Quantitative Models and Construction - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model combines Price-to-Book ratio (PB) and Return on Equity (ROE) to construct a stock selection strategy[25] **Model Construction Process**: The PB-ROE-50 model selects stocks based on their PB and ROE metrics. Stocks with favorable PB and ROE values are included in the portfolio. The model uses a monthly rebalancing approach to optimize the portfolio[25][26] **Model Evaluation**: The model demonstrates positive excess returns in most stock pools, indicating its effectiveness in capturing value and profitability factors[25][26] - **Model Name**: Institutional Research Tracking Strategy **Model Construction Idea**: This strategy leverages institutional research activities (public and private) to identify stocks with potential excess returns[27] **Model Construction Process**: The strategy tracks stocks that are frequently researched by public and private institutions. Stocks with higher research frequency are included in the portfolio. The portfolio is rebalanced periodically to reflect updated research trends[27][28] **Model Evaluation**: The strategy shows consistent positive excess returns, suggesting that institutional research activities can be a reliable indicator for stock selection[27][28] - **Model Name**: Block Trade Strategy **Model Construction Idea**: The strategy identifies stocks with high block trade activity and low volatility to construct a portfolio[31] **Model Construction Process**: Stocks are selected based on two criteria: high block trade transaction ratios and low 6-day transaction volatility. The portfolio is rebalanced monthly to maintain these characteristics[31][32] **Model Evaluation**: The strategy has mixed results, with negative excess returns in the recent 2-week period, but positive performance over the year[31][32] - **Model Name**: Directed Issuance Strategy **Model Construction Idea**: The strategy focuses on stocks involved in directed issuance events to capture potential investment opportunities[36] **Model Construction Process**: Stocks are selected based on the announcement date of directed issuance events. The strategy considers market capitalization, rebalancing frequency, and position control to construct the portfolio[36][37] **Model Evaluation**: The strategy shows negative excess returns in the recent 2-week period, raising questions about its effectiveness under current market conditions[36][37] Model Backtesting Results - **PB-ROE-50 Model**: - Excess return in CSI 500: -0.82% - Excess return in CSI 800: 1.45% - Excess return in the entire market: 0.75%[25][26] - **Institutional Research Tracking Strategy**: - Public research excess return: 1.03% - Private research excess return: 1.89%[27][28] - **Block Trade Strategy**: - Excess return relative to CSI All Index: -0.57%[31][32] - **Directed Issuance Strategy**: - Excess return relative to CSI All Index: -1.13%[36][37] Quantitative Factors and Construction - **Factor Name**: Liquidity Factor **Factor Construction Idea**: Measures the liquidity of stocks to identify those with higher trading activity[20] **Factor Construction Process**: The liquidity factor is calculated using metrics such as turnover rate and trading volume. Stocks with higher liquidity scores are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns in the recent 2-week period, indicating its effectiveness in capturing market liquidity trends[20] - **Factor Name**: Leverage Factor **Factor Construction Idea**: Evaluates the financial leverage of companies to identify those with higher risk-adjusted returns[20] **Factor Construction Process**: The leverage factor is derived from financial ratios such as debt-to-equity and interest coverage. Companies with optimal leverage levels are favored[20] **Factor Evaluation**: The factor demonstrates positive returns, suggesting its utility in identifying financially stable companies[20] - **Factor Name**: Profitability Factor **Factor Construction Idea**: Captures the profitability of companies to identify those with strong earnings performance[20] **Factor Construction Process**: The profitability factor is calculated using metrics such as ROE, ROA, and net profit margin. Stocks with higher profitability metrics are given positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its effectiveness in identifying profitable companies[20] - **Factor Name**: Valuation Factor **Factor Construction Idea**: Measures the relative valuation of stocks to identify undervalued opportunities[20] **Factor Construction Process**: The valuation factor is derived from metrics such as Price-to-Earnings (P/E) and Price-to-Book (P/B) ratios. Stocks with lower valuation scores are assigned positive weights[20] **Factor Evaluation**: The factor demonstrates positive returns, supporting its use in identifying undervalued stocks[20] - **Factor Name**: Non-linear Market Capitalization Factor **Factor Construction Idea**: Captures the non-linear relationship between market capitalization and stock returns[20] **Factor Construction Process**: The factor is constructed using a non-linear transformation of market capitalization data. Stocks with optimal market