Group 1: Report Industry Investment Rating - No relevant content found Group 2: Core Views of the Report - In the medium - term, the expectation of a slow - bull market in the equity market remains solid. With a temporary decline in market risk appetite, the dumbbell strategy is expected to achieve excess returns. The valuation factor and volatility factor are expected to strengthen marginally. In the short - term, attention should be paid to the risk of excess drawdown due to style mismatch in the convertible bond market. It is recommended to maintain a neutral position to enjoy the excess returns brought by the spill - over of the equity bull market, taking into account both growth and defense [1][22] Group 3: Summary by Relevant Catalog 1. Convertible Bond Weekly Thinking - From November 10 to November 14, 2025, the style of the convertible bond market changed significantly, with the tech - growth style retreating and the energy and consumption indices strengthening. The main line of the convertible bond market is not clear, and sector rotation has accelerated. The technology sectors represented by AI computing power and semiconductors have declined, while the power equipment and photovoltaic industries have performed well. The dividend style has strengthened due to risk - aversion and overseas tech valuation bubbles. As the year - end approaches, some investors may lock in profits, and the market is likely to be dominated by rotation, increasing the difficulty of convertible bond trading [11] - In the volatile market, the valuation of bond - like convertible bonds is firm, and the market tends to be defensive in the short - term. As of November 14, 2025, the median price of convertible bonds is close to 134 yuan, a recent high. The market style has shifted from offensive to defensive, with bond - biased convertible bonds performing better than equity - biased ones. The pure - bond premium rate of bond - like convertible bonds has been rising. In terms of valuation, the convertible bond valuation is oscillating at a high level, with the premium rate of bond - like convertible bonds at 84.51%, the balanced convertible bonds at about 22.66%, and the equity - like convertible bonds at 10.18%, down about 1.13 percentage points from the recent high [3][12] - In the volatile market, attention should be paid to the tail risk of the momentum factor to avoid the risk of excess return drawdown caused by trend reversal. The convertible bond momentum factor has performed well this year, mainly because it has captured the "trend effect" in the convertible bond market since Q2 2025. However, with the continuous small - scale outflow of passive funds represented by ETFs, there is a possibility of style switching in the convertible bond market. The momentum effect brought by liquidity premium may be the source of excess returns in the convertible bond market this year. In the short - term, attention should be paid to the risk of excess drawdown due to style mismatch. As the equity market enters the performance verification stage, the valuation factor and volatility factor are expected to strengthen, enabling investors to enjoy the excess returns from the value regression of undervalued convertible bonds and through high - selling and low - buying in the volatile market [4][14][19] - In November, investors are recommended to focus on convertible bonds such as Shangyin, Shouhua, Aola, Jingke, Baolong, Keshun, Yingbo, Wei, Jin 25, and Anji [23] 2. Convertible Bond Market Tracking 2.1 Convertible Bond Market Conditions - The report provides the performance data of various convertible bond indices in different time periods (recent week, recent two weeks, since September, recent month, recent two months, recent half - year, and recent one - year), including the Wande Convertible Bond Energy Index, Wande Convertible Bond Materials Index, etc. [24] 2.2 Convertible Bond Individual Securities - The report shows the top ten and bottom ten individual convertible bonds in terms of price increase and decrease in the recent week [26][27] 2.3 Convertible Bond Valuation - The report presents the valuation trends of bond - like, balanced, and equity - like convertible bonds, as well as the valuation trends of convertible bonds with different parities [28][36] 2.4 Convertible Bond Price - The report shows the proportion trend of high - price bonds and the median price trend of convertible bonds [38]

