Quantitative Models and Construction Methods 1. Model Name: CCBA Pricing Model - **Model Construction Idea**: The CCBA pricing model is used to calculate the pricing deviation of convertible bonds, defined as the difference between the market price and the model price, adjusted for redemption probability[6][24] - **Model Construction Process**: - The pricing deviation is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCBA\ Model\ Price} - 1 $ - Here, the "Convertible Bond Price" represents the market price of the bond, and the "CCBA Model Price" is derived from the CCBA pricing model[6][24] - The model incorporates historical volatility as a central parameter to determine the deviation level[7] - **Model Evaluation**: The model effectively identifies valuation ranges for convertible bonds, providing insights into their relative attractiveness[6] 2. Model Name: CCB_out Pricing Model - **Model Construction Idea**: This model builds upon the CCBA model by incorporating delisting risk to refine the pricing deviation calculation[24] - **Model Construction Process**: - The pricing deviation is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCB\_out\ Model\ Price} - 1 $ - The "CCB_out Model Price" adjusts the CCBA model price by accounting for delisting probabilities[24] - Convertible bonds are categorized into three domains: debt-biased, balanced, and equity-biased, with the lowest deviation bonds selected for each domain[24] - **Model Evaluation**: The model demonstrates strong stability and adaptability, achieving consistent returns even in volatile market conditions[24] 3. Model Name: Return Decomposition Model - **Model Construction Idea**: This model decomposes the returns of convertible bonds into three components: bond floor returns, equity-driven returns, and valuation-driven returns[17] - **Model Construction Process**: - The model uses historical data to separate the total return of convertible bonds into: - Bond floor returns, representing the fixed-income component - Equity-driven returns, reflecting the impact of the underlying stock's performance - Valuation-driven returns, capturing changes in the bond's relative pricing[17][21] - **Model Evaluation**: The model provides a detailed understanding of the drivers of convertible bond performance, aiding in strategy optimization[17] --- Quantitative Factors and Construction Methods 1. Factor Name: Pricing Deviation Factor (CCB_out) - **Factor Construction Idea**: Measures the relative valuation of convertible bonds by comparing market prices to model-derived prices[24] - **Factor Construction Process**: - The factor is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCB\_out\ Model\ Price} - 1 $ - Bonds with the lowest deviation are selected for further analysis[24] - **Factor Evaluation**: The factor effectively identifies undervalued bonds, contributing to the success of valuation-based strategies[24] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the price momentum of the underlying stock over different time horizons[29] - **Factor Construction Process**: - Momentum scores are calculated based on the stock's returns over the past 1, 3, and 6 months, with equal weighting applied to each period[29] - **Factor Evaluation**: The factor enhances the responsiveness of valuation-based strategies, improving their adaptability to market trends[29] 3. Factor Name: Turnover Factor - **Factor Construction Idea**: Measures the trading activity of convertible bonds to identify liquidity and investor interest[33] - **Factor Construction Process**: - The factor is derived from: - Bond turnover rates over 5-day and 21-day periods - The ratio of bond turnover to stock turnover over the same periods[33] - **Factor Evaluation**: The factor effectively identifies actively traded bonds, improving the liquidity profile of selected portfolios[33] --- Backtesting Results of Models 1. CCBA Pricing Model - **Annualized Return**: 8.6% - **Annualized Volatility**: 11.6% - **Maximum Drawdown**: 19.9% - **Information Ratio (IR)**: Not explicitly provided[6] 2. CCB_out Pricing Model - **Annualized Return**: 21.8% - **Annualized Volatility**: 13.6% - **Maximum Drawdown**: 15.6% - **Information Ratio (IR)**: 2.10[27] 3. Return Decomposition Model - **Annualized Return**: Not explicitly provided - **Annualized Volatility**: Not explicitly provided - **Maximum Drawdown**: Not explicitly provided - **Information Ratio (IR)**: Not explicitly provided[17] --- Backtesting Results of Factors 1. Pricing Deviation Factor (CCB_out) - **Annualized Return**: 21.8% - **Annualized Volatility**: 13.6% - **Maximum Drawdown**: 15.6% - **Information Ratio (IR)**: 2.10[27] 2. Momentum Factor - **Annualized Return**: 24.5% - **Annualized Volatility**: 14.3% - **Maximum Drawdown**: 11.9% - **Information Ratio (IR)**: 2.39[31] 3. Turnover Factor - **Annualized Return**: 23.4% - **Annualized Volatility**: 15.4% - **Maximum Drawdown**: 15.9% - **Information Ratio (IR)**: 2.15[35]