capitalization are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its ability to capture market capitalization trends effectively[20] - **Factor Name**: Beta Factor **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements[20] **Factor Construction Process**: The beta factor is calculated using historical return data and market indices. Stocks with lower beta values are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] - **Factor Name**: Residual Volatility Factor **Factor Construction Idea**: Evaluates the idiosyncratic risk of stocks to identify those with stable performance[20] **Factor Construction Process**: The residual volatility factor is derived from the standard deviation of residuals in a regression model of stock returns against market returns[20] **Factor Evaluation**: The factor shows negative returns, indicating its limited utility in the recent market conditions[20] - **Factor Name**: Growth Factor **Factor Construction Idea**: Captures the growth potential of companies based on their financial performance[20] **Factor Construction Process**: The growth factor is calculated using metrics such as revenue growth and earnings growth. Stocks with higher growth rates are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] Factor Backtesting Results - **Liquidity Factor**: Return: 0.36%[20] - **Leverage Factor**: Return: 0.34%[20] - **Profitability Factor**: Return: 0.27%[20] - **Valuation Factor**: Return: 0.18%[20] - **Non-linear Market Capitalization Factor**: Return: 0.18%[20] - **Market Capitalization Factor**: Return: 0.11%[20] - **Beta Factor**: Return: -0.65%[20] - **Residual Volatility Factor**: Return: -0.55%[20] - **Growth Factor**: Return: -0.21%[20]

1. Report Industry Investment Rating No relevant information provided. 2. Core View of the Report - From the beginning of 2025 to October 10, the convertible bond market underperformed the equity market, with the CSI Convertible Bond Index rising by 17.1% and the CSI All-Share Index rising by 23.3%. In the long term, convertible bonds remain relatively high-quality assets due to the persistent pattern of strong demand exceeding supply. However, the current valuation level is relatively high, so attention should be paid to structural opportunities [1][4]. 3. Summary by Relevant Catalogs Market Conditions - From October 9 to 10, 2025 (2 trading days), convertible bonds first rose and then fell. The CSI Convertible Bond Index had a change of 0% (previous trading cycle: +1.6%), and the CSI All-Share Index changed by -0.3% (previous trading cycle: +2.0%). Since the beginning of 2025, the convertible bond market has underperformed the equity market [1]. - By rating, high-rated bonds (AA+ and above), medium-rated bonds (AA), and low-rated bonds (AA- and below) had changes of +0.45%, +0.50%, and -0.31% respectively this week. Low-rated bonds performed poorly [1]. - By convertible bond size, large-scale convertible bonds (bond balance > 5 billion yuan), medium-scale convertible bonds (balance between 500 million and 5 billion yuan), and small-scale convertible bonds (balance < 500 million yuan) had changes of +0.32%, +0.12%, and -0.16% respectively this week. Large-scale convertible bonds performed the best [1]. - By conversion parity, ultra-high parity bonds (conversion value > 130 yuan), high parity bonds (conversion value between 110 and 130 yuan), medium parity bonds (conversion value between 90 and 110 yuan), low parity bonds (conversion value between 70 and 90 yuan), and ultra-low parity bonds (conversion value < 70 yuan) had changes of +0.03%, -0.17%, +0.03%, +0.14%, and +0.15% respectively this week. High parity bonds closed down [2]. Convertible Bond Price, Parity, and Conversion Premium Rate - As of October 10, 2025, there were 420 outstanding convertible bonds (423 at the close on September 30), with a balance of 587.832 billion yuan (589.024 billion yuan at the close on September 30). The average convertible bond price was 132.67 yuan (131.41 yuan at the close on September 30), the average parity was 105.35 yuan (100.18 yuan at the close on September 30), and the average conversion premium rate was 27.6% (27.1% at the close on September 30) [3]. - The conversion premium rate of medium parity convertible bonds (conversion value between 90 and 110 yuan) was 30.1%, higher than the median conversion premium rate of medium parity convertible bonds since 2018 (20.3%) [3]. Convertible Bond Performance and Allocation Directions - This week, convertible bonds first rose and then fell, and the CSI Convertible Bond Index had a change of 0%. Since the beginning of 2025, the convertible bond market has underperformed the equity market. Given the persistent pattern of strong demand exceeding supply in the convertible bond market, convertible bonds remain relatively high-quality assets in the long term. Currently, the overall valuation level is high, so attention should be paid to structural opportunities [4]. Convertible Bond Increase Situation - The top 15 convertible bonds in terms of increase this week include Zhonghuanzhuan 2, Guanzhong Convertible Bond, Haomei Convertible Bond, etc. The increase rates of these convertible bonds range from 6.01% to 20.00% [22].

