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].

Performance Overview - As of July 21, 2025, approximately 1,500 listed companies have disclosed performance forecasts, with a disclosure rate of 28.5%[12] - Among these, 44% of companies expect positive performance, a decrease of 4 percentage points compared to 2024, marking the third lowest level since 2009 and 2020[3] - The proportion of companies expecting losses is 42%, the highest since 2010, indicating an accelerated release of loss risks[3] Sector Analysis - The pre-positive performance rates for major sectors are as follows: Non-bank financials (83%), Non-ferrous metals (74%), Electronics (61%), Agriculture (56%), and Automotive (52%)[3] - The disclosure rates for major indices are: SSE 50 (24%), CSI 300 (28%), CSI 1000 (28%), STAR Market 50 (10%), and ChiNext Index (14%) with corresponding pre-positive rates of 82%, 71%, 55%, 80%, and 93% respectively[3] Profitability Outlook - A-share profitability is expected to gradually improve due to low base effects and supply contraction, with a projected growth rate of +6.8% in Q1 2025, marking a transition from negative to positive growth[4] - Forecasts for A-share net profit growth in Q2 to Q4 2025 (excluding financials and major oil companies) are 15.0%, 18.1%, and 25.4% based on 2015 data, and 15.3%, 18.7%, and 20.3% based on 2019 data[4] Industry-Specific Predictions - Industries expected to maintain good growth or recover from the bottom include: pig farming, pet food, automotive parts, home appliances, bicycles, light consumer goods, pharmaceuticals, non-bank financials, electronics, and renewable energy[5] - The gaming industry is also projected to continue its upward trend, while sectors like real estate and steel are still facing challenges[5] Risk Considerations - The current performance forecasts do not fully represent the overall industry situation, and discrepancies may exist between analyst predictions and actual company performance[5]

Group 1 - The core viewpoint is that approximately 75% of global DMC production capacity is concentrated in China, with overseas capacity growth constrained by raw materials, costs, and market factors [1] - Domestic demand for silicone is expected to maintain a high growth rate of 15.5% by 2025, while new capacity growth will slow to 3.0%, leading to a supply-demand mismatch as demand is projected to grow by 12% [1] - Current silicone prices are at historical low levels, and with Dow's capacity exit, China's export share to Europe is expected to increase, significantly boosting marginal effects, with industry prosperity and corporate profitability likely stabilizing and recovering by 2026 [1] Group 2 - The chemical leader ETF (516220) tracks a sub-sector chemical index (000813), which is compiled by China Securities Index Co., selecting representative listed companies from the chemical raw materials, chemical products, fertilizers, and agricultural chemicals sectors to reflect the overall market performance of the chemical industry [1] - Investors without stock accounts can consider the Guotai CSI Sub-sector Chemical Industry Theme ETF Connect C (012731) and Guotai CSI Sub-sector Chemical Industry Theme ETF Connect A (012730) [1]

