Investment Rating - The report maintains a "Recommended" rating for the coal mining industry, indicating a positive outlook for the sector's fundamentals and expectations for the industry index to outperform the benchmark index [3][11]. Core Insights - The "anti-involution" policy is expected to stabilize thermal coal prices, while coking coal is anticipated to contribute to elastic growth due to recent price adjustments and market dynamics [2][6]. - The coal supply-demand situation has been generally relaxed this year, with prices declining and some coal mines exceeding their announced production capacities, prompting regulatory actions to ensure orderly supply [1][2]. - The recent price increases in the coking market, following a series of price hikes, indicate a recovery in market sentiment and potential for further price rebounds in the future [6][7]. Summary by Sections Thermal Coal - The price of thermal coal has been under pressure, with the Qinhuangdao Shanxi Q5500 mixed coal price dropping to 610 RMB/ton in the first half of 2025, leading to some coal mines operating at a loss [2]. - The "anti-involution" policy aims to regulate production and stabilize prices, with expectations that the second quarter of 2025 may represent a bottom for the coal industry [2][6]. Coking Coal - Coking coal prices have seen significant declines, with prices dropping from 1950 RMB/ton in October 2024 to 1250 RMB/ton by June 2025, marking an eight-year low [6]. - Recent price increases in the coking market, including a 50 RMB/ton rise following the first round of price hikes, suggest a recovery in market conditions and potential for further growth [6][7]. Key Companies to Watch - For thermal coal, recommended companies include China Shenhua, Shaanxi Coal and Chemical Industry, China Coal Energy, Yanzhou Coal Mining, Xinji Energy, and Jinkong Coal Industry [6]. - For coking coal, recommended companies include Shanxi Coking Coal, Lu'an Environmental Energy, Pingdingshan Coal, and Huaibei Mining [6].

Investment Rating - The report maintains a "Recommended" rating for the AI sector, indicating a positive outlook for the industry based on current developments and market conditions [2][32]. Core Insights - The AI industry is experiencing significant support from both central and local government policies, which aim to enhance the integration of AI technologies across various sectors such as manufacturing, services, healthcare, and education [8][9]. - ByteDance has launched the "Seed Diffusion Preview," an experimental language model that significantly improves code generation speed and accuracy, achieving a performance increase of 5.4 times compared to traditional models [13][14]. - Major tech companies like Microsoft and Meta have reported strong financial results, driven by their AI and cloud computing segments, with Microsoft achieving a quarterly revenue of $764.4 billion and Meta's ad revenue growing by 21% [18][21]. Summary by Sections 1. Artificial Intelligence - Central and local governments have introduced policies to support AI development, including the "Artificial Intelligence+" action plan, which emphasizes leveraging China's comprehensive industrial system and large market scale [8]. - Shanghai has implemented measures to expand AI applications, including the issuance of 1 billion yuan in AI vouchers to support various AI-related initiatives [9][10]. - ByteDance's "Seed Diffusion Preview" model focuses on code generation, achieving a speed of 2146 tokens per second, which is a significant advancement in the field [13][14]. 2. Market Performance Review - The computer sector saw a slight decline of 0.20% in the last week of July 2025, with notable stock performances from companies like Chuangzhong Technology and Zhuoyi Information, which increased by over 20% [26]. - Microsoft and Meta's financial results highlight the robust growth in their AI and cloud services, with Microsoft reporting a 34% increase in Azure revenue and Meta's ad revenue growing significantly [18][21].