Investment Rating - The report maintains a "Buy" rating for the company [5]. Core Insights - The company is expected to achieve significant growth in its two-wheeler segment, with projected sales of 2.6 million and 2.39 million units for 2024 and the first half of 2025, respectively, representing year-on-year growth of 77% and 100% [1][27]. - The gross margin is anticipated to continue rising, reaching 21.1% and 23.7% for 2024 and the first half of 2025, placing the company in a leading position within the industry [1][31]. Summary by Sections Two-Wheeler Business - The company focuses on providing a full lifecycle user experience for its core target audience, with a strong emphasis on smart technology as a key differentiator in its product offerings [2][42]. - The company has established a robust brand presence, with a significant portion of its sales coming from younger consumers, who represent 66% of its customer base under 35 years old [2][47]. - The company has successfully optimized its product structure and achieved economies of scale, leading to a continuous increase in gross margins [1][31]. Research and Development System - The company's R&D system is characterized by a high degree of coupling among its organizational structure, mechanisms, and talent, which is crucial for maintaining competitive advantages [3][22]. - The dual-line R&D mechanism allows the company to balance short-term and long-term goals effectively, ensuring continuous innovation [3][22]. Future Outlook - The company plans to expand its store network significantly, with projections of 7,600 and 8,700 stores for 2024 and the first half of 2025, respectively, and aims to reach 9,500 stores by the end of 2025 [3][26]. - Continuous upgrades to its Over-The-Air (OTA) services will enhance user experience throughout the product lifecycle [3][26]. Profit Forecast and Valuation - The company is projected to achieve net profits of 2 billion, 2.7 billion, and 3.5 billion yuan for 2025, 2026, and 2027, respectively, with corresponding P/E ratios of 23, 18, and 14 [4][5].

- The report utilizes a methodology from the industry rotation series to track the configuration signals and business indicators of various industries, including coal, livestock farming, steel, structural materials, and fuel refining industries [9] Quantitative Models and Construction Methods Coal Industry Model - **Model Name**: Coal Industry Profit and Revenue Growth Estimation Model - **Model Construction Idea**: The model estimates monthly revenue and profit growth of the coal industry based on the changes in price and production capacity factors [10] - **Model Construction Process**: - The long-term contract mechanism for thermal coal determines the sales price for the next month based on the price index of the last month - Monthly revenue and profit growth are estimated using the year-on-year changes in price factors and production capacity factors [10] - **Model Evaluation**: The model predicts that the coal industry profit for October 2025 will continue to decline year-on-year due to coal prices being lower than the same period last year [14] Livestock Farming Model - **Model Name**: Livestock Supply and Demand Gap Estimation Model - **Model Construction Idea**: The model uses the relationship between the number of breeding sows and the quarterly pig slaughter rate to estimate the supply-demand gap for pigs six months later [15] - **Model Construction Process**: - The model assumes a stable proportional relationship between quarterly pig slaughter and the number of breeding sows six months prior - Formula: $ \text{Slaughter Coefficient} = \frac{\text{Quarterly Pig Slaughter}}{\text{Breeding Sow Inventory (lagged 6 months)}} $ [15] - Potential production capacity after 6 months is calculated as: $ \text{Potential Production Capacity (6 months later)} = \text{Breeding Sow Inventory (current month)} \times \text{Slaughter Coefficient (6 months prior)} $ [16] - Potential demand after 6 months is calculated as: $ \text{Potential Demand (6 months later)} = \text{Quarterly Pig Slaughter (6 months prior)} $ [16] - **Model Evaluation**: Historical experience shows