Quantitative Models and Construction Methods Model 1: Convertible Bond Valuation Model - **Model Name**: Convertible Bond Valuation Model - **Model Construction Idea**: The model aims to compare the valuation of convertible bonds with their underlying stocks using a time-series comparable valuation metric called "100 Yuan Conversion Premium Rate" and the median of "Adjusted YTM - Credit Bond YTM" to measure the relative allocation value between debt-biased convertible bonds and credit bonds[4][5][15] - **Model Construction Process**: - **100 Yuan Conversion Premium Rate**: Fit the relationship curve between the conversion premium rate and conversion value in the cross-sectional space at each time point, and substitute the conversion value = 100 into the fitting formula to obtain the "100 Yuan Conversion Premium Rate" - Formula: $$ y_{i}=\alpha_{0}+\,\alpha_{1}\cdot\,{\frac{1}{x_{i}}}+\epsilon_{i} $$ where \( y_{i} \) is the conversion premium rate of the i-th convertible bond, and \( x_{i} \) is the conversion value of the i-th convertible bond[43] - **Adjusted YTM - Credit Bond YTM**: Adjust the YTM of debt-biased convertible bonds by stripping out the impact of conversion terms - Formula: $$ \text{Adjusted YTM} = \text{Convertible Bond YTM} \times (1 - \text{Conversion Probability}) + \text{Expected Conversion Annualized Yield} \times \text{Conversion Probability} $$ The conversion probability is calculated using the BS model, substituting the closing price of the underlying stock, option exercise price, stock volatility, remaining term, and discount rate to calculate the conversion probability \( N(d2) \)[44] - **Model Evaluation**: The model provides a systematic approach to evaluate the relative allocation value of convertible bonds compared to their underlying stocks and credit bonds[15] Model 2: Convertible Bond Comprehensive Valuation Factor - **Model Name**: Convertible Bond Comprehensive Valuation Factor - **Model Construction Idea**: The model combines the deviation of the conversion premium rate and the theoretical value deviation (Monte Carlo model) to construct a comprehensive valuation factor for convertible bonds[6][19] - **Model Construction Process**: - **Conversion Premium Rate Deviation**: - Formula: $$ \text{Conversion Premium Rate Deviation} = \text{Conversion Premium Rate} - \text{Fitted Conversion Premium Rate} $$ - **Theoretical Value Deviation (Monte Carlo Model)**: - Formula: $$ \text{Theoretical Value Deviation} = \frac{\text{Convertible Bond Closing Price}}{\text{Theoretical Value}} - 1 $$ The Monte Carlo model fully considers the conversion, redemption, downward revision, and repurchase terms of convertible bonds, simulating 10,000 paths at each time point and using the same credit term interest rate as the discount rate to calculate the theoretical value of the convertible bond[20] - **Comprehensive Valuation Factor**: - Formula: $$ \text{Convertible Bond Comprehensive Valuation Factor} = \text{Rank}(\text{Conversion Premium Rate Deviation}) + \text{Rank}(\text{Theoretical Value Deviation (Monte Carlo Model)}) $$ - **Model Evaluation**: The comprehensive valuation factor performs well in the overall, balanced, and debt-biased convertible bonds, while the theoretical value deviation (Monte Carlo model) performs better in equity-biased convertible bonds[19][20] Model 3: Convertible Bond Style Rotation Model - **Model Name**: Convertible Bond Style Rotation Model - **Model Construction Idea**: The model uses convertible bond momentum and volatility deviation as market sentiment capture indicators to construct a convertible bond style rotation portfolio, with bi-weekly rebalancing[7][26] - **Model Construction Process**: - **Market Sentiment Capture Indicators**: - Formula: $$ \text{Convertible Bond Style Market Sentiment Capture Indicator} = \text{Rank}(\text{Convertible Bond 20-Day Momentum}) + \text{Rank}(\text{Volatility Deviation}) $$ - **Style Rotation Position Calculation**: - Example Calculation: | | Convertible Bond Equity-Biased Low Valuation | Convertible Bond Balanced