Investment Rating - The industry investment rating is "Overweight" [2] Core Insights - The report highlights the ongoing active research in life sciences and the global wave of biotechnology revolution, which is accelerating integration into economic and social development, providing new solutions to major challenges such as health, climate change, resource security, and food security. The National Development and Reform Commission has issued the "14th Five-Year Plan for Bioeconomic Development," indicating a trillion-yuan market potential in the bioeconomy [5][12]. Summary by Sections 1. Industry Market Performance - The synthetic biology sector saw an increase of 1.13% in the week of May 26 to May 30, 2025, outperforming the Shanghai Composite Index by 1.16% and the ChiNext Index by 2.53% [6][20]. 2. Company Business Progress - Shanghai Puranwei and the Shanghai Academy of Agricultural Sciences signed a strategic cooperation agreement to develop mycelium leather technology, aiming to create a new type of biological material to replace traditional leather [26]. - Angel Yeast announced a 230 million yuan investment in a project focused on serum-free cell culture medium technology, marking its entry into the synthetic biology sector [26]. - Xiangsheng Technology unveiled its Shanghai product headquarters, focusing on the large-scale application of bio-based materials like FDCA and PEF [27]. 3. Industry Financing Tracking - The report notes an acceleration in financing for synthetic biology companies, with nearly a hundred companies completing new financing rounds since the beginning of 2025 [37]. - Haobo Pharmaceutical completed a $50 million B+ round of financing to advance its antisense oligonucleotide drug AHB-137 for chronic hepatitis B [37]. - Swiss biotechnology company GlycoEra raised $130 million in a B round to develop its IgG4-targeting protein degradation agents [37].

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - The supply of urban investment bonds has seasonally weakened, and the market has entered a stock or even de - stock phase. Weak - qualified entities are accelerating their exit, increasing the scarcity of coupon assets. The secondary market trading activity has increased due to the "deposit relocation" [1][12][14]. 3. Summary According to Relevant Catalogs 2.1 Weak Entities Accelerate Exit, Coupon Scarcity Increases 2.1.1 Issuance and Repayment: Seasonal Weakening of Urban Investment Bond Supply - As of May 31, 2025, 3797 urban investment entities under the HA scope issued 280.2 billion yuan of bonds and repaid 351.5 billion yuan, with a net repayment of 71.3 billion yuan. The net repayment scale decreased by about 10.2 billion yuan month - on - month and increased by about 37.3 billion yuan year - on - year. The issuance scale was the lowest in the same period in the past three years. Since 2024, the cumulative net repayment has been 2.5 billion yuan. AA and below weak - qualified entities have cumulatively net - repaid 585.7 billion yuan, while AAA entities have net - borrowed 519 billion yuan [12][16]. - From an administrative perspective, all administrative - level entities were in a net - repayment state in May. The net - repayment amounts from high to low were prefecture - level cities (24.3 billion yuan), county - level regions (17.1 billion yuan), provincial - level (16.8 billion yuan), and park - level (13.1 billion yuan) [16]. - From a rating perspective, all rating entities were in a net - repayment state in May. The net - repayment amounts from high to low were AA (27.7 billion yuan), AAA (25.6 billion yuan), AA+ (15.8 billion yuan), below AA (140 million yuan), and unrated (90 million yuan) [17]. - From a variety perspective, the net financing amounts of various bond varieties from high to low were corporate bonds (11.4 billion yuan) and private placement bonds (6.6 billion yuan). The net - repayment amounts from high to low were SCP (44.2 billion yuan), enterprise bonds (21.4 billion yuan), MTN (10.2 billion yuan), CP (8.6 billion yuan), and PPN (4.9 billion yuan) [17]. - From a term perspective, only bonds with a term of over 3 years were in a net - borrowing state in May, with a net borrowing of 35.9 billion yuan. The net - repayment amounts of other term bonds from high to low were 2 - year (46.3 billion yuan), 6 - month to 1 - year (39 billion yuan), 3 - year (9.2 billion yuan), 6 - month and below (8.6 billion yuan), and 1 - year (4.2 billion yuan) [17]. - From a regional perspective, the provinces with the highest net financing in May were Shandong (7.3 billion yuan), Fujian (2.5 billion yuan), and Tibet (1 billion yuan). The provinces with the highest net - repayment were Jiangsu (18.2 billion yuan), Zhejiang (9.2 billion yuan), and Hubei (8.5 billion yuan) [18]. 