Core Viewpoint - The recent phenomenon of foreign capital inflow into A-shares has been a significant topic of discussion, indicating a growing interest from global investors in the Chinese stock market [2][4]. Group 1: Foreign Capital Inflow Data - From May to the end of July, long-term stable foreign institutional funds accumulated inflows of approximately 67.7 billion HKD, while short-term flexible foreign institutional funds saw inflows of about 16.2 billion HKD [2]. - During the week of August 14-20, the net inflow of foreign capital for allocation reached a new high since 2025, totaling 6.98 billion CNY, with active allocation foreign capital turning to net inflow for the first time since mid-October 2024, amounting to 140 million CNY [2]. - In the first week of September 2025, foreign capital net inflow into the Chinese mainland market was approximately 5.5 billion USD, with stock funds contributing 5.02 billion USD, primarily from passive funds [2]. Group 2: Foreign Investment Preferences - Foreign capital tends to favor industries with global competitive advantages and strong growth potential, such as innovative pharmaceuticals, leading internet companies in Hong Kong, the Nvidia supply chain, and renewable energy [4]. - Since July, foreign capital has shown a significant preference for sectors like technology, healthcare, and materials, particularly focusing on companies within the AI industry due to their clear technological advancements and profit growth expectations [4]. - The preference for core assets with local market characteristics is evident, with foreign capital increasing allocations in sectors like automotive, banking, and electronics in A-shares, while favoring software and services in Hong Kong stocks [5]. Group 3: Structural Characteristics of Foreign Investment - The structural characteristics of foreign capital allocation in A-shares are focused on high-growth technology, high-dividend assets, and high-end manufacturing [4]. - Foreign investors have shown a preference for stocks with strong fundamentals, as indicated by the higher return on equity (ROE) of foreign-held stocks in A-shares (17.2%) compared to the overall market [5]. - The trend of foreign capital favoring stocks with lower AH premium suggests a strategic approach to maximize returns while minimizing risks associated with market fluctuations [5].

Group 1 - The core viewpoint of the article highlights the positive performance of China National Heavy Duty Truck Group (China National Heavy Truck) in the heavy truck market, with a notable increase in sales and a stable financial performance [1] - As of August 2025, the heavy truck market in China sold approximately 84,000 units, reflecting a slight month-on-month decrease of 1% from July, but a significant year-on-year increase of about 35% compared to 62,500 units sold in the same month last year [1] - The company achieved revenue of approximately 50.878 billion yuan in the first half of the year, representing a year-on-year growth of 4.21%, while the net profit attributable to shareholders was about 3.427 billion yuan, also up by 4.03% year-on-year [1] Group 2 - The brokerage Guolian Minsheng Securities suggests that with the industry entering the peak season of September and October, the likelihood of annual heavy truck wholesale sales exceeding 1 million units has increased, indicating a positive outlook for the heavy truck industry in September and Q4 [1] - Despite facing pressure on heavy truck demand and a slowdown in export growth, China National Heavy Truck has managed to deliver stable performance through effective cost management and a consistent dividend policy [1] - The company is expected to benefit as an industry leader from the recovery in heavy truck sales in the second half of the year [1]

Quantitative Models and Construction Methods 1. Model Name: Coal Industry Profit Forecast Model - **Model Construction Idea**: The model estimates monthly revenue and profit growth rates for the coal industry based on changes in price and capacity factors[10][15] - **Model Construction Process**: 1. The pricing mechanism is determined by the last price index of the previous month, which sets the sales price for the next month[10] 2. The model uses year-on-year changes in price factors and capacity factors to estimate revenue and profit growth rates on a monthly basis[10] - **Model Evaluation**: The model provides a systematic approach to track and predict industry profitability trends, but it is sensitive to price fluctuations and external shocks[15] 2. Model Name: Hog Supply-Demand Gap Estimation Model - **Model Construction Idea**: This model predicts the supply-demand gap for hogs six months in advance based on the relationship between sow inventory and hog slaughter rates[16][17] - **Model Construction Process**: 1. The model assumes a stable proportional relationship between quarterly hog slaughter and sow inventory lagged by six months[16] 2. The formula for the slaughter coefficient is: $ \text{Slaughter Coefficient} = \frac{\text{Quarterly Hog Slaughter}}{\text{Sow Inventory (Lagged 6 Months)}} $[16] 3. The potential supply six months later is calculated as: $ \text{Potential Supply (t+6)} = \text{Sow Inventory (t)} \times \text{Slaughter Coefficient (t+6)} $[17] 4. The potential demand six months later is estimated using historical quarterly slaughter data[17] - **Model Evaluation**: The model