiles: 7% (3-Year), 4% (5-Year), 8% (10-Year)[9] - **Convexity**: - Current Value: -0.04% - Weekly Change: -6.28BP - Historical Percentiles: 8% (3-Year), 5% (5-Year), 5% (10-Year)[9]

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]