Core Viewpoint - The bond market in 2025 is characterized by low volatility, which limits the profit potential of traditional trend-following strategies. Quantitative and neutral trading strategies are proposed as effective methods to enhance returns in this low-volatility environment [1][2]. Summary by Sections Current Market Conditions - As of early 2025, China's bond market is experiencing low yields and low volatility, prompting investment institutions to rethink their strategies to navigate this challenging environment [2][6]. - The bond market's volatility has significantly decreased, reaching levels below the 10th percentile since April 2025, influenced by factors such as U.S. tariffs and domestic liquidity conditions [2][6]. Causes of Low Volatility - The low volatility in the bond market is attributed to several factors: 1. **Liquidity Constraints**: The central bank's policies have maintained reasonable liquidity, keeping overnight repo rates around 1.4%, which has limited further declines in bond yields [6][7]. 2. **Economic Expectations**: Weak economic indicators and uncertainties surrounding U.S.-China trade relations have constrained the upward movement of bond yields, with the 10-year government bond yield mostly staying below 1.75% [6][7]. 3. **Supply and Demand Dynamics**: Increased government bond issuance has not significantly impacted the market due to ongoing liquidity support from the central bank [7]. 4. **Arbitrage Strategies**: The widespread use of neutral arbitrage strategies by investment institutions has helped stabilize the market and reduce irrational volatility [7]. Investment Strategies in Low Volatility Market - In response to the low volatility environment, two main strategies are recommended: 1. **Quantitative Strategies**: These strategies utilize historical data and mathematical models to identify trading opportunities. A volatility factor model has been developed, demonstrating predictive capabilities and profitability in low-volatility conditions [9][10][17]. 2. **Neutral Strategies**: These involve constructing both long and short positions to hedge market risks and capture stable returns. The application of classic neutral trading strategies, such as basis trading, term spread trading, and new/old bond spread trading, has shown potential for excess returns [17][18]. Performance of Quantitative Strategies - A quantitative strategy based on a volatility factor was tested, yielding a cumulative return of 26.17 basis points with a win rate of 62.33%, outperforming traditional single-direction strategies [14][22]. - The strategy's performance highlighted areas for improvement, such as enhancing sensitivity to directional signals and optimizing threshold parameters for better risk management [15][16]. Performance of Neutral Strategies - Classic neutral strategies have been effectively employed to exploit market inefficiencies, with examples demonstrating successful basis trading, term spread trading, and new/old bond spread trading [18][19][20][21]. - These strategies have proven to enhance absolute returns and improve the return on assets (ROA) in a low-volatility market [22]. Future Outlook - The bond market's low volatility phase is seen as a transitional period that necessitates a restructuring of investment strategies. The integration of quantitative and neutral strategies is emphasized as crucial for adapting to the new market norm [23]. - Investment institutions are encouraged to enhance their research capabilities and technological integration to better navigate the evolving market landscape [23].

Group 1 - The core index, the China Securities A100 Stable Index, closed at 4591.97 points, with a one-month increase of 2.45%, a three-month increase of 5.37%, and a year-to-date increase of 3.32% [1] - The index is constructed based on volatility and quality factors, selecting securities with high risk exposure to macroeconomic changes for the dynamic index and those with lower risk exposure for the stable index [1] - The top ten holdings of the China Securities A100 Stable Index include Kweichow Moutai (11.53%), CATL (9.21%), China Merchants Bank (7.28%), and others, indicating a concentration in specific large-cap stocks [1] Group 2 - The industry composition of the index shows that industrials account for 23.09%, financials for 16.13%, and major consumer goods for 13.13%, among others, reflecting a diverse sector representation [2] - The index samples are adjusted biannually, with changes implemented on the next trading day after the second Friday of June and December, typically not exceeding 10% of the sample [2] - Special adjustments can occur under certain circumstances, such as delisting or corporate actions like mergers and acquisitions [2]

Group 1 - The core viewpoint of the news is that the CSI 200 Dynamic Index has shown a mixed performance, with a recent increase of 1.34% over the past month but a decline of 7.88% over the last three months and a year-to-date drop of 3.86% [1] - The CSI 200 Dynamic Index is constructed based on volatility and quality factors, selecting securities with high risk exposure to macroeconomic changes for the dynamic index and those with lower risk exposure for the stable index [1] - The index is benchmarked to December 31, 2004, with a base point of 1000.0 points, providing diversified risk-return characteristics for investors [1] Group 2 - The top ten holdings of the CSI 200 Dynamic Index include companies such as Xinyi Technology (3.34%), iFlytek (3.23%), and Zhongke Shuguang (2.94%) [1] - The market capitalization distribution of the CSI 200 Dynamic Index shows that the Shenzhen Stock Exchange accounts for 50.69% and the Shanghai Stock Exchange accounts for 49.31% [1] - In terms of industry composition, the CSI 200 Dynamic Index has a significant allocation to Information Technology (33.46%), followed by Industrial (15.89%) and Financial (13.96%) sectors [2] Group 3 - The index sample is adjusted semi-annually, with adjustments occurring on the next trading day after the second Friday of June and December, with a sample adjustment ratio generally not exceeding 10% [2] - Temporary adjustments to the index may occur under special circumstances, such as delisting of sample companies or corporate actions like mergers and acquisitions [2]