that the slaughter coefficient method effectively identifies pig price upward cycles [16] Steel Industry Model - **Model Name**: Steel Industry Profit and Unit Profit Estimation Model - **Model Construction Idea**: The model predicts monthly profit growth and calculates unit profit for the steel industry by considering comprehensive steel prices and cost indicators such as iron ore, coke, pulverized coal, and scrap steel [18] - **Model Construction Process**: - Comprehensive steel prices and cost indicators are used to predict monthly profit growth - Unit profit is calculated based on the difference between steel prices and costs [18] - **Model Evaluation**: The model predicts that the steel industry profit for September 2025 will grow year-on-year, but the PMI rolling 12-month average remains flat, maintaining a neutral configuration viewpoint [23] Structural Materials and Building Engineering Model - **Model Name**: Glass and Cement Industry Profit Tracking Model - **Model Construction Idea**: The model tracks profitability changes in the glass and cement manufacturing industries using price and cost indicators, and designs configuration signals based on profitability changes [25] - **Model Construction Process**: - Price and cost indicators are used to track profitability changes - Configuration signals are designed based on profitability changes [25] - **Model Evaluation**: - Glass industry profit turned positive year-on-year in September 2025, leading to an upgrade to a positive configuration signal [30] - Cement industry profit remained flat year-on-year, and no positive signals were observed in new housing starts, maintaining a neutral configuration viewpoint [30] Fuel Refining and Oil Services Model - **Model Name**: Fuel Refining and Oil Services Profit and Configuration Signal Model - **Model Construction Idea**: The model estimates industry profit growth and cracking spreads based on changes in refined fuel prices and crude oil prices, and designs configuration signals based on oil prices, cracking spreads, and new drilling changes [31] - **Model Construction Process**: - Refined fuel price changes and crude oil price changes are used to estimate industry profit growth and cracking spreads - Configuration signals are designed based on oil prices, cracking spreads, and new drilling changes [31] - **Model Evaluation**: - The model predicts that the fuel refining industry profit for September 2025 will grow year-on-year due to lower inventory costs from recent low oil prices [31] - Observations show that oil prices in September 2025 were lower than the same period last year, maintaining a neutral configuration viewpoint for the fuel refining and oil services industries [37][38] Model Backtesting Results Coal Industry Model - **Profit Growth**: Predicted to continue declining year-on-year in October 2025 due to lower coal prices compared to the same period last year [14] Livestock Farming Model - **Breeding Sow Inventory**: 4,038 million heads as of August 2025, slightly decreased month-on-month [17] - **Potential Production Capacity (26Q1)**: 19,361 million heads [17] - **Potential Demand (26Q1)**: 19,476 million heads [17] - **Supply-Demand Balance**: Slightly tight [17] Steel Industry Model - **Profit Growth**: Predicted to grow year-on-year in September 2025 [23] - **PMI Rolling Average**: Remained flat for 12 months, not exceeding the threshold [23] Structural Materials and Building Engineering Model - **Glass Industry Profitability**: Turned positive year-on-year in September 2025 [30] - **Cement Industry Profitability**: Remained flat year-on-year in September 2025 [30] - **Manufacturing PMI Rolling Average**: Remained flat for 12 months [30] - **Housing Sales Area**: Observed a year-on-year decline in August 2025 [30] Fuel Refining and Oil Services Model - **Fuel Refining Industry Profitability**: Predicted to grow year-on-year in September 2025 due to lower inventory costs [31] - **Oil Price**: Observed to be lower than the same period last year in September 2025 [37] - **New Drilling Activity**: No significant year-on-year changes observed in the US [38]