effectively identifies hog price cycles but relies heavily on the accuracy of historical slaughter coefficients[17] 3. Model Name: Steel Industry Profit Forecast Model - **Model Construction Idea**: The model predicts monthly profit growth and per-ton profitability for the steel industry by integrating steel prices and raw material costs[19] - **Model Construction Process**: 1. The model incorporates comprehensive steel prices and costs of raw materials such as iron ore, coke, pulverized coal, and scrap steel[19] 2. Monthly profit growth rates and per-ton profitability are calculated based on these inputs[19] - **Model Evaluation**: The model provides a detailed view of profitability trends but may not fully capture external demand-side factors[23] 4. Model Name: Glass and Cement Industry Profitability Tracking Model - **Model Construction Idea**: This model tracks profitability changes in the glass and cement industries using price and cost indicators, and generates allocation signals based on these changes[25] - **Model Construction Process**: 1. The model monitors price and cost indicators to assess profitability trends[25] 2. It incorporates manufacturing PMI and real estate sales data to evaluate macroeconomic impacts on industry expectations[25] - **Model Evaluation**: The model is useful for identifying short-term profitability trends but may be limited by the lag in macroeconomic data updates[26] 5. Model Name: Refining and Oilfield Services Profitability Model - **Model Construction Idea**: This model estimates profit growth and cracking spreads for the refining industry based on changes in fuel prices, crude oil prices, and new drilling activity[27] - **Model Construction Process**: 1. The model calculates profit growth rates using changes in fuel and crude oil prices[27] 2. Cracking spreads are derived from the difference between product prices and raw material costs[27] 3. Allocation signals are generated based on oil price trends and drilling activity[27] - **Model Evaluation**: The model captures key profitability drivers but may not fully account for geopolitical risks affecting oil prices[34][35] --- Backtesting Results of Models 1. Coal Industry Profit Forecast Model - **Excess Return**: The coal industry underperformed the Wind All-A Index by -9.8% in August 2025[10] 2. Hog Supply-Demand Gap Estimation Model - **Supply-Demand Balance**: The potential supply for Q1 2026 is estimated at 19,380 million heads, while the demand is forecasted at 19,476 million heads, indicating a slightly tight balance[18] 3. Steel Industry Profit Forecast Model - **Profit Growth**: The steel industry is predicted to achieve positive year-on-year profit growth in August 2025[23] 4. Glass and Cement Industry Profitability Tracking Model - **Glass Industry**: Profit margins continued to decline year-on-year in August 2025, but the rate of decline narrowed[26] - **Cement Industry**: Profitability slightly declined year-on-year in August 2025[26] 5. Refining and Oilfield Services Profitability Model - **Refining Industry**: Profit growth for August 2025 is predicted to be positive[28] - **Oilfield Services**: Oil prices in August 2025 were lower than the previous year, and drilling activity remained stable, leading to a neutral allocation signal[35]

Group 1 - The report indicates that as of mid-August, the upstream resource industry is experiencing an upward trend in prosperity, while the midstream manufacturing sector shows a mixed performance, with sectors like non-ferrous metals, coal, basic chemicals, and oil and petrochemicals improving continuously [4] - In the downstream consumption sector, there is a divergence in performance; the social services and home appliance industries are on the rise, while the commercial retail sector is declining. In essential consumption, the agriculture, forestry, animal husbandry, fishery, food and beverage, and textile and apparel industries are generally experiencing a downturn [4] - Supportive service industries and the financial sector are overall declining, with the environmental protection industry within supportive services also showing a downturn. However, the banking sector is improving, and the non-bank financial sector is on the rise, while the computer sector within the TMT industry is declining [4] Group 2 - The report tracks excess returns in various industries, including basic chemicals, steel, non-ferrous metals, coal, oil and petrochemicals, and construction materials, providing correlation data with high-frequency indicators [5][10][17][31][36][39][46][77] - The basic chemicals industry shows a strong correlation with various commodity prices, indicating potential investment opportunities based on price movements [6][9][17] - The steel industry is closely linked to production and inventory metrics, suggesting that monitoring these indicators can provide insights into future performance [10][12][14] Group 3 - The report highlights the importance of tracking excess returns in the automotive industry, with indicators such as daily sales and production rates being critical for understanding market dynamics [48][50] - The machinery equipment sector's performance is analyzed through various price indices, indicating a need for investors to pay attention to these metrics for better investment decisions [55][58] - The report also emphasizes the significance of high-frequency indicators in the transportation sector, which