2.1.2 Maturity Pressure: About 7.7 Trillion Yuan to Mature Before the End of 2026 - As of May 31, 2025, the maturity pressure of 3797 urban investment bonds under the HA scope before the end of 2026 is about 7.7 trillion yuan, with 3.4 trillion yuan in 2025 and 4.4 trillion yuan in 2026. By the end of 2025, the remaining maturity pressure is about 335.06 billion yuan (assuming 100% exercise of callable bonds), with maturity peaks in June (56.93 billion yuan), August (53.09 billion yuan), and September (57.12 billion yuan) [39]. - The top 5 provinces with the remaining maturity amounts by the end of 2025 are Jiangsu, Shandong, Zhejiang, Sichuan, and Hubei [40]. - The top 5 cities are Qingdao, Nanjing, Suzhou, Chengdu, and Nantong [41]. - The top 5 districts and counties are Jiangning District of Nanjing, Huangdao District (including the West Coast New Area) of Qingdao, Pudong New Area of Shanghai, Huangpu District of Guangzhou, and Wuzhong District of Suzhou [41]. - The top 5 parks are Xi'an High - tech Industrial Development Zone, Guangzhou Economic and Technological Development Zone, Suzhou High - tech Industrial Development Zone, Zhengzhou Airport Economy Comprehensive Experimental Zone, and Taizhou Medical High - tech Industrial Development Zone [41]. - The top 5 entities are Jiangsu Communications Holding Co., Ltd., Hunan Expressway Group Co., Ltd., Zhejiang Communications Investment Group Co., Ltd., Shandong Hi - Speed Group Co., Ltd., and Xi'an Hi - tech Holdings Co., Ltd. [41]. 2.1.3 Primary Subscription: Average of 3.00 Times, Continued High - Level Allocation Sentiment - As of May 31, 2025, among the urban investment bonds issued in the month, 103.3 billion yuan of bonds disclosed bidding data, with a cumulative bidding scale of 309.7 billion yuan and an average subscription multiple of 3.00 times, a decrease of 0.06 times month - on - month [44]. - In terms of administrative levels, the subscription sentiment of county - level and park - level entities significantly increased. The average subscription multiples of provincial, prefecture - level, county - level, and park - level entities were 1.99 times (a decrease of 0.26 times month - on - month), 3.16 times (a decrease of 0.23 times month - on - month), 4.09 times (an increase of 0.98 times month - on - month), and 3.47 times (an increase of 0.45 times month - on - month) respectively [46]. - In terms of bond ratings, investors favored the credit - sinking strategy. The average subscription multiples of AAA, AA+, AA, AA(2), and AA - were 1.26 times (a decrease of 0.36 times month - on - month), 2.94 times (a decrease of 0.08 times month - on - month), 4.24 times (an increase of 0.75 times month - on - month), 3.51 times (an increase of 0.27 times month - on - month), and 2.53 times (a decrease of 0.26 times month - on - month) respectively [46]. - In terms of bond terms, the sentiment for long - term bonds remained high. The average subscription multiples for bonds within 1 year, 1 - 2 years, 2 - 3 years, 3 - 5 years, and over 5 years were 2.14 times (a decrease of 0.4 times month - on - month), 3.57 times (an increase of 0.18 times month - on - month), 4.2 times (an increase of 1.19 times month - on - month), 3.27 times (a decrease of 0.15 times month - on - month), and 3.47 times (an increase of 0.4 times month - on - month) respectively [47]. 2.2 Deposit Relocation Triggers Credit Market, Trading Activity Increases 2.2.1 Valuation Spread: Yield Continues to Decline Driven by Demand - Side - In May 2025, due to the loose monetary policy, the central level of capital interest rates declined, and the coupon advantage of credit bonds became prominent. The reduction of bank deposit rates led to the "deposit relocation" effect, increasing the allocation demand for credit bonds by wealth management products. Urban investment bond yields showed a unilateral decline. However, at the end of the month, the bond market adjusted due to tariff policy fluctuations and institutional behavior changes [54]. - In the short - term, the spreads of each implied rating for short - term bonds have reached historical lows. The main capital gain space may lie in the compression of grade spreads and term spreads. For 1 - year bonds, the yields of AAA, AA+, AA, and AA(2) decreased by 9.1bp, 9.1bp, 9.1bp, and 10.1bp to 1.74%, 1.79%, 1.84%, and 1.89% respectively; for 3 - year bonds, they decreased by 9.0bp, 9.0bp, 14.0bp, and 16.0bp to 1.84%, 1.92%, 2.00%, and 2.11% respectively; for 5 - year bonds, they decreased by 7.5bp, 7.5bp, 12.5bp, and 13.5bp to 1.96%, 2.05%, 2.17%, and 2.37% respectively [55]. - Vertically, short - term spreads have reached new lows, while term spreads and grade spreads still have room for compression. As of May 31, the valuation yields of urban investment bonds with each implied rating from 1 - year to 5 - year have reached historical lows, and the three - year percentiles are all at extremely low levels of 5% and below. The credit spreads have also reached lows, with the three - year percentiles of 1 - year and 3 - year ratings below 10%. Only 5 - year bonds still have compression space [59]. 2.2.2 Secondary Trading: Increased Activity Month - on - Month, Medium - and Long - Term Bonds Lead the Gains - In May 2025, the sample trading records of urban investment bonds were about 16,000, with an average daily trading volume of about 841, a month - on - month increase of 1.1%. The average daily trading volume reached a new high this year. The taken trading volume was about 12,000, accounting for 76%, an increase of 3 percentage points from the previous month. The long - short ratio was 3.41, an increase of about 0.46 basis points from the previous month [63]. - In terms of bond ratings, the trading proportion of AAA - rated bonds was 9.7%, an increase of 0.4 percentage points month - on - month; AA+ was 21.5%, a decrease of 0.6 percentage points; AA was 23.7%, an increase of 2.2 percentage points; AA(2) was 35.8%, a slight decrease of 0.1 percentage point; AA - was 9.4%, a decrease of 1.8 percentage points. - In terms of terms, the trading proportion of bonds within 1 year was 31.2%, a significant decrease of 7.4 percentage points month - on - month; 1 - 3 years was 44.7%, an increase of 1.9 percentage points; 3 - 5 years was 21.0%, a significant increase of 4.9 percentage points; over 5 years was 3.3%, an increase of 0.7 percentage points [64].

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The company's revenue for Q1 2025 was 32.61 billion yuan, representing a year-over-year increase of 10.9%, with an adjusted net profit of 4.58 billion yuan, up 4.4% year-over-year. The gross margin was 54.6%, a decrease of 0.3 percentage points year-over-year but an increase of 0.5 percentage points quarter-over-quarter [4][5] - The Daily Active Users (DAU) reached a historical high of 408 million, growing 3.6% year-over-year, while Monthly Active Users (MAU) were 712 million, up 2.1% year-over-year. The average daily usage time per user was 133.8 minutes, with total usage time increasing by 5.9% year-over-year [4][5] - The company's e-commerce business saw a Gross Merchandise Volume (GMV) of 332.3 billion yuan in Q1 2025, reflecting a year-over-year growth of 15.4%. The number of active buyers reached 135 million, with significant growth from small and medium-sized businesses [5] - Online marketing revenue was 18 billion yuan, an increase of 8.0% year-over-year, driven mainly by external circulation. The local life sector saw marketing consumption grow over 50% year-over-year [6] - The company launched the 2.0 version of its AI application, which includes multi-modal editing capabilities, enhancing user engagement and marketing efficiency [7] - Revenue projections for 2025-2027 are estimated at 142.21 billion yuan, 154.96 billion yuan, and 168.18 billion yuan respectively, with adjusted net profits expected to be 20.16 billion yuan, 23.66 billion yuan, and 27.28 billion yuan [8][9] Financial Summary - For the fiscal year 2024, total revenue is projected at 126.90 billion yuan, with a year-over-year growth of 12%. The NON-GAAP net profit is expected to be 17.72 billion yuan, reflecting a significant increase of 72% [11] - The company’s gross margin is expected to improve gradually, reaching 57.1% by 2027, while the net profit margin is projected to increase to 14.8% [12]