Investment Rating - The report maintains a "Recommendation" rating for the real estate industry [1] Core Insights - The land premium rate in 300 cities increased in July compared to June, indicating a potential recovery in the real estate market [1] - The report highlights that the total demand for new and second-hand homes is stabilizing, driven by the narrowing gap between net rental yields and mortgage rates [5] - It emphasizes the importance of supply reduction expectations and the optimization of supply quality in improving the new housing market environment compared to the second-hand market [5] Summary by Sections New Housing Market - The year-on-year decline in new housing contract signing area has expanded, with a 19% decrease in sample cities compared to June [3] - The average contract signing area in first-tier cities saw a 22% year-on-year decline, while second-tier cities experienced a 13% decline [3][9] Second-Hand Housing Market - The year-on-year decline in second-hand housing contract signing area also expanded, with a 7% decrease in sample cities [3] - First-tier cities reported a 9% year-on-year decline in second-hand housing, marking a shift to negative growth [3][13] Land Transactions - From January to July 2025, the cumulative land transaction area in 300 cities saw a year-on-year decline of 6%, while the average transaction price increased by 32% [21] - The land premium rate increased by 2.0 percentage points compared to the previous month, indicating a potential recovery in land sales [27] Market Liquidity and Pricing Trends - The liquidity outlook indicates a tightening trend as of August 2025, with a reduction in the proportion of listings with price increases [5][44] - The average number of viewings for second-hand homes in 12 sample cities decreased by 8.7% compared to June [41] Future Outlook - The report suggests that the real estate sector is entering an investment zone, with the price-to-book (PB) ratio around 1.0, reflecting concerns about the impact of current sales on business models [5] - It identifies three main lines of risk premium recovery for national and regional real estate companies, focusing on balance sheet performance, credit premiums, and turnaround situations [5]

Quantitative Models and Construction Methods 1. Model Name: Credit Impulse Timing Strategy - **Model Construction Idea**: The model uses credit impulse as a timing indicator for A-shares, where the direction of credit impulse determines the market position (full position when upward, empty position when downward) [6][13][14] - **Model Construction Process**: - Calculate the year-on-year growth rate of long-term corporate loans (TTM) as the credit impulse indicator - Use the direction of the credit impulse to determine market positions: full position when the indicator is upward, empty position when downward - Formula: $ \text{Credit Impulse} = \frac{\text{Long-term Corporate Loans (TTM)} - \text{Long-term Corporate Loans (TTM, previous year)}}{\text{Long-term Corporate Loans (TTM, previous year)}} $ - **Model Evaluation**: The model has shown high effectiveness in avoiding major downtrends in the market [6][13][14] 2. Model Name: Beta Dispersion Timing Strategy - **Model Construction Idea**: The model uses beta dispersion as an indicator to measure local market sentiment overheating, with significant monthly timing effectiveness [6][17] - **Model Construction Process**: - Calculate the monthly beta dispersion of the market - Use the beta dispersion to determine market positions: higher beta dispersion indicates higher risk - Formula: $ \text{Beta Dispersion} = \frac{\sum_{i=1}^{N} (\beta_i - \bar{\beta})^2}{N} $ where $\beta_i$ is the beta of stock i, $\bar{\beta}$ is the average beta, and N is the number of stocks - **Model Evaluation**: The model has shown significant monthly timing effectiveness since 2013 [6][17] 3. Model Name: Trading Volume Timing Strategy - **Model Construction Idea**: The model uses trading volume as an indicator for market timing, with significant daily timing effectiveness [6][17] - **Model Construction Process**: - Calculate the daily trading volume and its 60-day moving average - Use the trading volume to determine market positions: higher trading volume indicates stronger market support - Formula: $ \text{Trading Volume Indicator} = \frac{\text{Daily Trading Volume}}{\text{60-day Moving Average of Trading Volume}} $ - **Model Evaluation**: The model has shown significant daily timing effectiveness since 2013 [6][17] 4. Composite Model: Credit Impulse, Beta Dispersion, Trading Volume - **Model Construction Idea**: The composite model combines credit impulse, beta