Quantitative Models and Construction 1. Model Name: CCBA Pricing Deviation Model - **Model Construction Idea**: The model evaluates the valuation level of convertible bonds by calculating the pricing deviation, which is defined as the difference between the market price and the model price derived from the CCBA model[6] - **Model Construction Process**: - Pricing deviation is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCBA\ Model\ Price} - 1 $ - Here, "Convertible Bond Price" represents the market price of the bond, and "CCBA Model Price" is the theoretical price derived from the CCBA model[6] - Historical data is used to determine the percentile levels of the pricing deviation, and the future returns of convertible bonds are analyzed based on different deviation intervals[6][9] - **Model Evaluation**: The model indicates that the current convertible bond market is in a moderately valued range, with a pricing deviation of 0.2%, corresponding to the 58.3% and 48.3% percentiles for the periods since 2018 and 2021, respectively[6] 2. Model Name: Regression Model for Convertible Bond Returns - **Model Construction Idea**: This model uses pricing deviation and YTM spread as explanatory variables to predict the future six-month returns of convertible bonds[12] - **Model Construction Process**: - The regression model is constructed with the following variables: - Explanatory variables: Pricing deviation and YTM spread - Dependent variable: Future six-month returns of convertible bonds - The regression includes sign constraints to ensure the model aligns with economic intuition[12] - **Model Evaluation**: The model demonstrates that convertible bonds in low-price, low-valuation intervals tend to have higher expected returns. However, the current prediction for the next six months is neutral, with an expected return of 0.58%[12] 3. Model Name: Return Decomposition Model - **Model Construction Idea**: This model decomposes the returns of convertible bonds into three components: bond floor returns, equity-driven returns, and valuation-driven returns[15] - **Model Construction Process**: - The model uses the CCB model to calculate the bond floor and equity-driven returns, while the valuation-driven returns are derived as the residual[15] - **Model Evaluation**: The model highlights that in the past month, equity-driven returns contributed -0.79%, and valuation-driven returns contributed -1.55% to the overall performance of the convertible bond index[15][19] --- Quantitative Factors and Construction 1. Factor Name: CCB_Out Pricing Deviation - **Factor Construction Idea**: This factor adjusts the CCBA pricing deviation by incorporating delisting risks to improve valuation accuracy[22] - **Factor Construction Process**: - The adjusted pricing deviation is calculated as: $ Adjusted\ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCB\_Out\ Model\ Price} - 1 $ - Here, "CCB_Out Model Price" accounts for delisting risks in the theoretical pricing[22] - **Factor Evaluation**: The factor is used in multiple strategies, such as low-valuation strategies, to identify undervalued convertible bonds. It has demonstrated strong stability and performance over time[22] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: This factor captures the momentum of the underlying stock prices of convertible bonds over different time horizons[25] - **Factor Construction Process**: - Momentum scores are calculated based on the equal-weighted returns of the underlying stocks over the past 1, 3, and 6 months[25] - **Factor Evaluation**: When combined with the adjusted pricing deviation factor, the momentum factor enhances the elasticity of strategies, leading to higher returns in certain market conditions[25] 3. Factor Name: Turnover Factor - **Factor Construction Idea**: This factor identifies convertible bonds with high trading activity, which may indicate better liquidity and market interest[30] - **Factor Construction Process**: - The turnover factor is calculated using: - Convertible bond turnover rates over 5 and 21 days - The ratio of convertible bond turnover to stock turnover over the same periods[30] - **Factor Evaluation**: The factor is particularly effective in identifying high-liquidity bonds within low-valuation pools, contributing to the success of high-turnover strategies[30] --- Backtesting Results of Models 1. CCBA Pricing Deviation Model - **Six-Month Average Return**: 1.5% - **Six-Month Win Rate**: 72%[6][9][11] 2. Regression Model for Convertible Bond Returns - **Expected Six-Month Return**: 0.58% - **Optimistic Scenario**: 3.91% - **Pessimistic Scenario**: -3.06%[12] 3. Return Decomposition Model - **Equity-Driven Return (Past Month)**: -0.79% - **Valuation-Driven Return (Past Month)**: -1.55%[15][19] --- Backtesting Results of Factors 1. CCB_Out Pricing Deviation - **Annualized Return (2018-2025)**: 21.8% - **Annualized Excess Return**: 12.4% - **IR**: 2.12[25] 2. Momentum Factor - **Annualized Return (2018-2025)**: 24.5% - **Annualized Excess Return**: 14.9% - **IR**: 2.41[29] 3. Turnover Factor - **Annualized Return (2018-2025)**: 23.2% - **Annualized Excess Return**: 13.8% - **IR**: 2.15[33]