Investment Rating - The report maintains a "Buy" rating for the automotive and automotive parts industry [5]. Core Insights - In Q3 2025, Tesla's global deliveries exceeded expectations, with a year-on-year increase of 7.4% and a quarter-on-quarter increase of 29.4%, reaching 497,000 units. The Model 3 and Model Y standard versions were launched in North America with reduced starting prices [1]. - Xpeng's sales surpassed 40,000 units in September, marking a year-on-year increase of 94.7% and a quarter-on-quarter increase of 10.3% [1]. - NIO's deliveries also showed growth, with a year-on-year increase of 64.1% and a quarter-on-quarter increase of 11.0%, totaling 34,749 units in September [1]. Summary by Sections Tesla and New Forces Sales Tracking - Tesla's global delivery volume reached 497,000 units in Q3 2025, with Model 3 and Y sales contributing significantly [1]. - Xpeng delivered 41,581 units in September, while NIO and Li Auto reported deliveries of 34,749 and 33,951 units, respectively [1]. Order Trends and Delivery Cycles - Tesla's delivery cycles for the domestic Model 3 and Model Y have been extended, indicating high demand as the peak season approaches [2]. - New energy vehicle manufacturers like Li Auto and NIO are also experiencing changes in delivery cycles, with some models seeing extended wait times [2]. Company Recommendations - The report recommends investing in companies such as NIO, Xpeng, SAIC Motor, and Geely Automobile, as well as parts suppliers like Fuyao Glass and Top Group [3]. - It highlights the potential in the robotics and intelligent driving themes, suggesting a focus on companies involved in these sectors [3]. Earnings Forecast and Valuation Table - The earnings per share (EPS) and price-to-earnings (PE) ratios for key companies are provided, with NIO, Xpeng, and SAIC Motor all receiving a "Buy" rating based on their projected performance [4].

2025 年 10 月 10 日 晨会速递 分析师点评 市场数据 总量研究 【金工】市场网下打新参与度仍在上升——打新市场跟踪月报 20251009 2025 年 9 月，共 11 只新股上市，其中主板 3 只、创业板 5 只、北交所 3 只，募集 金额共计 116.9 亿元，沪深两市新股发行规模环比增长。新股首日平均涨幅环比虽下 降但仍处较高水平：主板新股首日平均上涨 131.33%，创业板新股首日平均涨 251.9%。网下打新市场询价账户数量稳步上升，报价入围率略降。5 亿规模账户当月 打新收益率约为 A 类：0.15%，C 类 0.13%。 【债券】二级市场价格整体持续回调，资产类型有望得到大幅扩围——REITs 月度观 察（20250901-20250930） 截至 2025 年 9 月 30 日，我国公募 REITs 产品数量达 75 只，合计发行规模达 1966.2 亿元（不含扩募）。2025 年 9 月 1 日-2025 年 9 月 30 日（以下简称"本月"），我 国已上市公募 REITs 的二级市场价格整体呈现波动下行的趋势。与其他主流大类资产 相比，回报率由高至低排序分别为：黄金>美股>A ...

Investment Rating - The report maintains a "Buy" rating for the controlled nuclear fusion industry, indicating an expected investment return exceeding 15% over the next 6-12 months compared to the market benchmark index [7]. Core Insights - The successful installation of the BEST Dewar base marks a significant milestone in the controlled nuclear fusion industry, signaling the commencement of a concentrated bidding period for various projects [1][2]. - The domestic fusion industry is progressing positively, with multiple projects advancing and new initiatives being announced, suggesting an upcoming phase of intensive bidding [3]. - The strategic value of fusion energy is highlighted by increasing electricity demands driven by AI and cloud computing, with major tech companies entering the fusion energy market [4]. Summary by Sections Project Developments - The BEST project has accelerated its timeline, with the main assembly starting two months ahead of schedule. Recent announcements indicate multiple tenders related to the project components [2][3]. - Other projects, such as "Xinghuo No. 1" and "China Circulation No. 4," are also progressing, with significant milestones achieved in environmental assessments and approvals [3]. Technological Advancements - Key technological breakthroughs have been reported, including the introduction of new superconducting materials and advancements in plasma control systems, which are crucial for the development of fusion energy [3][4]. Market Potential - The report emphasizes the long-term growth potential of the controlled nuclear fusion industry, particularly in high-value segments such as magnet systems, vacuum chambers, and power systems, which are expected to benefit from ongoing industry advancements [4][5].