Low Valuation | Convertible Bond Debt-Biased Low Valuation | | --- | --- | --- | --- | | Equal Weight Index | 1 | 2 | 3 | | Volatility Deviation Ranking | 2 | 1 | 3 | | Market Sentiment Capture Indicator | 3 | 3 | 6 | | Style Rotation Position | 50% | 50% | 0% | - **Model Evaluation**: The style rotation model effectively captures market sentiment and allocates positions accordingly, showing superior performance compared to the equal-weight index[26][27][28] Model Backtesting Results Convertible Bond Valuation Model - **100 Yuan Conversion Premium Rate**: Rolling three-year percentile at 98.70%, rolling five-year percentile at 94.90%[4][15] - **Adjusted YTM - Credit Bond YTM**: Current median at -2.36%[5][15] Convertible Bond Comprehensive Valuation Factor - **Equity-Biased Convertible Bond Low Valuation Index**: - Annualized Return: 26.10% - Annualized Volatility: 20.55% - Maximum Drawdown: -22.94% - IR: 1.27 - Calmar Ratio: 1.14 - Monthly Win Rate: 62.22%[23] - **Balanced Convertible Bond Low Valuation Index**: - Annualized Return: 14.80% - Annualized Volatility: 11.82% - Maximum Drawdown: -15.95% - IR: 1.25 - Calmar Ratio: 0.93 - Monthly Win Rate: 62.22%[23] - **Debt-Biased Convertible Bond Low Valuation Index**: - Annualized Return: 13.37% - Annualized Volatility: 9.43% - Maximum Drawdown: -17.78% - IR: 1.42 - Calmar Ratio: 0.75 - Monthly Win Rate: 57.78%[23] Convertible Bond Style Rotation Model - **Convertible Bond Style Rotation**: - Annualized Return: 25.27% - Annualized Volatility: 16.68% - Maximum Drawdown: -15.89% - IR: 1.51 - Calmar Ratio: 1.59 - Monthly Win Rate: 65.56%[32] - **Convertible Bond Low Valuation Equal Weight Index**: - Annualized Return: 14.71% - Annualized Volatility: 10.97% - Maximum Drawdown: -15.48% - IR: 1.34 - Calmar Ratio: 0.95 - Monthly Win Rate: 61.11%[32] - **Convertible Bond Equal Weight Index**: - Annualized Return: 9.75% - Annualized Volatility: 11.66% - Maximum Drawdown: -20.60% - IR: 0.84 - Calmar Ratio: 0.47 - Monthly Win Rate: 60.00%[32]

Investment Rating - The industry investment rating is "Positive" (maintained) [1] Core Views - The report highlights that polyester filament enterprises are reducing production to support prices, leading to a decline in industry inventory [4][21] - The market for glyphosate and glufosinate is experiencing tight supply, which is expected to continue driving price increases [4][24] Summary by Sections Industry Trends - The chemical industry index outperformed the CSI 300 index by 0.09% this week [16] - The CCPI (China Chemical Product Price Index) reported 4034 points, down 0.49% from last week [19] Key Industry Insights - Polyester filament prices increased by 1.50% to 6,750 CNY/ton, with a price spread expansion of 11.95% [4][21] - Glyphosate prices rose to an average of 26,699 CNY/ton, up 1.14% from the previous week [4][24] - Glufosinate prices remained stable at around 44,500 CNY/ton, with a stable supply situation [4][26] Recommended and Beneficiary Stocks - Recommended stocks include leading chemical companies such as Wanhua Chemical, Hualu Hengsheng, and Hengli Petrochemical [6][29] - Beneficiary stocks include Jiangshan Co., Hebang Biotechnology, and Xin'an Chemical [6][28] Product Tracking - Viscose staple fiber prices increased by 0.78% to 12,950 CNY/ton [31] - The price of ammonium phosphate remained stable, while urea prices decreased by 1.85% to 1,747 CNY/ton [41][42]

Investment Rating - The investment rating for Jiangsu Jinzu (600901.SH) is "Buy" (maintained) [1] Core Views - The revenue and profit growth for the first half of 2025 met expectations, with revenue and net profit at 3.006 billion and 1.564 billion yuan respectively, reflecting year-on-year increases of 15% and 9% [4] - The company is considered a high-quality, high-dividend investment target, with a current dividend yield of 4.62% and a dynamic dividend yield of 5.15% assuming a constant dividend payout ratio of 53% [4] - The company has a stable performance in terms of asset quality, with a non-performing loan ratio of 0.91% and a slight increase