dispersion, and trading volume indicators for market timing [6][18] - **Model Construction Process**: - Use equal weighting to combine the three indicators - Adjust positions based on the combined signal: average 2-week signal change frequency - Formula: $ \text{Composite Indicator} = \frac{\text{Credit Impulse Indicator} + \text{Beta Dispersion Indicator} + \text{Trading Volume Indicator}}{3} $ - **Model Evaluation**: The composite model has shown a high annual turnover rate and significant annualized returns since 2013 [6][18] Model Backtesting Results 1. Credit Impulse Timing Strategy - **Annualized Return**: 10.83% [6][13][14] - **Avoided Major Downtrends**: 2015 H2, 2018, 2022-2024 H1 [6][13][14] 2. Beta Dispersion Timing Strategy - **Annualized Return**: 13.12% [6][17] - **Monthly Timing Effectiveness**: Significant since 2013 [6][17] 3. Trading Volume Timing Strategy - **Annualized Return**: 14.33% [6][17] - **Daily Timing Effectiveness**: Significant since 2013 [6][17] 4. Composite Model: Credit Impulse, Beta Dispersion, Trading Volume - **Annualized Return**: 19.98% [6][18] - **Annual Turnover Rate**: 24 times [6][18] Quantitative Factors and Construction Methods 1. Factor Name: Manufacturing PMI Timing Strategy - **Factor Construction Idea**: The factor uses manufacturing PMI as a timing indicator for A-shares, with positions adjusted based on PMI levels [6][13] - **Factor Construction Process**: - Calculate the rolling 5-year percentile of manufacturing PMI - Adjust positions based on PMI levels: full position when >60%, empty position when <40%, half position when between 40%-60% - Formula: $ \text{PMI Timing Indicator} = \begin{cases} \text{Full Position} & \text{if PMI Percentile} > 60\% \\ \text{Empty Position} & \text{if PMI Percentile} < 40\% \\ \text{Half Position} & \text{if 40\% \leq PMI Percentile \leq 60\%} \end{cases} $ - **Factor Evaluation**: The factor has shown poor timing performance with an annualized return of only 0.41% since 2009 [6][13] Factor Backtesting Results 1. Manufacturing PMI Timing Strategy - **Annualized Return**: 0.41% [6][13] - **Comparison with Benchmark**: Underperformed the Wind All A Index annualized return of 8.49% [6][13] Style Rotation Models and Construction Methods 1. Model Name: Growth-Value Style Rotation Model - **Model Construction Idea**: The model suggests overweighting growth based on economic cycle analysis, valuation differences, and sentiment indicators [35][36] - **Model Construction Process**: - Analyze economic cycle indicators: profitability slope, interest rate cycle, credit cycle - Calculate valuation differences: PE and PB percentiles - Assess sentiment indicators: turnover and volatility differences - Formula: $ \text{Growth-Value Rotation Indicator} = \frac{\text{Profitability Slope Indicator} + \text{Interest Rate Cycle Indicator} + \text{Credit Cycle Indicator} + \text{PE Difference Indicator} + \text{PB Difference Indicator} + \text{Turnover Difference Indicator} + \text{Volatility Difference Indicator}}{7} $ - **Model Evaluation**: The model suggests overweighting growth based on current indicators [35][36] 2. Model Name: Small-Cap Large-Cap Style Rotation Model - **Model Construction Idea**: The model suggests balanced allocation based on economic cycle analysis, valuation differences, and sentiment indicators [35][41] - **Model Construction Process**: - Analyze economic cycle indicators: profitability slope, interest rate cycle, credit cycle - Calculate valuation differences: PE and PB percentiles - Assess sentiment indicators: turnover and volatility differences - Formula: $ \text{Small-Cap Large-Cap Rotation Indicator} = \frac{\text{Profitability Slope Indicator} + \text{Interest Rate Cycle Indicator} + \text{Credit Cycle Indicator} + \text{PE Difference Indicator} + \text{PB Difference Indicator} + \text{Turnover Difference Indicator} + \text{Volatility Difference Indicator}}{7} $ - **Model Evaluation**: The model suggests balanced allocation based on current indicators [35][41] 3. Composite Model: Four-Dimensional Style Rotation Model - **Model Construction Idea**: The model combines growth-value and small-cap large-cap rotation models for allocation [35][44] - **Model Construction Process**: - Combine the signals from growth-value and small-cap large-cap rotation models - Adjust positions based on combined signals - Formula: $ \text{Four-Dimensional Rotation Indicator} = \frac{\text{Growth-Value Rotation Indicator} + \text{Small-Cap Large-Cap Rotation Indicator}}{2} $ - **Model Evaluation**: The model suggests specific allocation proportions based on current indicators [35][44] Style Rotation Model Backtesting Results 1. Growth-Value Style Rotation Model - **Annualized Return**: 11.65% [35][37] - **Comparison with Benchmark**: Outperformed the benchmark annualized return of 6.91% [35][37] 2. Small-Cap Large-Cap Style Rotation Model - **Annualized Return**: 12.32% [35][42] - **Comparison with Benchmark**: Outperformed the benchmark annualized return of 7.11% [35][42] 3. Composite Model: Four-Dimensional Style Rotation Model - **Annualized Return**: 13.22% [35][44] - **Comparison with Benchmark**: Outperformed the benchmark annualized return of 7.50% [35][44]

