Report Industry Investment Rating No relevant content provided. Core Viewpoints - Today, convertible bonds declined following the underlying stocks, while the valuation increased on a month - on - month basis [1] - The large - cap value style was relatively dominant, and the trading sentiment in the convertible bond market heated up [1] Summary by Directory 1. Market Main Index Performance - The CSI Convertible Bond Index decreased by 0.18% month - on - month, the Shanghai Composite Index decreased by 0.18%, the Shenzhen Component Index decreased by 0.29%, the ChiNext Index increased by 0.21%, the SSE 50 Index decreased by 0.09%, and the CSI 1000 Index decreased by 1.09% [1] - In terms of market style, large - cap growth rose by 0.42%, large - cap value rose by 0.64%, mid - cap growth decreased by 0.36%, mid - cap value decreased by 0.59%, small - cap growth decreased by 0.04%, and small - cap value decreased by 0.35% [1] 2. Market Fund Performance - The trading volume of the convertible bond market was 83.594 billion yuan, a month - on - month increase of 16.18%; the total trading volume of the Wind All - A was 2.518471 trillion yuan, a month - on - month increase of 17.55% [1] - The net outflow of the main funds in the Shanghai and Shenzhen stock markets was 76.167 billion yuan, and the yield of the 10 - year treasury bond increased by 1.23bp to 1.88% on a month - on - month basis [1] 3. Convertible Bond Valuation - The weighted average closing price of convertible bonds was 128.51 yuan, a month - on - month decrease of 0.17%. The closing price of equity - biased convertible bonds was 176.30 yuan, a month - on - month decrease of 0.40%; the closing price of bond - biased convertible bonds was 116.52 yuan, a month - on - month increase of 0.01%; the closing price of balanced convertible bonds was 124.70 yuan, a month - on - month decrease of 0.21% [2] - The proportion of high - price bonds above 130 yuan was 47.07%, a month - on - month decrease of 0.59pct; the proportion of the 120 - 130 (including 130) range increased by 0.31pct. There were 0 bonds with a closing price below 100 yuan. The median price was 128.34 yuan, a month - on - month decrease of 0.30% [2] - The fitted conversion premium rate of 100 - yuan par value was 27.55%, a month - on - month increase of 0.28pct; the overall weighted par value was 99.40 yuan, a month - on - month decrease of 0.39%. The premium rate of equity - biased convertible bonds was 8.02%, a month - on - month decrease of 0.59pct; the premium rate of bond - biased convertible bonds was 86.45%, a month - on - month increase of 2.88pct; the premium rate of balanced convertible bonds was 22.58%, a month - on - month increase of 0.27pct [2] 4. Industry Performance - In the A - share market, the top three industries with the largest declines were social services (-3.11%), commerce and retail (-2.90%), and computers (-2.39%); the top three industries with the largest increases were banks (+1.52%), coal (+1.11%), and power equipment (+0.43%) [3] - In the convertible bond market, 19 industries declined. The top three industries with the largest declines were machinery and equipment (-4.15%), communications (-2.74%), and household appliances (-1.66%); the top three industries with the largest increases were environmental protection (+2.37%), automobiles (+1.06%), and petroleum and petrochemicals (+0.29%) [3] - In terms of closing price, large - cycle increased by 0.04%, manufacturing decreased by 0.90%, technology decreased by 1.14%, large - consumption decreased by 0.34%, and large - finance decreased by 0.13% [3] - In terms of conversion premium rate, large - cycle increased by 1.1pct, manufacturing increased by 0.98pct, technology increased by 0.66pct, large - consumption increased by 1.3pct, and large - finance increased by 0.7pct [3] - In terms of conversion value, large - cycle decreased by 0.76%, manufacturing decreased by 1.48%, technology decreased by 1.23%, large - consumption decreased by 1.45%, and large - finance decreased by 0.52% [3] - In terms of pure bond premium rate, large - cycle increased by 0.035pct, manufacturing decreased by 1.3pct, technology decreased by 1.8pct, large - consumption decreased by 0.44pct, and large - finance decreased by 0.14pct [4] 5. Industry Rotation - The banking, coal, and power equipment industries led the gains. For example, the daily increase of the banking industry's underlying stocks was 1.52%, and the daily increase of convertible bonds was 0.06%; the daily increase of the coal industry's underlying stocks was 1.11%, and the daily increase of convertible bonds was -0.66%; the daily increase of the power equipment industry's underlying stocks was 0.43%, and the daily increase of convertible bonds was 0.16% [55]