in the non-performing loan generation rate to 0.61% [6] Financial Performance Summary - For the first half of 2025, the annualized weighted average ROE was 12.68%, an increase from 12.60% in the first quarter [4] - The company forecasts net profits of 3.26 billion, 3.62 billion, and 4.03 billion yuan for 2025, 2026, and 2027 respectively, with a consistent year-on-year growth rate of 12% [4] - The company's revenue is projected to grow from 5.977 billion yuan in 2025 to 7.353 billion yuan in 2027, with a compound annual growth rate of approximately 10.5% [8][11] Business Model and Growth Strategy - Jiangsu Jinzu's business model, which includes "vendor leasing + regional direct sales + shareholder collaboration," has matured and is effective, with partnerships established with nearly 6,000 manufacturers and dealers [5] - The company has diversified its industry structure to mitigate cyclical fluctuations, focusing on high-end equipment, clean energy, and transportation sectors, which have shown significant growth [5] Valuation Metrics - The current price-to-book (PB) ratios for 2025, 2026, and 2027 are projected at 1.3, 1.2, and 1.1 respectively, indicating a favorable valuation [4] - The earnings per share (EPS) for the next three years are estimated at 0.6 yuan for 2025, 0.6 yuan for 2026, and 0.7 yuan for 2027 [4]

Investment Rating - The report assigns a positive investment rating to the company, highlighting its growth potential in the automotive maintenance equipment sector. Core Viewpoints - The company is a leading manufacturer of automotive maintenance and repair equipment, focusing on R&D, production, and sales, with a strong growth trajectory in revenue and profit from 2022 to 2024 [1][11]. - The automotive industry is experiencing significant growth, with global production and sales expected to increase, driven by the aging vehicle population, which presents opportunities for the automotive maintenance market [2][3]. - The company has established a robust technological advantage through years of industry experience and a comprehensive R&D system, holding numerous patents and software copyrights [3][14]. Summary by Sections 1. Company Overview - The company specializes in automotive maintenance and repair equipment, with major products including tire changers, wheel balancers, and lifts. It has a strong domestic and international customer base, including well-known automotive manufacturers and service chains [1][11]. 2. Financial Performance - The company's total revenue for 2022, 2023, and 2024 was 642.64 million, 794.26 million, and 1.057 billion yuan, respectively, with net profits of 30.04 million, 80.55 million, and 129.40 million yuan, indicating a consistent upward trend in both revenue and profit [1][62]. - The gross profit margins for the same years were 23.62%, 27.04%, and 28.55%, showing an overall growth trend [1][62]. 3. Industry Insights - The global automotive market is projected to produce 92.5 million vehicles in 2024, with a significant increase in vehicle ownership and aging vehicles, particularly in developed countries [2][3]. - The automotive maintenance market in China is expected to reach 1.3476 trillion yuan by 2025, with a compound annual growth rate of 6.50% from 2020 to 2025 [2]. 4. Technological and Competitive Advantages - The company has developed a strong technological edge, with 226 patents and recognition as a high-tech enterprise. It is also acknowledged as a specialized and innovative small enterprise in various provinces [3][14]. - The company’s products have received multiple certifications and awards, enhancing its brand reputation and market competitiveness [53][56]. 5. Market Position and Growth Potential - The company is positioned as one of the largest manufacturers in the domestic automotive maintenance equipment industry, with a growing market share both domestically and internationally [1][11]. - The expected increase in automotive maintenance demand due to the aging vehicle population presents a significant growth opportunity for the company [2][3].