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Insights - The company reported Q1 2025 revenue of 326.1 billion RMB, a year-over-year increase of 10.9%, and an adjusted net profit of 45.8 billion RMB, up 4.4% year-over-year. The gross margin was 54.6%, a decrease of 0.3 percentage points year-over-year but an increase of 0.5 percentage points quarter-over-quarter [4][5] - Daily Active Users (DAU) reached a record high of 408 million, growing 3.6% year-over-year, while Monthly Active Users (MAU) reached 712 million, up 2.1% year-over-year. The average daily usage time per user was 133.8 minutes, with total usage time increasing by 5.9% year-over-year [4][5] - The company's e-commerce segment saw a Gross Merchandise Volume (GMV) of 332.3 billion RMB in Q1 2025, representing a year-over-year growth of 15.4%. The number of active buyers reached 135 million, with significant growth from small and medium-sized businesses [5] - Online marketing revenue was 18 billion RMB, an increase of 8.0% year-over-year, driven primarily by external circulation. The local life sector saw marketing spending grow over 50% year-over-year [6] - The company launched the 2.0 version of its AI tool, which includes multi-modal visual language capabilities, enhancing user engagement and marketing efficiency [7] - Revenue projections for 2025-2027 are 1,422.1 billion RMB, 1,549.6 billion RMB, and 1,681.9 billion RMB, respectively, with adjusted net profits expected to be 201.6 billion RMB, 236.6 billion RMB, and 272.8 billion RMB [8][9] Financial Summary - For 2025, the company expects total revenue of 142.2 billion RMB, a 12% increase from 2024, and a NON-GAAP net profit of 20.2 billion RMB, reflecting a 14% increase [11] - The projected earnings per share (EPS) for 2025 is 4.70 RMB, with a price-to-earnings (P/E) ratio of 10.14 [11]

Investment Rating - Industry Rating: Overweight [1] Core Insights - The demand for green electricity is expected to increase due to direct connections, and offshore wind projects are progressing steadily [1][18] - The report highlights the importance of various segments within the power equipment industry, including photovoltaic, wind energy, energy storage, hydrogen energy, and grid equipment [3][4] Summary by Sections Photovoltaic - June production is expected to decline, with price trends remaining sticky; the impact of rush installations on prices is weakening [3][11] - The main industry chain prices are anticipated to remain stable but under downward pressure due to weak domestic demand [13][14] - Investment recommendation focuses on companies with high certainty in the BC technology trend, including Longi Green Energy and Aiko Solar [17] Wind Energy - Offshore wind projects are entering a positive phase, with significant projects in Guangdong and Shandong progressing [18][19] Energy Storage - The release of the 136 document in Inner Mongolia aims to promote green electricity connections, with a mechanism price set at 0.3035 yuan/kWh [20][22] - Bulgaria has launched the largest battery storage system in the EU, with a capacity of 496.2MWh [23] Hydrogen Energy - The hydrogen drone industrial park is set to be established in Jiangxi, with a total investment of approximately 480 million yuan [29] - The hydrogen energy sector is accelerating, with a focus on hydrogen production and storage [28][30] Grid Equipment - The State Grid has announced a new batch of candidates for ultra-high voltage equipment, with a total bid amount of 519 million yuan [32] - The integration of source-network-load-storage is being accelerated in Henan province, promoting local consumption of renewable energy [32][33] Humanoid Robots - Companies like Honor and UBTECH are advancing in the humanoid robot sector, with significant developments in technology and applications [34][36] - The humanoid robot industry is expected to enter a mass production phase by 2025, with a focus on key components [38] Electric Vehicles - CATL's solid-state batteries are expected to achieve small-scale production by 2027, with a focus on high-profit companies [39][41] - The report emphasizes the importance of lithium battery technology and the shift towards lower-cost lithium iron phosphate batteries [42]