Market Outlook - The market is expected to experience a volatile pattern in early August, followed by a return to an upward trend in late August, potentially reaching new highs[2] - Concerns regarding the US-China tariff conflict may persist until around August 12, after which risk appetite is likely to recover[3] - The overall free cash flow of listed companies is anticipated to improve, reinforcing the logic for re-evaluating A-shares[3] Economic Indicators - The GDP growth rate for the first half of the year is reported at 5.3%, indicating a stable economic environment[17] - The second quarter earnings growth for listed companies is expected to remain between 0% and 5%[16] - The market has successfully surpassed key resistance levels, with the Shanghai Composite Index above 3450 and the WIND All A Index above 5400 points[18] Investment Strategy - A "barbell" investment strategy is recommended, focusing on high ROE and free cash flow companies on one side, and sectors like AI and defense on the other[19] - Key sectors to watch include non-bank financials, pharmaceuticals, electric power equipment, and machinery[21] Fund Flows - Incremental capital is expected to continue flowing into the market, driven by financing, private equity, and industry ETFs[7] - The net inflow of funds is likely to persist, supported by the positive feedback loop from the market's performance[25] Industry Focus - Attention should be given to sectors with high earnings growth or marginal improvement, particularly in TMT, manufacturing, and essential consumer goods[8] - The focus on "de-involution" competition is expected to drive capacity clearing in various industries, enhancing profitability[21]

Group 1: Planning and Strategy - The "15th Five-Year Plan" is crucial for achieving socialist modernization and will focus on enhancing core competitiveness and functionality of state-owned enterprises (SOEs) [1] - The "14th Five-Year Plan" has been successfully implemented, with major indicators such as economic growth and R&D expenditure meeting expectations, and 8 indicators exceeding expectations [2] - The "15th Five-Year Plan" will emphasize the development of new productive forces and the optimization of strategic emerging industries [2] Group 2: Key Industries and Focus Areas - The focus will be on strategic emerging industries, including marine economy, artificial intelligence, new energy and green environmental protection, next-generation information communication, and biomedicine [34] - The marine economy is highlighted as a significant development direction, with policies aimed at enhancing marine technology and optimizing marine economic layout [35] - Artificial intelligence is recognized as a new economic growth engine, with ongoing support for its integration into various sectors [38] Group 3: Implementation and Risks - SOEs are encouraged to enhance five values: value addition, functional value, economic value added, revenue from strategic emerging industries, and brand value [30] - The plan includes a focus on three concentrations of state capital: critical industries related to national security, public services, and strategic emerging industries [30] - Risks include potential delays in policy implementation and changes in the macroeconomic environment [2]

Investment Rating - The report maintains a recommendation for the transportation industry, suggesting a focus on the potential for price increases in the express delivery sector and the valuation recovery in the logistics sector [3]. Core Insights - The express delivery industry is expected to see a price increase in South China, which may lead to a recovery in industry valuations due to reduced price competition driven by "anti-involution" policies [7][23]. - The shipping sector is currently experiencing weak overall market conditions, with a focus on OPEC+ production plans and the potential for price recovery in the second half of the year [16]. - Infrastructure assets in Hong Kong are seen as having room for valuation improvement, particularly in the context of a declining interest rate environment [19]. - The aviation sector