Quantitative Models and Construction Methods 1. Model Name: Virtual Index (虚拟指数) - **Model Construction Idea**: The Virtual Index is designed as an alternative to the official index, aiming to replicate the weight distribution of the original index while reducing concentration. This ensures that the enhanced strategy based on the Virtual Index can outperform the original index with greater stability[3][45][56] - **Model Construction Process**: - The Virtual Index is constructed by fitting the holdings of index-enhanced funds to approximate the weight distribution of the original index. - Two key metrics are used to evaluate the Virtual Index: - **JS Divergence (Jensen-Shannon Divergence)**: Measures the similarity between the weight distributions of the Virtual Index and the original index. A lower JS divergence indicates higher similarity $$ J S(P||Q)={\frac{1}{2}}K L(P||M)+{\frac{1}{2}}K L(Q||M) $$ $$ M={\frac{P+Q}{2}} $$ $$ K L(P||Q)=\sum_{x\in X}P(x)l n{\frac{P(x)}{Q(x)}} $$ - **HHI (Herfindahl-Hirschman Index)**: Measures the concentration of weights in the Virtual Index. A lower HHI indicates lower concentration $$ H H I=\sum w_{i}^{2} $$ - The Virtual Index is tested across three major indices: CSI 300, CSI 500, and CSI 1000[45][49][50] - **Model Evaluation**: The Virtual Index demonstrates weight distribution similarity to the original index (low JS divergence) and lower industry concentration (low HHI), making it a robust alternative for enhanced strategies[46][50][56] 2. Model Name: Enhanced Strategy Based on Virtual Index - **Model Construction Idea**: This strategy uses the Virtual Index as the baseline for constructing enhanced portfolios, aiming to outperform the original index by leveraging multi-factor models[57][63] - **Model Construction Process**: - Two groups of enhanced portfolios are constructed: - **Reference Group**: Based on the original index's weight distribution - **Test Group**: Based on the Virtual Index's weight distribution - Both groups use the same multi-factor framework and constraints for consistency[57][59] - **Model Evaluation**: The test group (Virtual Index-based) consistently outperforms the reference group (original index-based), particularly for CSI 300 and CSI 500. However, the performance improvement diminishes as the number of index constituents increases (e.g., CSI 1000)[59][61] --- Model Backtesting Results 1. Virtual Index - **JS Divergence**: - CSI 300: 0.0078 - CSI 500: 0.0062 - CSI 1000: 0.0062[46] - **HHI (Industry Concentration)**: - CSI 300: Lower than the original index - CSI 500: Lower than the original index - CSI 1000: Lower than the original index, but with smaller deviations compared to CSI 300 and CSI 500[50][52] 2. Enhanced Strategy Based on Virtual Index - **Cumulative Net Value**: - CSI 300: - Test Group: 4.35 - Reference Group: 3.25[57] - CSI 500: - Test Group: 5.38 - Reference Group: 4.02[59] - CSI 1000: - Test Group: Slightly higher than the Reference Group, with divergence starting in 2024[59][61] --- Quantitative Factors and Construction Methods 1. Factor Name: RankIC and RankICIR Evaluation - **Factor Construction Idea**: Evaluate the predictive power and stability of individual factors within the Virtual Index and original index constituents[62][63] - **Factor Construction Process**: - RankIC and RankICIR are calculated for each factor within the Virtual Index and original index constituents - Factors are tested for their ability to differentiate stock performance and their stability over time[62][64] - **Factor Evaluation**: - Most factors show higher RankIC and RankICIR values within the Virtual Index constituents, indicating better predictive power and stability - Exceptions include factors like "long_momentum2" and "active_trading," which perform better in the original index constituents[62][64] --- Factor Backtesting Results 1. RankIC and RankICIR - **RankIC**: Higher for most factors in the Virtual Index constituents compared to the original index constituents - **RankICIR**: Higher for most factors in the Virtual Index constituents compared to the original index constituents[62][64]