Investment Rating - The industry investment rating is maintained at "Neutral" as of July 16, 2025 [2]. Core Insights - The current cycle is nearing its end, with expectations for demand recovery. Infrastructure and export demand are expected to remain robust in 2024, while the real estate cycle continues to decline. The consumption sector has shown resilience after two years of recovery [4]. - On the supply side, global chemical capital growth is projected to turn negative in 2024. Domestic construction projects are seeing a rapid decline, nearing a bottom by Q2 2024, while fixed asset investments maintain a growth rate exceeding 15% [4]. - The chemical industry is entering a replenishment phase after a year of destocking, with inventory growth turning positive by Q3 2024. However, the overall price and profit levels in the chemical industry are expected to face pressure throughout the year [4]. Summary by Sections Industry Valuation and Economic Indicators - The report tracks various indicators including the chemical industry's comprehensive prosperity index and industrial added value [3]. Price Indicators - The report includes PPI, PPIRM, CCPI, and price differentials for chemical products, highlighting recent trends and historical positions [3]. Supply-Side Indicators - Key metrics include capacity utilization rates, energy consumption, fixed asset investments, inventory levels, and ongoing construction projects [3]. Import and Export Indicators - The report analyzes the contribution of import and export values to the industry [3]. Downstream Industry Performance - The report examines performance indicators for downstream sectors such as PMI, real estate, home appliances, automotive, and textiles [3]. Global Macro and End-Market Indicators - It includes global procurement manager indices, GDP year-on-year changes, civil construction starts, consumer confidence indices, and automotive sales [3]. Global Chemical Product Prices and Differentials - The report provides insights into the pricing and differentials of chemical raw materials, intermediate products, and sub-industries like resins and fibers [3]. Global Industry Economic Indicators - It covers sales revenue changes, profitability, growth potential, debt repayment capacity, operational efficiency, and per-share metrics [3]. Recommendations for Investment Opportunities - The report suggests focusing on industries with stable demand and supply logic, such as refrigerants, phosphates, and amino acids, while also highlighting sectors with improving supply-demand dynamics like organic silicon [7]. - Key recommended companies include Juhua Co., Sanmei Co., and Dongyue Group for refrigerants, and Wanhua Chemical for MDI [7]. Market Trends and Strategic Directions - The report emphasizes the shift from a cost-efficiency-driven global investment model to a stability and security-oriented regional cooperation model, suggesting investment opportunities in both domestic and international markets [7]. - Companies recommended for investment include Lite-On Technology, Ruile New Materials, and Wanrun Co. in the OLED materials sector [7].

Group 1: Coal Industry - In June 2025, coal prices are lower than the same period last year, leading to a forecast of a year-on-year decline in industry profits for July 2025, maintaining a neutral outlook for the coal industry [3]. Group 2: Livestock Farming - As of the end of May 2025, the number of breeding sows is 40.42 million, showing a slight month-on-month increase. It is predicted that the supply and demand for pigs will balance in Q4 2025, with pork prices expected to stabilize at the bottom while waiting for a significant reduction in production capacity [4]. Group 3: Steel Industry - A forecast for June 2025 indicates a year-on-year negative growth in profits for the general steel industry. The rolling average of PMI has not exceeded the threshold, maintaining a neutral signal for the steel industry [5]. Group 4: Construction Materials and Engineering - In June 2025, the gross profit of float glass is expected to decline year-on-year, maintaining a neutral signal for the glass industry. The cement industry is predicted to see year-on-year profit growth in June 2025, awaiting positive signals from new housing starts, also maintaining a neutral outlook for the cement industry [5]. - The manufacturing PMI rolling average is stabilizing, while year-on-year data for commercial housing sales shows a slight decline. Economic data remains stable, and expectations for infrastructure support are unlikely to materialize, maintaining a neutral signal for the construction and decoration industry [5]. Group 5: Fuel Refining and Oil Services - A forecast for June 2025 suggests that profits in the fuel refining industry will remain roughly flat year-on-year, maintaining a neutral outlook. Oil prices have not yet formed an upward trend year-on-year, and new drilling activities are also stable year-on-year, leading to a neutral outlook for oil services [6].