Quantitative Factors and Construction Methods Factor Name: BP (Book-to-Price Ratio) - **Construction Idea**: Measures the valuation of a stock by comparing its book value to its market value [13] - **Construction Process**: - Formula: $ BP = \frac{\text{Current Book Value}}{\text{Current Market Value}} $ [13] Factor Name: BP Three-Year Percentile - **Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Construction Process**: - Formula: BP Three-Year Percentile = Percentile rank of the current BP within the last three years [13] Factor Name: Quarterly EP (Earnings-to-Price Ratio) - **Construction Idea**: Measures the profitability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] Factor Name: Quarterly EP One-Year Percentile - **Construction Idea**: Tracks the relative profitability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly EP One-Year Percentile = Percentile rank of the current Quarterly EP within the last year [13] Factor Name: Quarterly SP (Sales-to-Price Ratio) - **Construction Idea**: Measures the revenue generation capability of a stock relative to its market price [13] - **Construction Process**: - Formula: $ \text{Quarterly SP} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ [13] Factor Name: Quarterly SP One-Year Percentile - **Construction Idea**: Tracks the relative revenue generation capability of a stock over the past year [13] - **Construction Process**: - Formula: Quarterly SP One-Year Percentile = Percentile rank of the current Quarterly SP within the last year [13] Factor Name: Small Market Cap - **Construction Idea**: Captures the size effect by focusing on smaller companies [13] - **Construction Process**: - Formula: $ \text{Small Market Cap} = \log(\text{Market Capitalization}) $ [13] Factor Name: 1-Month Reversal - **Construction Idea**: Captures the short-term reversal effect in stock prices [13] - **Construction Process**: - Formula: $ \text{1-Month Reversal} = \text{Cumulative Return over the Last 20 Trading Days} $ [13] Factor Name: Fama-French Three-Factor 1-Month Residual Volatility - **Construction Idea**: Measures the idiosyncratic risk of a stock based on the Fama-French three-factor model [13] - **Construction Process**: - Formula: $ \text{Residual Volatility} = \text{Standard Deviation of Residuals from Fama-French Three-Factor Regression over the Last 20 Trading Days} $ [13] --- Factor Backtesting Results IC Performance - **BP**: Weekly IC = -4.17%, Monthly IC = 0.88%, Yearly IC = 1.86%, Historical IC = 2.19% [9] - **BP Three-Year Percentile**: Weekly IC = -1.08%, Monthly IC = -0.99%, Yearly IC = 2.58%, Historical IC = 1.58% [9] - **Quarterly EP**: Weekly IC = 2.10%, Monthly IC = -0.48%, Yearly IC = -0.46%, Historical IC = 1.18% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 4.23%, Monthly IC = 3.81%, Yearly IC = 0.98%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = 0.79%, Monthly IC = 0.93%, Yearly IC = 0.53%, Historical IC = 0.74% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 4.80%, Monthly IC = 2.82%, Yearly IC = 2.87%, Historical IC = 1.83% [9] - **Small Market Cap**: Weekly IC = 10.49%, Monthly IC = 8.17%, Yearly IC = 3.61%, Historical IC = 2.05% [9] - **1-Month Reversal**: Weekly IC = 7.22%, Monthly IC = 1.22%, Yearly IC = 3.40%, Historical IC = 2.22% [9] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly IC = 3.60%, Monthly IC = 1.11%, Yearly IC = 3.49%, Historical IC = 2.48% [9] Excess Return Performance (Long-Only Portfolio) - **BP**: Weekly Excess Return = -0.83%, Monthly Excess Return = -1.04%, Yearly Excess Return = 3.02%, Historical Cumulative Excess Return = 28.90% [11] - **BP Three-Year Percentile**: Weekly Excess Return = -0.58%, Monthly Excess Return = -1.51%, Yearly Excess Return = 0.97%, Historical Cumulative Excess Return = -3.21% [11] - **Quarterly EP**: Weekly Excess Return = 0.57%, Monthly Excess Return = 1.10%, Yearly Excess Return = 1.44%, Historical Cumulative Excess Return = 30.83% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.51%, Yearly Excess Return = 3.23%, Historical Cumulative Excess Return = 34.69% [11] - **Quarterly SP**: Weekly Excess Return = -0.01%, Monthly Excess Return = 0.49%, Yearly Excess Return = 0.70%, Historical Cumulative Excess Return = -2.69% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.09%, Monthly Excess Return = 1.25%, Yearly Excess Return = 7.91%, Historical Cumulative Excess Return = 2.23% [11] - **Small Market Cap**: Weekly Excess Return = 0.96%, Monthly Excess Return = 2.76%, Yearly Excess Return = 18.31%, Historical Cumulative Excess Return = 62.57% [11] - **1-Month Reversal**: Weekly Excess Return = 0.83%, Monthly Excess Return = 0.76%, Yearly Excess Return = 3.54%, Historical Cumulative Excess Return = 1.57% [11] - **Fama-French Three-Factor 1-Month Residual Volatility**: Weekly Excess Return = 0.28%, Monthly Excess Return = 0.75%, Yearly Excess Return = 8.69%, Historical Cumulative Excess Return = 18.67% [11]