can provide insights into overall economic activity and sector performance [60][62] Group 4 - The agricultural sector's excess returns are tracked against food product price indices, indicating a strong relationship between agricultural prices and overall sector performance [96][98] - The report discusses the food and beverage industry's performance in relation to various price indices, suggesting that monitoring these can help identify investment opportunities [98][99] - The pharmaceutical and biotechnology sectors are analyzed with respect to traditional Chinese medicine price indices, highlighting the importance of these metrics in understanding market trends [101][106] Group 5 - The public utilities sector's performance is linked to coal consumption metrics, indicating that energy prices and consumption patterns are critical for assessing sector health [111][114] - The real estate sector's excess returns are correlated with metrics such as transaction volumes and land prices, suggesting that these indicators are vital for understanding market conditions [115][121] - The report also examines the computer industry, focusing on the relationship between excess returns and pricing trends in electronic components, which can inform investment strategies [124][127]

Group 1 - The core observation indicates a narrowing year-on-year growth in July's social retail sales, which fell below market expectations, while the effects of consumption expansion policies are still present, particularly in home appliances, furniture, and communication equipment [2][21][22] - The report highlights that first-tier cities continue to be a major drag on retail recovery, with consumption drivers shifting towards third and fifth-tier cities [21][22] - Essential consumption shows a mixed performance, with staple food demand remaining robust, while clothing and textiles have slowed down [21][22] Group 2 - In the information technology sector, the Philadelphia Semiconductor Index has declined, while the Taiwan Semiconductor Industry Index and DXI Index have increased [4][6] - The production of integrated circuits and smartphones has shown a rolling year-on-year increase in July, indicating a positive trend in the tech manufacturing sector [4][6] - The prices of lithium raw materials and cobalt products have risen, while the price of DMC has decreased, reflecting mixed trends in the midstream manufacturing sector [4][6] Group 3 - In the midstream manufacturing sector, the production of metal cutting machine tools and packaging equipment has seen a year-on-year increase, while the production of solar cells has narrowed [4][6] - The sales of major engineering machinery companies improved year-on-year in July, indicating a recovery in the construction and machinery sectors [4][6] - The report recommends focusing on sectors with high or improving economic conditions, such as building materials, engineering machinery, general equipment, photovoltaics, semiconductors, and non-bank financials [1][12]

Core Viewpoint - The article emphasizes that not all stocks with doubled earnings are genuine growth stocks, and distinguishing between true growth and inflated figures is crucial for investment success [3][4]. Group 1: True vs. Pseudo Growth - True growth is characterized by substantial business improvement, such as high order volumes and increased production capacity, exemplified by companies like Jiao Cheng Ultrasound, which saw contract liabilities triple and capacity utilization at 95% [3][4]. - Pseudo growth often relies on government subsidies or minor profit increases from previous losses, as seen with Huayin Power, which reported a net profit of only 1.9 million last year, making this year's doubling less impressive [3][4]. Group 2: Screening Methodology - A three-step screening method is proposed to identify genuine growth stocks: 1. Filter out "watered-down earnings" by ensuring net profit growth exceeds 50% after excluding non-recurring income, and that cash received is over 80% of net profit [4]. 2. Identify opportunities with unrecognized market potential, such as companies exceeding growth forecasts or having lower-than-average P/E ratios [4]. 3. Assess industry health, focusing on sectors with high certainty, like AI and high-end manufacturing, where companies show significant contract growth and high capacity utilization [4]. Group 3: Investment Strategies - Three practical strategies for buying and selling stocks are outlined: 1. The "Golden Pit First Jump" strategy targets stocks that show significant initial earnings growth and high trading volume [5]. 2. The "Quarterly Report Scholar Relay" strategy focuses on stocks with consistent earnings growth across quarters, particularly when the stock price remains stable after positive reports [5]. 3. The "Windfall Ambush" strategy seeks stocks in trending sectors that show substantial growth but are temporarily undervalued [5]. Group 4: Exit Strategies - For profit-taking, sell when the P/E ratio exceeds the industry average by 20% or when the stock price reaches new highs but shows declining momentum [6]. - For loss-cutting, exit if the stock price fills a gap within three days or if earnings are proven false [6]. Group 5: Key Investment Principles - The article concludes that the best opportunities during earnings season lie within the triangle of "exceeding expectations, undervaluation, and high industry health" [6].

