- 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]

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The company's Q1 2025 performance showed lower-than-expected revenue and profit, with a significant increase in expense ratios [4][5] - The online marketing services revenue reached 48.7 billion yuan, a year-on-year increase of 14.8%, exceeding Bloomberg's consensus estimate by 1.5% [5] - The transaction services revenue was 46.9 billion yuan, a year-on-year increase of 5.8%, falling short of Bloomberg's consensus estimate by 12.8% [5] - The company is facing challenges in its overseas business due to tariff policy changes affecting its Temu operations in the U.S. [5][6] - Domestic operations are under pressure from increased subsidy efforts, impacting profit margins [6] Financial Summary - For Q1 2025, the company's revenue was 95.7 billion yuan, a year-on-year increase of 10.2%, but below Bloomberg's consensus estimate by 5.6% [4] - Non-GAAP net profit for the quarter was 16.9 billion yuan, a year-on-year decrease of 44.7%, also below consensus estimates by 38.3% [4] - The company expects revenues of 410.2 billion, 439.6 billion, and 509.9 billion yuan for 2025, 2026, and 2027 respectively, with year-on-year growth rates of 4.2%, 7.2%, and 16.0% [7] - Adjusted net profits are projected to be 92.8 billion, 133.3 billion, and 158.4 billion yuan for the same years, with year-on-year changes of -24.2%, +43.6%, and +18.9% [7] - The company maintains a strong cash position, with cash and cash equivalents expected to reach 534.0 billion yuan by 2027 [11]

执业证书号：S0010522030002 电话：13127532070 邮箱：yanzq@hazq.com [Table_Author] 研究助理：洪子彦 [Table_IndNameRptType]2 固定收益 固收周报 债市"每调买机"情绪回归 ——债市情绪面周报（6 月第 1 周） 报告日期： 2025-06-03 [Table_Author] 首席分析师：颜子琦 执业证书号：S0010123060036 电话：15851599909 邮箱：hongziyan@hazq.com 主要观点： ⚫[Table_Summary] 华安观点：6 月债市高胜率+低赔率的组合延续 当前 10Y 国债收益率在 1.65%至 1.70%附近持续震荡超一月，5 月利率 弱、信用强，存单在 1.70%附近震荡，短期债市多空交织。第一，在关税反复 扰动背景下，央行的主要目标由防空转、稳汇率切换至稳增长，双降以及一揽 子货币政策带动广谱利率下行，债牛环境不变；第二，但从短期来看，6 月资 金面易受扰动，存单大额到期+季末流动性冲击+供给高峰，在此背景下央行 对于资金面的话语权已经提升，我们预计一季度的情形大概率不会重演，资金 ...

Group 1: Report Industry Investment Rating - No relevant content provided Group 2: Core Viewpoints of the Report - In May, the credit bond market had an independent performance. By the end of the month, the valuation yields of urban investment bonds with implicit ratings from 1 - 5 years reached historical lows, and credit spreads also hit lows. Only the 5 - year variety still had compression space. At the end of the month, there was a slight bond - market shock, with a 2 - 3bp retracement in credit bond yields and spreads [1]. - Short - duration spreads hit new lows, while term spreads and grade spreads still have room. The yields of 1 - year varieties in May continued to decline, breaking the low in June 2024. There is still room for compression in grade spreads and term spreads [2]. - Currently, the coupon advantage of credit bonds remains, but the valuation fluctuation risk has started to increase. The main reasons for the stronger performance of credit bonds than interest - rate bonds in May were the decline in the central funds rate and the increased demand for credit bond allocation due to deposit transfer. However, overseas uncertainties and institutional behavior changes at the end of the month and quarter have a growing impact on the market [3]. - In the future, short - duration spreads of various implicit ratings have reached historical lows. Without new expectations, the probability of further decline in the short - term is low. The main capital gain space may come from the compression of grade spreads and term spreads. At the same time, the valuation fluctuation risk of credit bonds is accumulating, and medium - and long - term risks cannot be ignored [3][5]. - Strategically, investors are advised to adopt a duration strategy. Consider 3 - 4 - year credit bonds for riding returns, and also consider extending the duration of high - grade credit bonds to 6 - 7 years. The annualized riding return of AAA - grade bonds is about 2.6% [5]. Group 3: Summary by Related Catalogs Credit Bond Market Performance in May - The valuation yields of 1 - 5 - year urban investment bonds with various implicit ratings reached historical lows, and credit spreads also hit lows. Only the 5 - year variety still had compression space. At the end of the month, there was a slight bond - market shock, with a 2 - 3bp retracement in credit bond yields and spreads [1]. - The yields of 1 - year varieties in May continued to decline, breaking the low in June 2024. The 3 - year AA +, AA, and AA(2) implicit ratings had grade spreads of 7bp, 16bp, and 27bp compared to AAA, with 5 - 10bp compression space compared to historical lows. The historical quantiles of term spreads of 3 - year and 5 - year varieties compared to 1 - year varieties of the same rating were still in the 10% - 20% range [2]. Reasons for Market Performance and Future Outlook - The stronger performance of credit bonds than interest - rate bonds in May was due to the decline in the central funds rate and increased credit bond allocation demand from deposit transfer. But overseas uncertainties and institutional behavior changes at the end of the month and quarter had a growing impact. At the end of May, fund redemptions caused significant bond - market fluctuations [3]. - Short - duration spreads have reached historical lows. Without new expectations, the probability of further decline in the short - term is low. The main capital gain space may come from the compression of grade spreads and term spreads. The valuation fluctuation risk of credit bonds is accumulating, and medium - and long - term risks cannot be ignored [3][5]. Investment Strategy - Adopt a duration strategy. Consider 3 - 4 - year credit bonds for more riding returns. Also, consider extending the duration of high - grade credit bonds to 6 - 7 years. Based on the end - of - month yield curve, the annualized riding return of AAA - grade bonds is about 2.6% [5].