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**: - The pricing mechanism is determined by the last price index of the previous month, which sets the sales price for the next month[10] - The model incorporates 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 no significant improvement signals were observed for July 2025[13] 2. Model Name: Hog Supply-Demand Gap Estimation Model - **Model Construction Idea**: The model leverages the stable proportional relationship between hog slaughter and sow inventory lagged by six months to estimate future supply-demand gaps[14] - **Model Construction Process**: - The slaughter coefficient is calculated as: $ \text{Slaughter Coefficient} = \text{Quarterly Hog Slaughter} / \text{Sow Inventory (Lagged 6 Months)} $[14] - Future potential supply is estimated as: $ \text{6-Month Potential Supply} = \text{Current Sow Inventory} \times \text{Slaughter Coefficient (6 Months Ago)} $[15] - Future demand is projected based on historical quarterly slaughter data[15] - **Model Evaluation**: Historical data shows that this method effectively identifies hog price upward cycles[15] 3. Model Name: Steel Industry Profit Forecast Model - **Model Construction Idea**: The model predicts monthly profit growth rates and calculates per-ton profit for the steel industry by considering steel prices and raw material costs[17] - **Model Construction Process**: - The model integrates steel prices with the costs of raw materials such as iron ore, coke, pulverized coal, and scrap steel to estimate profit growth rates[17] - **Model Evaluation**: The model highlights the industry's profit trends but indicates a negative profit growth rate for June 2025[21] 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[23] - **Model Construction Process**: - For the glass industry, the model calculates gross profit based on price and cost data[27] - For the cement industry, the model incorporates coal fuel price changes to predict profit growth rates[27] - **Model Evaluation**: The model effectively tracks profitability trends but maintains a neutral signal for both industries due to the lack of significant positive indicators[27] 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, crude oil prices, and new drilling activity[28] - **Model Construction Process**: - The model uses variations in fuel and crude oil prices to calculate profit growth rates and cracking spreads[28] - Allocation signals are designed based on observed changes in oil prices, cracking spreads, and new drilling activity[28] - **Model Evaluation**: The model predicts stable profit growth for June 2025 but maintains a neutral signal due to the lack of significant upward trends in oil prices and drilling activity[35][38] --- Backtesting Results of Models 1. Coal Industry Profit Forecast Model - **Excess Return**: The model tracks the historical excess return of the coal industry relative to the Wind All-A Index, showing a declining profit trend for July 2025[13] 2. Hog Supply-Demand Gap Estimation Model - **Supply-Demand Balance**: The model predicts a balanced supply-demand scenario for Q4 2025, with potential supply at 18,226 million heads and demand at 18,244 million heads[16] 3. Steel Industry Profit Forecast Model - **Profit Growth**: The model forecasts a negative profit growth rate for June 2025, with no significant improvement in PMI rolling averages[21] 4. Glass and Cement Industry Profitability Tracking Model - **Glass Industry**: Gross profit for float glass continues to decline year-on-year as of June 2025[27] - **Cement Industry**: Profit growth is predicted to be positive for June 2025, driven by lower coal fuel prices[27] 5. Refining and Oilfield Services Profitability Model - **Profit Growth**: The model predicts stable profit growth for the refining industry in June 2025, with oil prices and new drilling activity showing no significant upward trends[35][38]

Core Viewpoint - The article discusses the increasing complexity and commercialization of college entrance examination (Gaokao) volunteer filling in China, highlighting the significant market growth and the emotional and financial stakes involved for families [3][5][29]. Group 1: Market Dynamics - The market for volunteer filling services has grown tenfold over the past decade, reflecting the rising importance of strategic choices in education [3][5]. - The price of volunteer filling services has increased, with notable examples such as Zhang Xuefeng's services selling out quickly after price hikes [3][5]. - The number of companies involved in Gaokao volunteer filling has surged, with over 1,300 operating in China, predominantly in high-stakes provinces like Hebei [23]. Group 2: Changes in Filling Mechanisms - The transition from gradient to parallel volunteer systems has made the filling process more complex, with the introduction of real-time ranking systems in regions like Inner Mongolia [6][9]. - The new Gaokao system allows for a significantly larger number of choices, with some provinces enabling students to fill out up to 270 professional preferences [9][10]. - The importance of specific majors has increased due to the limited number of prestigious universities, which has remained constant while the number of available majors has expanded dramatically [10][11]. Group 3: Emotional and Financial Stakes - The pressure on students and families is immense, as the choice of major and university can significantly impact future career prospects and income [13][19]. - The article emphasizes that the decision-making process for students is often fraught with uncertainty, leading to a reliance on external advice and services [26][27]. - The financial implications of these choices are profound, with high margins reported for volunteer filling consultation services, indicating a lucrative market for providers [24][25].