is witnessing a recovery in passenger traffic, but domestic ticket prices are experiencing a significant year-on-year decline [25]. Summary by Sections Shipping - The shipping market is currently weak, with freight rates for major routes declining. The SCFI index for the East America route dropped by 7.5% to $3,126 per FEU [11]. - OPEC+ is expected to approve an increase in production by 548,000 barrels per day in September, which may influence shipping rates positively in the latter half of the year [14][16]. - The demand for dry bulk shipping is fluctuating, with iron ore and grain transport demand decreasing, while coal imports remain strong [16]. Infrastructure - As of June 2025, the national port cargo throughput reached 1.56 billion tons, a year-on-year increase of 4.8%, while container throughput grew by 4.7% [50]. - The report highlights the stable performance of leading highway assets, suggesting a dividend yield returning to around 4% [19]. - The CR450 high-speed train is expected to enhance operational capacity significantly once it enters commercial service [18]. Express Delivery - The express delivery sector is projected to maintain a growth rate of over 20% in 2024, with a 19.3% increase in business volume in the first half of 2025 [20][23]. - The industry is experiencing a shift towards price stabilization due to "anti-involution" measures, with potential price increases expected in August [23]. - Major players like ZTO Express and YTO Express are recommended for investment due to their market positioning and growth potential [23]. Aviation - Passenger traffic in the civil aviation sector has shown a week-on-week increase of 3.1%, but domestic ticket prices have seen a year-on-year decline of 9.5% [24][25]. - The report emphasizes the importance of "anti-involution" policies in stabilizing the aviation market and improving valuations [25]. - Key airline stocks recommended include Air China and Southern Airlines, with a focus on their recovery potential [25]. Logistics - The logistics sector is seeing a slight decrease in air freight prices, with the TAC Shanghai outbound air freight price index down by 3.8% year-on-year [26]. - China National Freight is highlighted for its potential non-operating income from asset sales, making it a recommended stock [26].

Quantitative Models and Construction Methods Style Factors 1. **Factor Name**: Beta Factor - **Construction Idea**: Captures the market sensitivity of stocks - **Construction Process**: - Calculate the daily returns of individual stocks and the market index (CSI All Share Index) over the past 252 trading days - Perform an exponentially weighted regression with a half-life of 63 trading days - The regression coefficient is taken as the Beta factor - **Evaluation**: High Beta stocks outperformed low Beta stocks in the recent week, indicating a preference for market-sensitive stocks[15][16] 2. **Factor Name**: Leverage Factor - **Construction Idea**: Measures the financial leverage of companies - **Construction Process**: - Calculate three sub-factors: Market Leverage (MLEV), Debt to Assets (DTOA), and Book Leverage (BLEV) - MLEV = Non-current liabilities / Total market value - DTOA = Total liabilities / Total assets - BLEV = Non-current liabilities / Shareholders' equity - Combine the three sub-factors equally to form the Leverage factor - **Evaluation**: Low leverage companies outperformed high leverage companies, indicating a market preference for financially stable companies[15][16] 3. **Factor Name**: Growth Factor - **Construction Idea**: Measures the growth potential of companies - **Construction Process**: - Calculate two sub-factors: Sales Growth (SGRO) and Earnings Growth (EGRO) - SGRO = Regression slope of past five years' annual sales per share divided by the average sales per share - EGRO = Regression slope of past five years' annual earnings per share divided by the average earnings per share - Combine the two sub-factors equally to form the Growth factor - **Evaluation**: The Growth factor showed a negative return, indicating a decline in market preference for high-growth stocks[15][16] Stock Selection Factors 1. **Factor Name**: Single Quarter ROA - **Construction Idea**: Measures the return on assets for a single quarter - **Construction Process**: - Single Quarter ROA = Net income attributable to parent company / Total assets - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] 2. **Factor Name**: 240-Day Skewness - **Construction Idea**: Measures the skewness of daily returns over the past 240 trading days - **Construction Process**: - Calculate the skewness of daily returns over the past 240 trading days - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] 3. **Factor Name**: Single Quarter ROE - **Construction Idea**: Measures the return on equity for a single quarter - **Construction Process**: - Single Quarter ROE = Net income attributable to parent company / Shareholders' equity - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] Factor Backtesting Results 1. **Beta Factor**: Weekly long-short return: 1.86%, Monthly long-short return: 1.64%[17] 2. **Leverage Factor**: Weekly long-short return: -3.07%, Monthly long-short return: -1.58%[17] 3. **Growth Factor**: Weekly long-short return: -1.73%, Monthly long-short return: -5.13%[17] Stock Selection Factor Backtesting Results 1. **Single Quarter ROA**: Weekly excess return: 0.98%, Monthly excess return: 2.61%, Annual excess return: 9.49%, Ten-year annualized return: 3.69%[22] 2. **240-Day Skewness**: Weekly excess return: 0.75%, Monthly excess return: 2.48%, Annual excess return: 6.40%, Ten-year annualized return: 2.85%[22] 3. **Single Quarter ROE**: Weekly excess return: 0.74%, Monthly excess return: 1.55%, Annual excess return: 8.96%, Ten-year annualized return: 3.46%[22]

Group 1: Q3 Refinancing Meeting Insights - The Q3 refinancing meeting maintained the long-term bond issuance pace while moderately increasing short-term bond issuance and long-term bond repurchases[7] - The Treasury Department announced a doubling of the repurchase frequency for 10-20 year and 20-30 year bonds, increasing the quarterly repurchase limit from $8 billion to $16 billion[10] - The estimated financing needs for the next three years show little change, with a total decrease of $14 billion compared to April estimates[18] Group 2: Supply Shock and Interest Rate Outlook - The risk of a supply shock in U.S. Treasury bonds is considered low for the remainder of 2023, with upward pressure on bond yields significantly reduced[20] - Short-term interest rate pressures are manageable, with the 3-month U.S. Treasury yield rising approximately 30 basis points from March to October 2023[20] - Long-term bond issuance increases have pushed long-term bond yields and term premiums higher, with yields rising over 130 basis points from June to October 2023[23] Group 3: Economic Data and Rate Expectations - The Federal Reserve's decisions will increasingly depend on economic data, with potential scenarios for CPI and employment data influencing interest rate expectations[32] - The Jackson Hole meeting in August is highlighted as a critical time for potential interest rate guidance, with expectations of a 50 basis point cut if inflation remains within the 2.8-3.0% range[32]

Investment Rating - The report maintains a "Strong Buy" rating for Hisense Home Appliances [3] Core Views - The company is currently facing operational pressure but is expected to see a turnaround in its performance. The revenue for H1 2025 was 49.3 billion yuan, a year-on-year increase of 1%, while the net profit attributable to shareholders was 2.08 billion yuan, up 3% year-on-year. However, Q2 2025 saw a decline in revenue by 3% and a net profit decrease of 8% [1][2] Financial Data and Valuation - Projected total revenue for 2023 is 85.6 billion yuan, with a year-on-year growth of 15%. This is expected to grow to 99.6 billion yuan by 2025, with a growth rate of 7% [2][14] - The net profit attributable to shareholders is projected to reach 3.68 billion yuan in 2025, reflecting a 10% increase from the previous year [2][14] - Earnings per share (EPS) is expected to be 2.66 yuan in 2025, with a price-to-earnings (PE) ratio of 10.2 [2][14] - The company has a return on equity (ROE) of 21.3% and a debt-to-asset ratio of 73.9% [3] Product Performance - In Q2 2025, the air conditioning segment saw a year-on-year increase in domestic and foreign sales of 6% and 17%, respectively. However, both segments experienced negative growth in Q2 due to industry price wars and high base effects from the previous year [6] - The refrigerator segment reported a 4% increase in domestic sales and a 2% increase in foreign sales, with improved profitability in foreign sales due to enhanced brand strength [6] - The central air conditioning segment experienced a revenue decline of 6% in H1 2025, attributed to a sluggish real estate market, but maintains strong brand power in the renovation market [6] Investment Outlook - The report suggests that the domestic consumption support policies will positively impact the company's performance, with a strong growth outlook for 2025-2027. The projected net profits for these years are 3.7 billion yuan, 4.2 billion yuan, and 4.9 billion yuan, respectively, with corresponding growth rates of 10%, 15%, and 15% [6][2]