Investment Rating - The investment rating for the company is "Buy" (maintained) [2] Core Views - The company's performance in Q1 2025 exceeded expectations, with revenue of 111.3 billion yuan (yoy +47.4%) and Non-GAAP net profit of 10.7 billion yuan (yoy +64.5%) [5][6] - The IoT business continues to show strong growth, driven by major appliances, with revenue of 32.3 billion yuan (yoy +58.7%) [6] - The automotive business is expected to gain momentum with the upcoming launch of the YU7 model, which is anticipated to enhance sales and profitability [6][7] - The smartphone segment shows improvement in gross margin and average selling price (ASP), with ASP reaching 1,211 yuan (yoy +5.8%) [7] Summary by Sections Financial Performance - Q1 2025 revenue was 111.3 billion yuan, exceeding Bloomberg's expectations by 2.1% [5] - Non-GAAP net profit for Q1 2025 was 10.7 billion yuan, surpassing expectations by 17.7% [5] - Revenue breakdown: - Mobile business: 50.6 billion yuan (yoy +8.9%) [5] - IoT business: 32.3 billion yuan (yoy +58.7%) [5] - Internet services: 9.1 billion yuan (yoy +12.8%) [5] - Smart automotive and other innovative businesses: 18.6 billion yuan [5] IoT Business - The IoT segment's revenue growth is primarily driven by major appliances, with a significant increase in sales of air conditioners, refrigerators, and washing machines [6] - The gross margin for IoT reached 25.2%, an increase of 5.3 percentage points year-on-year [6] - A new smart appliance factory is expected to start production in November 2025, aiming for an annual output of 3 million air conditioners by 2026 [6] Automotive Business - Automotive revenue for Q1 2025 was 18.6 billion yuan, with a gross margin of 23.2% [6] - The YU7 model is set to launch in July 2025, featuring advanced technology and expected to drive sales growth [6][7] Smartphone Business - The smartphone segment's gross margin improved to 12.4% in Q1 2025 [7] - The ASP for smartphones reached a record high of 1,211 yuan, with a market share increase in the high-end segment [7] Future Projections - Revenue projections for 2025, 2026, and 2027 are 482.7 billion yuan, 612.7 billion yuan, and 713.5 billion yuan respectively, with year-on-year growth rates of 31.9%, 26.9%, and 16.5% [8] - Adjusted net profit forecasts for the same years are 41.2 billion yuan, 56.9 billion yuan, and 69.9 billion yuan, reflecting growth rates of 51.3%, 38.1%, and 22.9% [8]

Investment Rating - The investment rating for the company is "Buy" (maintained) [2] Core Views - The company's performance in Q1 2025 exceeded expectations, with revenue of 111.3 billion yuan (yoy +47.4%) and Non-GAAP net profit of 10.7 billion yuan (yoy +64.5%) [5][6] - The IoT business continues to show strong growth, driven by major appliances, with revenue of 32.3 billion yuan (yoy +58.7%) [6] - The automotive business is expected to see an increase in sales and profitability with the upcoming launch of the YU7 model [6][7] - The smartphone segment shows improvement in gross margin and average selling price (ASP), with ASP reaching 1,211 yuan (yoy +5.8%) [7] Summary by Sections Q1 2025 Performance - Overall performance: Revenue of 111.3 billion yuan (yoy +47.4%), exceeding BBG expectations by 2.1%; Non-GAAP net profit of 10.7 billion yuan (yoy +64.5%), exceeding BBG expectations by 17.7% [5] - Business breakdown: - Mobile business: Revenue of 50.6 billion yuan (yoy +8.9%), gross margin of 12.4% [5] - IoT business: Revenue of 32.3 billion yuan (yoy +58.7%), gross margin of 25.2% [5] - Internet business: Revenue of 9.1 billion yuan (yoy +12.8%), gross margin of 76.9% [5] - Smart automotive and innovative business: Revenue of 18.6 billion yuan, gross margin of 23.2% [5] IoT Business Growth - Driven by major appliances, IoT revenue reached 32.3 billion yuan (yoy +58.7%), with significant growth in air conditioning, refrigerators, and washing machines [6] - The gross margin for IoT improved to 25.2%, up 5.3 percentage points year-on-year [6] - A new smart appliance factory is expected to start production in November 2025, aiming for an annual output of 3 million air conditioners by 2026 [6] Automotive Business Outlook - Automotive revenue for Q1 2025 was 18.6 billion yuan, with a gross margin of 23.2% [6] - The YU7 model is set to launch in July 2025, featuring advanced technology and expected to drive sales growth [6][7] Smartphone Segment Performance - The smartphone gross margin improved to 12.4%, with ASP reaching a historical high of 1,211 yuan [7] - Market share in the high-end smartphone segment has increased, particularly in the 4,000-5,000 yuan price range [7] Financial Projections - Revenue projections for 2025, 2026, and 2027 are 482.7 billion yuan, 612.7 billion yuan, and 713.5 billion yuan respectively, with year-on-year growth rates of 31.9%, 26.9%, and 16.5% [8] - Adjusted net profit projections for the same years are 41.2 billion yuan, 56.9 billion yuan, and 69.9 billion yuan, with growth rates of 51.3%, 38.1%, and 22.9% [8]

The provided content does not contain any quantitative models or factors, nor does it include any related construction processes, formulas, or backtesting results. The document primarily focuses on company-specific financial performance, industry outlooks, and investment rationales for various stocks. There are no references to quantitative analysis, factor construction, or model testing within the text.