Investment Rating - Industry Investment Rating: Overweight [1] Core Insights - Green electricity direct connection is expected to boost demand, and offshore wind projects are progressing steadily [1] - The report highlights the stable development of offshore wind projects, with significant tenders and construction activities in various regions [18][19] - The energy storage sector is seeing policy support, with the introduction of market-driven pricing for renewable energy [20][22] - Hydrogen energy applications are accelerating, with new projects and government support for hydrogen production and storage [28][30] - The power grid equipment sector is advancing with new high-voltage equipment tenders and integrated energy solutions [32][33] Summary by Sections 1.1 Photovoltaics - June production is declining, and the price trend remains sticky, with a slight decrease in silicon material and N-type battery prices [11][12] - The report suggests a cautious outlook for the second quarter of 2025, with potential downward pressure on prices due to weak domestic demand [13][14] - Investment focus on companies with stable earnings and high certainty in the BC technology trend, including Longi Green Energy and Aiko Solar [17] 1.2 Wind Power - Offshore wind projects are entering a positive phase, with significant tenders announced for various projects [18][19] - The report emphasizes the importance of monitoring the progress of these projects and their impact on the industry [18] 1.3 Energy Storage - The introduction of a market-driven pricing mechanism for renewable energy in Inner Mongolia is a significant development [20][22] - The report notes the completion of a large-scale battery storage system in Bulgaria, marking a milestone in the EU [23] 1.4 Hydrogen Energy - The establishment of a hydrogen drone industrial park in Jiangxi is highlighted, with a total investment of approximately 480 million yuan [29] - The report discusses the international collaboration on hydrogen pipelines between the UK and Germany, enhancing energy security [28] 1.5 Power Grid Equipment - The State Grid has announced a new batch of high-voltage equipment candidates, with a total bid amount of 519 million yuan [32] - The report discusses the integration of source-network-load-storage systems in Henan province, promoting local consumption of renewable energy [32] 1.6 Humanoid Robots - The entry of major companies like Honor into the humanoid robotics sector is noted, indicating a growing market potential [34][35] - The report suggests that the humanoid robot industry is expected to enter a production phase in 2025, with significant investment opportunities [38] 1.7 Lithium Batteries - CATL's solid-state battery technology is projected to achieve small-scale production by 2027, representing a significant advancement in battery technology [39] - The report highlights the ongoing developments in lithium battery materials and the shift towards more cost-effective solutions [40][41]

- Model Name: Size Rotation Model; Construction Idea: The model aims to rotate between large-cap and small-cap stocks based on macroeconomic indicators, market conditions, and micro characteristics; Construction Process: The model uses HA large-cap and small-cap as proxy variables, and the excess return relative to the equal-weighted benchmark is calculated. The formula is: $ \text{Excess Return} = \text{Portfolio Return} - \text{Benchmark Return} $; Evaluation: The model effectively captures the rotation between large-cap and small-cap stocks, providing significant excess returns[3][12][18] - Model Name: Value-Growth Rotation Model; Construction Idea: The model rotates between value and growth stocks based on macroeconomic indicators, market conditions, and micro characteristics; Construction Process: The model uses HA value and growth as proxy variables, and the excess return relative to the equal-weighted benchmark is calculated. The formula is: $ \text{Excess Return} = \text{Portfolio Return} - \text{Benchmark Return} $; Evaluation: The model effectively captures the rotation between value and growth stocks, providing significant excess returns[15][23][26] Model Backtest Results - Size Rotation Model, Annualized Excess Return: 11.1%, IR: 1.40, Monthly Win Rate: 64.43%[18] - Value-Growth Rotation Model, Annualized Excess Return: 18.73%, IR: 2.02, Monthly Win Rate: 70.47%[23] Annual Performance of Size Rotation Model - 2013: Excess Return: 11.99%, IR: 2.3594, Monthly Win Rate: 66.67%[21] - 2014: Excess Return: 45.30%, IR: 6.7613, Monthly Win Rate: 75.00%[21] - 2015: Excess Return: 62.95%, IR: 4.6008, Monthly Win Rate: 91.67%[21] - 2016: Excess Return: 0.53%, IR: 0.0784, Monthly Win Rate: 58.33%[21] - 2017: Excess Return: 17.82%, IR: 2.8949, Monthly Win Rate: 83.33%[21] - 2018: Excess Return: 1.62%, IR: 0.2670, Monthly Win Rate: 41.67%[21] - 2019: Excess Return: 0.09%, IR: 0.0171, Monthly Win Rate: 58.33%[21] - 2020: Excess Return: 7.50%, IR: 1.2650, Monthly Win Rate: 58.33%[21] - 2021: Excess Return: 20.48%, IR: 2.5886, Monthly Win Rate: 75.00%[21] - 2022: Excess Return: 4.01%, IR: 0.5426, Monthly Win Rate: 50.00%[21] - 2023: Excess Return: 14.12%, IR: 2.9028, Monthly Win Rate: 83.33%[21] - 2024: Excess Return: -20.37%, IR: -1.5954, Monthly Win Rate: 33.33%[21] - 2025 (up to May 30): Excess Return: 5.62%, IR: 0.7109, Monthly Win Rate: 60.00%[21] Annual Performance of Value-Growth Rotation Model - 2013: Excess Return: 10.61%, IR: 1.1641, Monthly Win Rate: 58.33%[25] - 2014: Excess Return: 27.37%, IR: 3.2529, Monthly Win Rate: 66.67%[25] - 2015: Excess Return: 16.46%, IR: 1.2072, Monthly Win Rate: 66.67%[25] - 2016: Excess Return: 9.96%, IR: 1.2172, Monthly Win Rate: 83.33%[25] - 2017: Excess Return: 14.23%, IR: 2.1003, Monthly Win Rate: 66.67%[25] - 2018: Excess Return: 18.34%, IR: 2.5083, Monthly Win Rate: 91.67%[25] - 2019: Excess Return: 17.04%, IR: 2.8518, Monthly Win Rate: 75.00%[25] - 2020: Excess Return: 37.05%, IR: 3.9631, Monthly Win Rate: 66.67%[25] - 2021: Excess Return: 47.65%, IR: 3.9594, Monthly Win Rate: 83.33%[25] - 2022: Excess Return: 19.46%, IR: 1.6708, Monthly Win Rate: 83.33%[25] - 2023: Excess Return: 10.82%, IR: 1.7148, Monthly Win Rate: 66.67%[25] - 2024: Excess Return: 1.32%, IR: 0.1561, Monthly Win Rate: 41.67%[25] - 2025 (up to May 30): Excess Return: 1.27%, IR: 0.1259, Monthly Win Rate: 60.00%[25]

- The report systematically reviews 80 new quantitative finance-related research papers in May 2025, covering areas such as equity research, fixed income, fund studies, asset allocation, machine learning applications, and ESG-related studies [1][2][3] - Equity research includes studies on fundamental factors, price-volume and alternative factors, factor research, active quantitative strategies, and other categories, exploring investor behavior biases, asset pricing models, market structure distortions, prediction model innovations, and corporate resilience mechanisms [2][10] - Fixed income research focuses on high-frequency inflation forecasting, sovereign risk premium decomposition, and stochastic interest rate model innovations, with findings such as weekly online inflation rates predicting yield curve slope factors and semi-Markov-modulated Hull-White/CIR models achieving semi-analytical pricing for zero-coupon bonds [22][23] - Fund studies investigate fund selection factors, fund style evaluation, and behavioral biases, revealing strategies like liquidity picking driving excess returns and public pension funds underperforming benchmarks due to alternative investment errors post-2008 [28][30] - Asset allocation research explores multi-asset portfolio management paradigm shifts, systematic currency management, and volatility connectedness constraints, demonstrating dynamic adaptation mechanisms and enhanced performance during crises [32][33][35] - Machine learning applications in finance include innovations in volatility forecasting, credit risk prediction using GraphSAGE models, and long-memory stochastic interval models, significantly improving prediction accuracy and economic value [36][38][40] - ESG-related studies analyze green innovation drivers, ESG evaluation distortions, and corporate environmental response strategies, highlighting mechanisms like family business constraints on green innovation and AI-driven manufacturing green transformation [42][43][45]

1. Report Industry Investment Rating The provided content does not mention the industry investment rating. 2. Core Viewpoints of the Report - The convertible bond system of the Beijing Stock Exchange (BSE) has been gradually improved under the promotion of relevant policies [3][14]. - BSE's private - placement convertible bonds have characteristics such as a relatively high initial conversion price, strict redemption clauses, and small changes in conditional put - option clauses [3][14]. - Compared with the Shanghai Stock Exchange's public - offering convertible bonds, BSE's private - placement convertible bonds do not provide issuance ratings, and some do not set conversion price revision clauses [3][17]. - BSE's convertible bonds have lower profit thresholds for issuance and no price limits for trading, with more flexible trading rules [4][20]. - The launch of BSE's public - offering convertible bonds is imminent, which will bring benefits to listed companies, investors, the government, and the convertible bond market [7][27]. 