Consumption - The contribution of trade-in programs to retail sales has weakened, with July retail sales growth declining by 1.1 percentage points to 3.7% year-on-year[3] - The personal consumption loan interest subsidy is expected to boost retail sales by approximately 0.2 percentage points, with a historical context showing a 1% subsidy could lead to a greater impact than previous years[4] - The consumer loan consumption rate has remained low, averaging around 2.5% since 2024, indicating a shift towards cash purchases rather than credit expansion[3] Production - Industrial production growth in July was 5.7%, down 1.1 percentage points from the previous value, with a month-on-month increase of only 0.38%[5] - Service sector production also saw a slight decline of 0.2 percentage points to 5.8% year-on-year, with mixed performance across various industries[5] Fixed Investment - Real estate investment has further declined, with July showing a year-on-year drop of 12.0%, and new housing sales showing signs of weakness[6] - Manufacturing investment has decreased by 1.3 percentage points to 6.2%, with significant declines in sectors such as non-ferrous metallurgy and chemical products[6] - Infrastructure investment turned negative for the first time since 2021, with broad infrastructure showing a decline of 1.9% year-on-year in July[6] Economic Outlook - The data from July indicates a further weakening of domestic demand, suggesting increased downward pressure on economic growth in Q4, which may prompt policy adjustments[7] - Risks include potential underperformance of policy measures and unexpected downturns in the U.S. economy[7]

Report Industry Investment Rating - Not provided in the content Core Viewpoints - Despite the decline in economic and financial data in July 2025, a series of policies are expected to take effect, and the economy in the second half of 2025 is expected to remain stable, in the second half of the economic L-shaped curve [7]. - The current deviation between the stock-bond market trend and economic data may follow a similar logic to the first quarter of 2023. Policy signals have led to an upward revision of expectations, resulting in rising stocks and falling bonds [6]. - In the bond market, the target for the 10-year Treasury yield in the second half of 2025 is expected to be 1.9 - 2.2%. If inflation normalizes, the reasonable range of the 10-year Treasury yield may also rise accordingly [7]. - In the equity market, considering the upward revision of economic expectations and the continuous upgrading of the technology industry, the stock market is expected to continue its upward trend in the second half of the year [7]. Summaries by Related Content Economic Data Overview - In July 2025, the added value of industrial enterprises above the designated size increased by 5.7% year-on-year, the service production index increased by 5.8% year-on-year, and the total retail sales of consumer goods was 387.8 billion yuan, a year-on-year increase of 3.7%. From January to July, the national fixed - asset investment (excluding rural households) was 2.88229 trillion yuan, a year-on-year increase of 1.6% [3]. - In July 2025, RMB loans decreased by 5 billion yuan, the first decrease since August 2005 [4]. Market Performance - On August 15, 2025, the Shanghai Composite Index rose 0.83%, and the 10-year Treasury yield rose 1.2 BP, showing a trend of rising stocks and falling bonds [4]. Historical Comparison - In the first quarter of 2023, there was also a deviation between the fundamentals and market trends. The PMI in February - March reached 52.6% and 51.9% respectively, but the Shanghai Composite Index fluctuated and the 10-year Treasury yield declined [5]. Policy Impact - A series of policies since July 2025 have released positive signals, including promoting inflation recovery, boosting domestic investment, subsidizing childbirth, and promoting consumption and credit recovery [6].