Group 1 - The current market is focusing on the annual reports and Q1 performance of listed companies, as the time lag between policy implementation and its impact on company performance requires confirmation from institutions regarding industry prosperity and earnings realization [1][2] - As of March 25, nearly 500 companies have disclosed their 2021 annual reports, with over 4,000 companies expected to report by the end of April [1] - Historical data suggests that A-shares have a high probability of adjustment in mid-April, leading to a period of repeated bottoming with a focus on structural opportunities [1][2] Group 2 - Institutions are likely to increase their focus on companies with sustainable earnings and favorable industry conditions to attract further investment [1] - The investment community is particularly interested in sectors with high growth potential, such as the semiconductor industry, while also considering defensive stocks like telecom operators and high-dividend stocks [2] - Market sentiment is expected to remain weak post-adjustment, with a heightened demand for growth certainty in investment targets [2]

Investment Rating - The report maintains an "Outperform" rating for the agricultural chemical industry [4][8]. Core Viewpoints - The agricultural chemical industry is experiencing upward price trends in potassium and glyphosate, with an expanding price gap for phosphate exports [1][3]. - The supply-demand balance for potassium fertilizer is tight, with international prices continuing to rise, while domestic production is expected to decrease slightly in 2024 [1][23]. - The phosphate chemical sector is expected to maintain a high price level due to the scarcity of resources and increasing demand from new applications such as lithium iron phosphate [2][46]. - The pesticide sector is anticipated to see a recovery as the "rectification and reform" initiative progresses, with demand increasing due to rising agricultural planting areas in South America [3][4]. Summary by Sections Potassium Fertilizer - The global potassium fertilizer market is characterized by a supply-demand imbalance, with China being the largest consumer and an import dependency exceeding 60% [1][23]. - Domestic potassium chloride production is projected to be 5.5 million tons in 2024, a decrease of 2.7% year-on-year, while imports are expected to reach a record high of 12.633 million tons, up 9.1% [1][23]. - The average price of potassium chloride in July rose from 3,239 CNY/ton to 3,399 CNY/ton, stabilizing at 3,230 CNY/ton by the end of the month [1][40]. Phosphate Chemicals - The long-term price center for phosphate rock is expected to remain high due to declining grades and increasing extraction costs, with the market price for 30% grade phosphate rock remaining above 900 CNY/ton for over two years [2][46]. - As of July 31, 2025, the price for 30% grade phosphate rock in Hubei was 1,040 CNY/ton, while in Yunnan it was 970 CNY/ton, both stable compared to the previous month [2][46]. - The price gap between domestic and international phosphate fertilizers has widened, benefiting companies with export quotas [3][46]. Pesticides - The pesticide sector is entering a recovery phase, with demand driven by increased agricultural planting areas in South America [3][4]. - The pesticide price index has seen a significant decline over the past three years, but demand is expected to strengthen as inventory levels are replenished [3][4]. - Key companies in the pesticide sector include Yangnong Chemical and Lier Chemical, which are recommended for investment [4][8].