Group 1 - The report constructs a valuation scoring system to assess the price-performance ratio of convertible bond underlying stocks, focusing on quickly and accurately evaluating individual stock valuation levels while controlling for drawdown risks [1][9] - The valuation framework employs both vertical (relative to historical levels) and horizontal (relative to peers) analyses to position stocks in a two-dimensional space, allowing for a comprehensive assessment of their valuation [1][9] - The horizontal analysis identifies which underlying stocks have better valuation cost-effectiveness compared to others, using a set of primary and secondary indicators to filter out unsuitable metrics [1][10][11] Group 2 - The horizontal valuation framework aims to determine which convertible bonds (or underlying stocks) are relatively inexpensive at a given moment, addressing the challenge of cross-industry valuation comparisons [10][11] - The report identifies suitable primary indicators for various industries, categorizing them based on the adequacy of data points, stability across periods, and the dispersion of individual stock valuations [11][12][16] - The report highlights that the PE (3-year non-negative average) and PB indicators are widely applicable across industries, with the introduction of PE (3-year non-negative average) providing a more reliable alternative to traditional PE metrics [17][18] Group 3 - The vertical analysis framework assesses which underlying stocks have improved valuation cost-effectiveness compared to their historical levels, using data from June 2021 to the present [28][29] - The report finds that stocks with low vertical valuations tend to exhibit greater upward elasticity in bullish markets, with those above the 80% valuation threshold showing significantly lower average price increases [29][30] - The report identifies low-valued convertible bond targets worth attention, particularly in industries such as defense, basic chemicals, and construction decoration, which have shown high elasticity in the current market environment [34][36]

Quantitative Models and Construction Methods 1. Model Name: CRR Pricing Model for Convertible Bonds - **Model Construction Idea**: The CRR pricing model uses a binomial tree framework to calculate the theoretical value of convertible bonds, incorporating embedded options, credit spreads, and other factors to improve pricing accuracy compared to traditional models like BSM[15][44]. - **Model Construction Process**: 1. Use the CRR binomial tree model to calculate the theoretical value of convertible bonds. 2. Define the "pricing deviation" as the difference between the CRR theoretical price and the market price. 3. Select bonds with the highest pricing deviation for portfolio construction. 4. Rebalance the portfolio monthly with equal weighting[15][44][45]. - **Model Evaluation**: The CRR model is more precise than traditional models like BSM due to its consideration of embedded clauses and credit spreads[15][44]. 2. Model Name: Low Valuation Momentum Strategy - **Model Construction Idea**: This strategy combines low valuation metrics (e.g., low conversion premium) with momentum indicators (e.g., short-term stock price trends) to identify undervalued convertible bonds with upward potential[48][49]. - **Model Construction Process**: 1. Screen bonds based on criteria such as credit rating (AA- or above), liquidity, and absence of negative historical events. 2. Classify bonds into equity-like, balanced, and debt-like categories based on parity levels. 3. Score bonds within each category based on valuation metrics and momentum indicators. 4. Select the top 10 bonds from each category for portfolio inclusion. 5. Rebalance the portfolio monthly with equal weighting[48][49][51]. - **Model Evaluation**: The strategy effectively combines valuation and momentum factors to capture both undervaluation and positive price trends[48][49]. --- Model Backtesting Results 1. CRR Pricing Model - **Absolute Return (June)**: 3.73% - **Annualized Return (Since 2017)**: 15.56% - **Maximum Drawdown**: 12.08% - **Return-to-Volatility Ratio**: 1.22 - **Return-to-Drawdown Ratio**: 1.29 - **Monthly Win Rate**: 62.22%[44][48]. 2. Low Valuation Momentum Strategy - **Absolute Return (June)**: 2.91% - **Annualized Return (Since 2017)**: 15.39% - **Maximum Drawdown**: 11.26% - **Return-to-Volatility Ratio**: 1.21 - **Return-to-Drawdown Ratio**: 1.37 - **Monthly Win Rate**: 65.56%[49][55]. --- Quantitative Factors and Construction Methods 1. Factor Name: Conversion Premium - **Factor Construction Idea**: The conversion premium measures the relative overvaluation of a convertible bond compared to its parity value, serving as a valuation indicator[13][15]. - **Factor Construction Process**: 1. Use a power function model to fit the relationship between parity value and conversion premium. 2. Calculate the median conversion premium for equity-like, balanced, and debt-like bonds. 3. Track changes in the conversion premium curve over time[13][15]. 2. Factor Name: Implied Volatility - **Factor Construction Idea**: Implied volatility reflects the market's expectations of future stock price fluctuations, derived from convertible bond prices using the BSM model[35][36]. - **Factor Construction Process**: 1. Use the BSM model to reverse-calculate implied volatility from convertible bond prices. 2. Aggregate implied volatility data to calculate the median and weighted average for the market. 3. Monitor changes in implied volatility over time to assess market sentiment[35][36]. --- Factor Backtesting Results 1. Conversion Premium - **Equity-like Bonds**: Median premium increased from 7.72% to 9.18% (+1.46%) - **Balanced Bonds**: Median premium increased from 23.67% to 26.05% (+2.37%) - **Debt-like Bonds**: Median premium increased from 57.49% to 62.77% (+5.28%)[15][18]. 2. Implied Volatility - **Market Median**: Increased from 32.25% to 35.35% (+3.10%) - **Weighted Average**: Increased from 28.93% to 35.24% (+6.41%)[35][36].