3. Summary According to the Directory 3.1 North Beijing Stock Exchange Convertible Bond System Gradually Improves - **Relevant Policies Boost the Development of the BSE Convertible Bond System**: Since 2022, a series of policies have been introduced to support the development of the BSE convertible bond system, including the introduction of public - offering convertible bonds and support for private - placement convertible bonds [14]. - **Characteristics of BSE Private - Placement Convertible Bonds**: The initial conversion price is generally 120% or more of the previous trading day's stock trading average price. The conditions for triggering the redemption clause are relatively high and flexible, and the conditions for triggering the conditional put - option clause are that the stock price is not less than 50% - 70% of the current conversion price [3][14]. - **Differences between BSE and the Shanghai Stock Exchange**: BSE's private - placement convertible bonds do not provide issuance ratings, and some do not set conversion price revision clauses. The initial conversion price setting requirements are higher, and the conditions for triggering the redemption clause are also higher in some cases [3][17]. 3.2 BSE Convertible Bonds Have Lower Profit Thresholds for Issuance and No Price Limits for Trading - **BSE Convertible Bond Issuance Conditions**: Compared with the Shanghai and Shenzhen Stock Exchanges, BSE has lower profit thresholds and looser conditions for convertible bond issuance. Although the basic issuance conditions, negative lists, and initial conversion price determination rules are the same, the Shanghai and Shenzhen Stock Exchanges have higher requirements for the profitability of issuing companies [20][22]. - **BSE Convertible Bond Trading Conditions**: BSE's convertible bond trading rules have fewer restrictions. There are differences in trading methods, quotation methods, trading transfer times, declaration quantities, price limits, and intraday suspension rules compared with the Shanghai and Shenzhen Stock Exchanges. BSE does not set price limits, making trading more flexible and volatile [4][24]. 3.3 If BSE Public - Offering Convertible Bonds Are Listed, It Will Bring Multiple Benefits - **For Listed Companies**: The launch of BSE public - offering convertible bonds will enrich financing channels, meet the refinancing needs of companies, simplify the financing process, reduce costs, and promote standardized and high - quality operations [7][27]. - **For Investors**: It will increase the supply of the convertible bond market, promote investors' indirect participation in the equity market, and provide more acceptable investment options [7][30]. - **For the Government**: It is conducive to supporting the development of small and medium - sized enterprises, improving the multi - level capital market system, and promoting economic transformation and upgrading [7][31]. - **For the Convertible Bond Market**: It will help expand the market scale, enrich market varieties, and promote the coordinated development of the market, strengthening the connection between the BSE and other capital market sectors [7][32].

Group 1: Quantitative Finance Research Overview - A total of 80 new quantitative finance-related research papers were added this month, with the following distribution: 31 on equity research, 4 on fund research, 8 on bond research, 9 on asset allocation, 3 on machine learning applications in finance, and 22 on ESG-related research[1] - Equity research covers various topics including investor behavior biases, asset pricing models, and market structure distortions, impacting capital markets[2] - Bond research focuses on interest rate bonds, credit bonds, and other bond markets, analyzing high-frequency inflation forecasting and pricing distortion mechanisms[2] Group 2: Specific Findings in Research - High-frequency online inflation rates predict yield curve slope factors with a contribution rate of 61%[22] - The sovereign risk premium in the Eurozone is primarily driven by credit risk premiums, with Italy accounting for 78% of this effect[22] - Climate disasters lead to a temporary premium for green bonds over brown bonds, which diminishes within five months due to behavioral overreaction[24] Group 3: Machine Learning and Risk Management - Machine learning models significantly improve the prediction of implied volatility, showing economic value superior to traditional models[38] - The GraphSAGE model enhances credit risk prediction accuracy by 19% through integrating stock returns, risk spillovers, and trading networks[38] - Long Memory Stochastic Interval Models (LMSR) capture persistent characteristics in volatility, reducing out-of-sample prediction loss by 38%[38]