Quantitative Models and Construction Methods 1. Model Name: Coal Industry Profit Forecast Model - **Model Construction Idea**: The model estimates monthly revenue and profit growth rates for the coal industry based on changes in price and capacity factors[10] - **Model Construction Process**: 1. The pricing mechanism is determined by the long-term contract system, where the sales price for the next month is based on the last price index of the current month[10] 2. The model incorporates year-over-year changes in price factors and capacity factors to estimate revenue and profit growth rates on a monthly basis[10] - **Model Evaluation**: The model provides a systematic approach to track and predict industry profitability trends, but it relies heavily on the accuracy of price and capacity factor inputs[10][14] 2. Model Name: Hog Supply-Demand Gap Estimation Model - **Model Construction Idea**: The model predicts the supply-demand gap for hogs six months in advance based on the relationship between sow inventory and hog slaughter rates[15] - **Model Construction Process**: 1. The model assumes a stable proportional relationship between quarterly hog slaughter and sow inventory lagged by six months[15] 2. The formula for the slaughter coefficient is: $ \text{Slaughter Coefficient} = \frac{\text{Quarterly Hog Slaughter}}{\text{Sow Inventory (Lagged 6 Months)}} $[15] 3. The potential supply and demand six months later are calculated as: $ \text{Potential Supply (t+6)} = \text{Sow Inventory (t)} \times \text{Slaughter Coefficient (t+6)} $ $ \text{Potential Demand (t+6)} = \text{Hog Slaughter (t+6, Previous Year)} $[16] - **Model Evaluation**: Historical data shows that this model effectively identifies hog price upcycles, making it a valuable tool for forecasting[16] 3. Model Name: Steel Industry Profit Forecast Model - **Model Construction Idea**: The model predicts monthly profit growth rates and per-ton profitability for the steel industry by integrating steel prices and raw material costs[18] - **Model Construction Process**: 1. The model uses comprehensive steel prices and considers the costs of raw materials such as iron ore, coke, pulverized coal, and scrap steel[18] 2. Monthly profit growth rates and per-ton profitability are calculated based on these inputs[18] - **Model Evaluation**: The model captures the dynamics of the steel industry effectively, but its accuracy depends on the reliability of input data[23] 4. Model Name: Glass and Cement Industry Profitability Tracking Model - **Model Construction Idea**: The model tracks profitability changes in the glass and cement industries using price and cost indicators, and designs allocation signals based on these changes[25] - **Model Construction Process**: 1. The model monitors price and cost indicators to assess profitability trends in the glass and cement industries[25] 2. It incorporates economic data such as manufacturing PMI and real estate sales to analyze potential infrastructure investment expectations[25] - **Model Evaluation**: The model provides a comprehensive view of industry profitability and its drivers, but it is sensitive to macroeconomic fluctuations[29] 5. Model Name: Refining and Oilfield Services Profitability Model - **Model Construction Idea**: The model estimates profit growth rates and cracking spreads for the refining industry based on changes in fuel prices and crude oil prices[30] - **Model Construction Process**: 1. The model calculates profit growth rates and cracking spreads using changes in fuel and crude oil prices[30] 2. Allocation signals are designed based on oil prices, cracking spreads, and new drilling activity[30] - **Model Evaluation**: The model effectively captures the profitability dynamics of the refining industry, but its performance is influenced by oil price volatility[37] --- Backtesting Results of Models 1. Coal Industry Profit Forecast Model - **Excess Return**: The coal industry index achieved a cumulative excess return of 0.3% in July 2025[10] 2. Hog Supply-Demand Gap Estimation Model - **Supply-Demand Balance**: The model predicts a potential supply of 18,249,000 hogs and a demand of 18,226,000 hogs for Q4 2025, indicating a roughly balanced market[17] 3. Steel Industry Profit Forecast Model - **Profit Growth**: The model predicts positive year-over-year profit growth for July 2025, with improved per-ton profitability[23] 4. Glass and Cement Industry Profitability Tracking Model - **Glass Industry**: The model indicates that glass industry gross profit remains in a year-over-year decline, but the rate of decline has narrowed[29] - **Cement Industry**: The model predicts a slight year-over-year profit growth for the cement industry in July 2025[29] 5. Refining and Oilfield Services Profitability Model - **Profit Growth**: The model predicts slight year-over-year profit growth for the refining industry in July 2025[33] - **Oilfield Services**: The model observes that oil prices in July 2025 are lower than the previous year, with no significant change in new drilling activity[38]