1. Report Industry Investment Rating No industry investment rating information is provided in the report. 2. Core Viewpoints of the Report - The secondary - market prices of publicly - offered REITs in China showed a fluctuating downward trend in September 2025, with relatively poor performance compared to other mainstream asset classes. However, the total net inflow of main funds increased, indicating a rise in market trading enthusiasm. Meanwhile, relevant policies in September 2025 are expected to further expand the asset types of REITs [2][17][44] 3. Summary by Directory 3.1 Primary Market 3.1.1 Listed Projects - As of September 30, 2025, there were 75 publicly - offered REITs in China, with a total issuance scale of 196.62 billion yuan (excluding expansion). Among them, transportation infrastructure REITs had the largest issuance scale, reaching 68.771 billion yuan, followed by park infrastructure REITs with 31.835 billion yuan. In September 2025, two new REITs were listed: CICC Vipshop Outlet Mall REIT on September 12 with an issuance scale of 3.48 billion yuan, and Huaxia CapitaLand Commercial REIT on September 29 with an issuance scale of 2.287 billion yuan, both being of the consumption infrastructure type [11] 3.1.2 Pending - Listing Projects - As of September 30, 2025, there were 17 REITs pending listing, including 11 initial - offering REITs and 6 REITs pending expansion. In September, the project status of several REITs was updated, such as CITIC Construction Investment Shenyang International Software Park Closed - end Infrastructure Securities Investment Fund being updated to "Approved" [14][15] 3.2 Secondary - Market Performance 3.2.1 Price Trends - **At the major - asset level**: From September 1 to September 30, 2025, the secondary - market prices of publicly - offered REITs in China showed a fluctuating downward trend. The returns of REITs were - 1.08%, ranking behind other major asset classes. The order of returns from high to low was: gold > US stocks > A - shares > convertible bonds > pure bonds > crude oil > REITs [17] - **At the underlying - asset level**: In terms of project attributes, the secondary - market price trends of equity - type REITs and franchise - type REITs diverged in September. Equity - type REITs rose, with a return of 0.54%, while franchise - type REITs fell, with a return of - 0.77%. Among different underlying - asset types, energy - type REITs had the largest increase, and the underlying - asset categories with better returns were energy, new infrastructure, and ecological and environmental protection, with returns of 1.09%, 0.05%, and - 0.52% respectively [21][22] - **At the single - REIT level**: In September, 15 REITs rose and 60 REITs fell. The top three in terms of increase were CICC Liandong Science and Technology Innovation REIT, Hongtu Innovation Yantian Port REIT, and GF Chengdu High - tech Investment Industrial Park REIT, with increases of 3.87%, 2.33%, and 1.73% respectively. The top three in terms of decline were Huatai Jiangsu Expressway REIT, ICBC Inner Mongolia Energy Clean Energy REIT, and E Fund Guangzhou Development Zone High - tech Industrial Park REIT, with declines of 8.16%, 7%, and 6.69% respectively [25] 3.2.2 Trading Volume and Turnover Rate - **At the underlying - asset level**: In September, the trading volume of publicly - offered REITs decreased compared to the previous month. New infrastructure - type REITs led in the average daily turnover rate. The total trading volume of 75 listed REITs in September was 10.95 billion yuan, and the average daily turnover rate was 0.58%. The top three in terms of trading volume were consumption infrastructure, transportation infrastructure, and park infrastructure, with trading volumes of 2.36 billion, 2.16 billion, and 1.61 billion yuan respectively. The top three in terms of average daily turnover rate were new infrastructure, ecological and environmental protection, and consumption infrastructure, with rates of 1.09%, 0.87%, and 0.73% respectively [28] - **At the single - REIT level**: In terms of trading volume, the top three in September were CICC Vipshop Outlet Mall REIT, Bosera Shekou Industrial Park REIT, and Huaxia CapitaLand Commercial REIT, with trading volumes of 166 million, 84 million, and 78 million shares respectively. In terms of trading amount, the top three were CICC Vipshop Outlet Mall REIT, Huaxia CapitaLand Commercial REIT, and