Investment Rating - The industry investment rating is "Overweight" [8] Core Viewpoints - The report indicates that social retail sales maintained steady growth, with a year-on-year increase of 3.7% in July, supported by national subsidies [3][4] - Essential categories like grain, oil, and food showed stronger resilience, while discretionary categories such as gold and jewelry, and cosmetics saw improved performance [4] - Online retail channels continued to grow, with a 9.2% year-on-year increase in online retail sales from January to July 2025, while offline retail growth showed signs of marginal slowdown [5] Summary by Sections Social Retail Sales - The total retail sales of consumer goods from January to July 2025 reached 28,423.8 billion yuan, with July sales at 3,878 billion yuan, reflecting a year-on-year growth of 4.8% and 3.7% respectively [3] - Urban and rural retail sales increased by 4.8% and 4.7% year-on-year [3] Price Factors - The overall Consumer Price Index (CPI) remained stable, with food CPI down by 1.6% year-on-year [4] - Retail sales in various categories showed different growth rates, with essential goods like grain and oil up by 8.6% year-on-year, while discretionary items like cosmetics and jewelry saw increases of 4.5% and 8.2% respectively [4] Online vs Offline Channels - Online retail sales reached 86,835 billion yuan from January to July 2025, with physical goods online sales at 70,790 billion yuan, accounting for 24.9% of total retail sales [5] - Offline retail growth rates for supermarkets, convenience stores, and department stores showed a slight decline compared to the previous month [5] Investment Recommendations - The report suggests focusing on high-quality companies in sectors aligned with "emotional consumption," particularly in gold jewelry, offline retail, cosmetics, and medical aesthetics [6] - Specific recommendations include brands like Lao Pu Gold and Chao Hong Ji in gold jewelry, and companies like Mao Ge Ping and Pechoin in cosmetics [6]

Investment Rating - The investment rating for JD Group is "Buy" (maintained) [1] Core Insights - JD Group's Q2 2025 performance exceeded expectations, with revenue of 356.7 billion yuan, a year-on-year increase of 22.4%, surpassing Bloomberg consensus estimates of 335.5 billion yuan [5] - Non-GAAP net profit for Q2 2025 was 7.4 billion yuan, a decline of 49% year-on-year, but also better than the expected 5.35 billion yuan [5] - The company has adjusted its non-GAAP net profit forecasts for 2025-2027 to 27.7 billion, 46 billion, and 52.6 billion yuan respectively, reflecting a year-on-year growth rate of -42%, +66%, and +15% [4] Revenue and Profit Analysis - Revenue from product sales grew by 20.7% year-on-year, with core electronics and home appliances increasing by 23.4% [5] - Service revenue rose by 29.1%, driven by a 21.7% increase in platform and advertising services due to user traffic growth [5] - The retail operating profit margin improved by 0.6 percentage points to 4.5%, while logistics operating profit margin decreased by 1.1 percentage points to 3.8% [5] Business Strategy and Market Position - The company is benefiting from the "trade-in" policy for electronics and home appliances, which has significantly improved core business performance [4] - Continued investment in the food delivery business is expected to enhance user engagement and cross-purchase rates, contributing to long-term growth [6] - JD Group's share buyback program has repurchased approximately 2.8% of its outstanding shares, with a remaining buyback amount of 3.5 billion USD [6] Financial Summary and Valuation Metrics - For 2025, the projected revenue is 1,313.5 billion yuan, with a year-on-year growth of 13.3% [7] - The projected diluted EPS for 2025 is 8.7 yuan, with a corresponding P/E ratio of 12.7 times [7] - The gross margin is expected to remain stable around 15.5% for the coming years [7]

Investment Rating - The investment rating for the company is "Buy" (maintained) [3][9] Core Views - The company achieved a significant year-on-year profit increase of 27% in Q2 2025, driven by the launch of new games and the fine-tuning of existing games, alongside improvements in cloud music and other business segments [3][4] - The forecast for net profit from 2025 to 2027 has been raised, with expected figures of 375 billion, 405 billion, and 464 billion respectively, reflecting a positive outlook for the company's growth trajectory [3][5] Summary by Relevant Sections Financial Performance - In Q2 2025, the company reported revenue of 279 billion (up 9.4% year-on-year, down 3.3% quarter-on-quarter) and a net profit of 86 billion (up 27.3% year-on-year, down 16.5% quarter-on-quarter) [3][4] - The gross margin for Q2 was 64.7%, an increase of 1.8 percentage points year-on-year, while the operating expense ratio decreased to 32.2%, down 3.3 percentage points year-on-year [3] Game and Related Services - Revenue from games and related value-added services in Q2 2025 was 228 billion (up 13.7% year-on-year, down 5.2% quarter-on-quarter), with a gross margin of 70.2% [4] - The company has a strong pipeline of games, including "Infinite" and "Forgotten Sea," with "Infinite" expected to be revealed around the Tokyo Game Show [4] Cloud Music and Other Segments - Cloud music revenue in Q2 was 20 billion (down 3.5% year-on-year, up 5.9% quarter-on-quarter), with a gross margin of 36.1% [4] - The AI-driven business innovation in Youdao led to its first operational profit in Q2, amounting to 28.8 million [4]