Group 1 - The A-share market indices closed mixed, with the Shanghai 180 Dynamic Index down by 0.32% to 5437.78 points, with a trading volume of 45.945 billion yuan [1] - The Shanghai 180 Dynamic Index has decreased by 6.45% over the past month, 0.86% over the past three months, and 4.17% year-to-date [1] - The index is based on the Shanghai 180 and 380 indices, selecting securities with high risk exposure to macroeconomic changes for the dynamic index and low risk exposure for the stable index, providing diversified investment targets [1] Group 2 - The top ten holdings of the Shanghai 180 Dynamic Index include China Ping An (11.49%), CITIC Securities (5.23%), and SMIC (3.89%), among others [1] - The index is fully composed of securities listed on the Shanghai Stock Exchange, with a total market share of 100% [1] - The industry composition of the index shows that finance accounts for 33.17%, information technology for 26.76%, and industrials for 14.48%, among other sectors [2] Group 3 - The index sample is adjusted semi-annually, with adjustments occurring on the next trading day after the second Friday of June and December, with a sample change not exceeding 30% [2] - Temporary adjustments may occur under special circumstances, such as delisting or corporate actions like mergers and acquisitions [2]

Core Viewpoint - The A-share market showed mixed performance with the Shanghai 180 Stable Index experiencing a slight decline of 0.03% to close at 11,128.3 points, with a trading volume of 51.95 billion yuan [1] Group 1: Index Performance - The Shanghai 180 Stable Index has decreased by 1.24% over the past month, increased by 2.50% over the last three months, and has declined by 1.06% year-to-date [1] - The index is based on a sample space from the Shanghai 180 and 380 indices, focusing on securities with varying risk exposures to macroeconomic conditions [1] Group 2: Index Holdings - The top ten weighted stocks in the Shanghai 180 Stable Index include Kweichow Moutai (11.91%), China Merchants Bank (6.3%), and Yangtze Power (4.32%) [1] - The index is composed entirely of stocks listed on the Shanghai Stock Exchange [2] Group 3: Sector Allocation - The sector distribution of the index holdings is as follows: Financials (33.92%), Consumer Staples (16.25%), Industrials (13.93%), Materials (8.52%), Utilities (7.52%), Healthcare (6.48%), Energy (5.49%), Consumer Discretionary (3.81%), Communication Services (3.80%), and Information Technology (0.28%) [2] Group 4: Index Adjustment - The index samples are adjusted biannually, typically on the second Friday of June and December, with a sample adjustment limit of 30% [2] - Temporary adjustments may occur under special circumstances, such as delisting or corporate actions like mergers and acquisitions [2]

Group 1 - The core viewpoint of the news is that the 中证A100动态指数 has shown a decline of 4.88% over the past month but has increased by 1.41% year-to-date, indicating mixed performance in the market [1] - The top ten holdings of the 中证A100动态指数 include 宁德时代 (13.11%), 中国平安 (10.74%), 比亚迪 (6.71%), 中信证券 (5.03%), 立讯精密 (3.95%), 中芯国际 (3.53%), 汇川技术 (2.84%), 北方华创 (2.63%), 寒武纪 (2.55%), and 海光信息 (2.53%) [1] - The market capitalization distribution of the 中证A100动态指数 shows that 51.23% of the holdings are from the Shenzhen Stock Exchange, while 48.77% are from the Shanghai Stock Exchange [1] Group 2 - The industry composition of the 中证A100动态指数 indicates that Information Technology accounts for 29.75%, Industrial for 27.99%, Financial for 15.78%, Materials for 8.48%, Consumer Discretionary for 7.88%, Communication Services for 5.04%, Real Estate for 2.76%, and Healthcare for 2.33% [2] - The index sample is adjusted biannually, with adjustments occurring on the next trading day after the second Friday of June and December, with a sample adjustment ratio generally not exceeding 10% [2] - In special circumstances, the index may undergo temporary adjustments, and companies that are delisted will be removed from the index sample [2]