Southern Runze Technology Data Center REIT, with trading amounts of 729 million, 509 million, and 415 million yuan respectively. In terms of turnover rate, the top three were CICC Vipshop Outlet Mall REIT, Huaxia CapitaLand Commercial REIT, and Huatai Jiangsu Expressway REIT, with turnover rates of 55.41%, 48.89%, and 30.07% respectively [30] 3.2.3 Main - Fund Inflow and Block - Trading Situation - **Main - fund inflow situation**: In September, the total net inflow of main funds reached 87.51 million yuan, and the market trading enthusiasm increased compared to the previous month. At the underlying - asset level, the top three underlying - asset types in terms of net inflow of main funds were consumption infrastructure, new infrastructure, and park infrastructure, with net inflows of 56.13 million, 49.8 million, and 18.58 million yuan respectively. At the single - REIT level, the top three REITs in terms of net inflow of main funds were Southern Runze Technology Data Center REIT, CICC Vipshop Outlet Mall REIT, and Huaxia Capital Outlets REIT, with net inflows of 51.33 million, 27.05 million, and 20.03 million yuan respectively [33] - **Block - trading situation**: In September, the total block - trading volume was 1.31 billion yuan, a decrease compared to the previous month. There were block trades on 20 trading days in September. The block - trading volume on September 8 was the highest in the month, reaching 233.35 million yuan. At the single - REIT level, the top three in terms of block - trading volume were Huaxia Shenzhen International REIT, Huaxia Capital Outlets REIT, and CICC Yinli Consumption REIT, with trading volumes of 242.86 million, 168.81 million, and 104.31 million yuan respectively, and corresponding average discount/premium rates of - 0.52%, + 0.12%, and + 0.20% respectively [39] 3.3 Relevant Policies - In September 2025, nine departments including the Ministry of Commerce jointly issued the "Notice on Strengthening and Promoting the Expansion and Upgrading of the 15 - Minute Convenient Living Circle in Cities", proposing to give priority to supporting the issuance of infrastructure - related real - estate investment trusts (REITs) for consumption infrastructure projects such as community commercial complexes, neighborhood centers, department stores, and vegetable markets. The General Office of the National Development and Reform Commission issued the "Notice on Further Improving the Regular Declaration and Recommendation of Real - Estate Investment Trusts (REITs) in the Infrastructure Sector", which proposed to accelerate the declaration of projects with mature asset types, increase the organization of projects with large potential issuance space, actively promote the issuance of projects with new asset types, and optimize the expansion mechanism [44][45]

1. Report Industry Investment Rating No relevant content provided. 2. Core View of the Report - As of the end of September 2025, the balance of outstanding credit bonds in China was 30.49 trillion yuan. In September 2025, the issuance of credit bonds increased month - on - month, with a net financing of 1398.89 billion yuan. The issuance of industrial bonds showed significant growth, while the net financing of urban investment bonds was negative [1][9]. - In September 2025, the trading volume of urban investment bonds increased month - on - month but decreased year - on - year, and the trading volume of industrial bonds decreased both month - on - month and year - on - year. The credit spreads of both urban investment bonds and industrial bonds widened compared to the previous month [2][41]. 3. Summary According to the Directory 3.1 Credit Bond Issuance and Maturity 3.1.1 Credit Bond Issuance - As of the end of September 2025, the balance of outstanding credit bonds was 30.49 trillion yuan. From September 1 to 30, 2025, the issuance of credit bonds was 12355.38 billion yuan, a month - on - month increase of 10.27%, with a total repayment of 10956.49 billion yuan and a net financing of 1398.89 billion yuan [1][9]. - **Urban Investment Bonds**: As of the end of September 2025, the balance of outstanding urban investment bonds was 15.31 trillion yuan. In September 2025, the issuance was 5039.05 billion yuan, a month - on - month increase of 0.84% and a year - on - year increase of 9.78%. The net financing of urban investment entities was - 105.01 billion yuan. In terms of regions, Jiangsu had the highest issuance, and in terms of ratings, AA + and AAA - rated bonds accounted for a relatively high proportion [10][13][20]. - **Industrial Bonds**: As of the end of September 2025, the balance of outstanding industrial bonds was 15.18 trillion yuan. In September 2025, the issuance was 7316.33 billion yuan, a month - on - month increase of 17.85% and a year - on - year increase of 15.04%. The net financing of industrial entities was 1503.9 billion yuan. In terms of industries, the public utilities sector had the highest issuance, and in terms of ratings, AAA - rated bonds accounted for 90.52% [22][24][29]. 