Report Industry Investment Rating No relevant content provided. Core Viewpoints Manufacturing - Overall: In July, the manufacturing PMI's five - year percentile was 25.4%, with a change of - 18.6%. Seven industries had their manufacturing PMI in the expansion range, an increase of 1 month - on - month and 5 year - on - year [4]. - Supply: It slightly rebounded. The 3 - month average of the manufacturing PMI production index in July was 50.7, a 0.2 - percentage - point increase month - on - month. Nine industries improved month - on - month, while 6 declined [4]. - Demand: It slightly improved. The 3 - month average of the manufacturing PMI new orders in July was 49.8, a 0.1 - percentage - point increase month - on - month. Nine industries improved month - on - month, while 6 declined [4]. - Inventory: De - stocking slowed down. The 3 - month average of the manufacturing PMI finished - goods inventory in July remained unchanged at 47.3, with 7 industries seeing inventory increases and 8 seeing decreases. The raw - material inventory in March increased by 0.2 percentage points to 47.7, with 6 industries seeing inventory increases and 8 seeing decreases [4]. Non - manufacturing - Overall: In July, the non - manufacturing PMI's five - year percentile was 15.2%, with a change of - 15.3%. Eleven industries had their non - manufacturing PMI in the expansion range, unchanged month - on - month and a decrease of 1 year - on - year [5]. - Supply: Employment slowed down. The 3 - month average of the non - manufacturing PMI employee index in July remained unchanged at 45.5. The service industry decreased by 0.1 percentage points, while the construction industry increased by 1 percentage point [5]. - Demand: It recovered. The 3 - month average of the non - manufacturing PMI new orders in July was 46.1, a 0.3 - percentage - point increase month - on - month. The service industry's new orders increased by 0.1 percentage points, and the construction industry's increased by 1 percentage point [5]. - Inventory: De - stocking slowed down. The 3 - month average of the non - manufacturing PMI inventory in July remained unchanged at 45.4. The service industry remained unchanged, and the construction industry increased by 0.2 percentage points [5]. Summary by Directory Overview - Manufacturing PMI: In July, the manufacturing PMI's five - year percentile was 25.4%, with a change of - 18.6%. Seven industries had their manufacturing PMI in the expansion range, an increase of 1 month - on - month and 5 year - on - year [10]. - Non - manufacturing PMI: In July, the non - manufacturing PMI's five - year percentile was 15.2%, with a change of - 15.3%. Eleven industries had their non - manufacturing PMI in the expansion range, unchanged month - on - month and a decrease of 1 year - on - year [10]. Demand: Focus on the Improvement of General Equipment and Construction Installation and Decoration - Manufacturing: The 3 - month average of the manufacturing PMI new orders in July was 49.8, a 0.1 - percentage - point increase month - on - month. Nine industries improved month - on - month, while 6 declined [17]. - Non - manufacturing: The 3 - month average of the non - manufacturing PMI new orders in July was 46.1, a 0.3 - percentage - point increase month - on - month. The service industry's new orders increased by 0.1 percentage points, and the construction industry's increased by 1 percentage point. By industry, 8 industries improved month - on - month, while 7 declined [17]. Supply: Focus on the Contraction of Non - ferrous Metals, Automobiles, and Textiles - Manufacturing: The 3 - month average of the manufacturing PMI production index in July was 50.7, a 0.2 - percentage - point increase month - on - month. Nine industries improved month - on - month, while 6 declined. The manufacturing PMI employee index in March remained unchanged at 48.0. Six industries improved month - on - month, while 9 declined [24]. - Non - manufacturing: The 3 - month average of the non - manufacturing PMI employee index in July remained unchanged at 45.5. The service industry decreased by 0.1 percentage points, and the construction industry increased by 1 percentage point. By industry, 4 industries improved month - on - month, while 11 declined [24]. Price: Focus on the Pressure of Non - ferrous Metals and Textiles - Manufacturing: The 3 - month average of the manufacturing PMI ex - factory price index in July was 46.4, a 1.2 - percentage - point increase month - on - month. Nine industries saw price improvements, while 6 declined. In terms of profit, the profit trend in March decreased by 1.4 percentage points, and the overall profit continued to converge [31]. - Non - manufacturing: The 3 - month average of the non - manufacturing charge price index in July was 48.0, a 0.4 - percentage - point increase month - on - month. The service industry increased by 0.4 percentage points, and the construction industry increased by 0.7 percentage points. By industry, 8 industries improved month - on - month, while 6 declined. In terms of profit, the profit in March decreased by 0.6 percentage points. The service industry decreased by 0.4 percentage points, and the construction industry decreased by 1.3 percentage points [31]. Inventory: Focus on the Low Levels of Postal Services and Textile and Apparel - Manufacturing: The 3 - month average of the manufacturing PMI finished - goods inventory in July remained unchanged at 47.3. Seven industries saw inventory increases, and 8 saw decreases. The raw - material inventory in March increased by 0.2 percentage points to 47.7. Six industries saw inventory increases, and 8 saw decreases [40]. - Non - manufacturing: The 3 - month average of the non - manufacturing PMI inventory in July remained unchanged at 45.4. The service industry remained unchanged, and the construction industry increased by 0.2 percentage points. By industry, 6 industries saw inventory increases, and 9 saw decreases [40]. Main Manufacturing Industry PMI Charts - The report provides multiple charts showing data such as the manufacturing and non - manufacturing PMI in July, new orders, production, prices, and inventory, along with their changes and five - year percentiles [8]. - Tables present detailed PMI data for various manufacturing industries, including general equipment, automobiles, computers, and others, covering aspects like new orders, production, employment, prices, and inventory [51][56][60].