Quantitative Models and Construction 1. Model Name: Coal Industry Profit Forecast Model - **Model Construction Idea**: The model estimates the revenue and profit growth rate of the coal industry based on changes in price and capacity factors[10] - **Model Construction Process**: - 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] - The model uses the year-on-year changes in price and capacity factors to estimate monthly revenue and profit growth rates[10] - **Model Evaluation**: The model provides a systematic approach to track and predict industry profitability, but it relies heavily on the stability of the pricing mechanism and external factors like market demand[10][14] 2. Model Name: Hog Supply-Demand Gap Estimation Model - **Model Construction Idea**: The model predicts the hog supply-demand gap six months ahead based on the breeding sow inventory and historical slaughter coefficients[15] - **Model Construction Process**: - The slaughter coefficient is calculated as: $ \text{Slaughter Coefficient} = \frac{\text{Quarterly Hog Slaughter}}{\text{Breeding Sow Inventory (Lagged 6 Months)}} $[15] - The potential supply six months later is estimated as: $ \text{Potential Supply (t+6)} = \text{Breeding Sow Inventory (t)} \times \text{Slaughter Coefficient (t+6, YoY)} $[15] - The potential demand six months later is estimated as: $ \text{Potential Demand (t+6)} = \text{Hog Slaughter (t+6, YoY)} $[16] - **Model Evaluation**: Historical data shows that this model effectively identifies hog price upward cycles, making it a valuable tool for supply-demand analysis[16] 3. Model Name: Steel Industry Profit Forecast Model - **Model Construction Idea**: The model predicts monthly profit growth and per-ton profit for the steel industry by integrating steel prices and raw material costs[18] - **Model Construction Process**: - The model incorporates comprehensive steel prices and costs of raw materials such as iron ore, coke, pulverized coal, and scrap steel to estimate profit growth rates[18] - **Model Evaluation**: The model provides a detailed profit analysis but is sensitive to fluctuations in raw material prices and global demand[22] 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[23] - **Model Construction Process**: - The model monitors price and cost indicators to assess profitability changes and generate allocation signals[23] - **Model Evaluation**: The model is effective in identifying short-term profitability trends but requires additional macroeconomic indicators for long-term predictions[30] 5. Model Name: Refining and Oilfield Services Profitability Model - **Model Construction Idea**: The model estimates profit growth and cracking spreads for the refining industry based on changes in fuel prices, crude oil prices, and new drilling activities[31] - **Model Construction Process**: - The model calculates profit growth rates and cracking spreads using variations in fuel and crude oil prices[31] - Allocation signals are designed based on oil prices, cracking spreads, and new drilling activity[31] - **Model Evaluation**: The model provides a comprehensive view of industry profitability but is highly dependent on volatile oil price movements[35] --- Backtesting Results of Models 1. Coal Industry Profit Forecast Model - **Profit Growth Forecast**: Predicted a year-on-year profit decline for June 2025 due to lower coal prices compared to the previous year[14] 2. Hog Supply-Demand Gap Estimation Model - **Supply-Demand Balance**: Predicted a balanced supply-demand scenario for Q4 2025, with potential supply and demand both estimated at 18,226 million hogs[17] 3. Steel Industry Profit Forecast Model - **Profit Growth Forecast**: Predicted a slight year-on-year profit decline for May 2025, with PMI rolling averages remaining flat[22] 4. Glass and Cement Industry Profitability Tracking Model - **Glass Industry**: Predicted a year-on-year decline in gross profit for May 2025[30] - **Cement Industry**: Predicted a year-on-year profit growth for May 2025, driven by price recovery[30] 5. Refining and Oilfield Services Profitability Model - **Refining Industry**: Predicted a year-on-year profit decline for May 2025 due to lower oil prices compared to the previous year[35] - **Oilfield Services**: Observed stable new drilling activity and lower oil prices compared to the previous year, maintaining a neutral outlook[38]