3.1.2 Credit Bond Maturity - **Urban Investment Bonds**: From October to December 2025, Jiangsu, Shandong, and Zhejiang had relatively large maturity scales of urban investment bonds, all exceeding 100 billion yuan [29]. - **Industrial Bonds**: From October to December 2025, the public utilities, non - banking finance, building decoration, transportation, and real estate industries had relatively large maturity scales of credit bonds, all exceeding 100 billion yuan [33]. 3.2 Credit Bond Trading and Spreads 3.2.1 Credit Bond Trading - **Urban Investment Bonds**: In September 2025, the trading volume of urban investment bonds was 10210.31 billion yuan, with a month - on - month increase and a year - on - year decrease. The turnover rate was 6.67% [37]. - **Industrial Bonds**: In September 2025, the trading volume of industrial bonds was 12677.1 billion yuan, with both month - on - month and year - on - year decreases. The turnover rate was 8.35% [41]. 3.2.2 Credit Bond Spreads - **Urban Investment Bonds**: In September 2025, the credit spreads of urban investment bonds of all levels widened compared to the previous month. For example, the average credit spread of AAA - rated urban investment bonds was 57bp, 6bp wider than in August 2025. Regionally, different regions showed different spread levels and changes [41][44]. - **Industrial Bonds**: In September 2025, the credit spreads of credit bonds of all levels of industrial entities widened compared to the previous month. For example, the average credit spread of AAA - rated industrial entities was 53bp, 3bp wider than in August 2025. By industry, different industries had different spread levels and changes [47][49].

- The report tracks the performance of new stock issuances in September 2025, noting that 11 new stocks were listed, raising a total of 11.689 billion yuan, a 185.58% increase from the previous month[1][12][13] - Among these, 8 stocks were issued offline, raising 10.628 billion yuan, a 314.65% increase from the previous month[1][12][13] - The number of accounts participating in initial inquiries has steadily increased, with 9194 accounts for the main board and 8306 for the dual innovation board (comprising the ChiNext and STAR Market)[2][24][25] - The average first-day increase for main board stocks was 131.33%, while for the dual innovation board, it was 251.91%[2][24][25] - The offline subscription rates for A and C class investors were 0.11‰ and 0.11‰ for the main board, and 0.22‰ and 0.20‰ for the dual innovation board, respectively[2][24][25] - The report provides a detailed calculation method for new stock issuance returns, using the formula: $$ \text{Single account stock issuance return} = \min(\text{account size}, \text{subscription limit}) \times \text{winning rate} \times \text{return rate} $$ $$ \text{A/B/C class investors' full return} = \text{subscription limit} \times \text{A/B/C class offline winning rate} \times \text{return rate} $$[41] - For September 2025, the return rates for a 5 billion yuan account were 0.026% for A class and 0.025% for C class on the main board, and 0.125% for A class and 0.103% for C class on the ChiNext board[42][43][44][45][46][47] - The cumulative return rates for 2025 were 1.285% for A class and 1.164% for C class accounts[48][49][50] - In a full subscription scenario, the returns for A class accounts were 133,000 yuan on the main board and 877,000 yuan on the ChiNext board, while for C class accounts, the returns were 127,000 yuan on the main board and 727,000 yuan on the ChiNext board[51][52][54] - The report also evaluates the performance of fund products and institutions in new stock issuances, listing the top-performing funds and institutions based on their participation and winning rates[57][58][60][61][62][64][65][66][67]