煤炭 煤炭进口数据拆解 领先大市-A(维持) 【山证煤炭】7 月：供给收缩，反内卷或 带来"温和风暴"-煤炭月度供需数据点 评 2025.8.18 【山证煤炭】煤炭行业动态点评：长协 倒挂解除，煤价预期再次提升 2025.8.7 分析师： 资料来源：最闻 首选股票 评级 胡博 执业登记编码：S0760522090003 邮箱：hubo1@sxzq.com 煤炭板块近一年市场表现 25 年 7 月进口煤量收缩趋势放缓，未来增量有待观察 2025 年 8 月 26 日 行业研究/行业月度报告 投资要点： 数据拆解： 进口煤量收缩趋势放缓，进口价下降。进口量方面，1-7 月累计增速实现 -13%，累计进口煤量仍然呈现收缩趋势；尽管 7 月当月同比连续 5 个月保持负 增速，但同比负增速出现边际放缓走势、环比呈现正增长，其中 7 月进口煤同比 降 22.94%、环比增 7.78%。分煤种来看，所有煤种同比仍然呈现负增长，但环 比方面仅无烟煤呈现负增长。炼焦煤增量主要来自外蒙古和俄国；动力煤增量主 要来澳大利亚；褐煤增量主要来自印度尼西亚。价格方面，全煤种进口价格实现 67 美元/吨，维持同比回落趋势，7 月当月环比降 ...

Group 1: Electricity Generation - April electricity generation remained stable year-on-year [1] - Total installed capacity exceeds 17 million kilowatts [2] Group 2: Electricity Pricing - April settlement electricity price showed little change month-on-month, slightly higher than mid-to-long-term prices [2] - Anticipated consumption situation for the 800,000 kW photovoltaic base in Xinjiang is favorable as it is a priority external power source project [2] Group 3: Coal Pricing - Long-term coal price is determined by a base price plus a floating pricing mechanism [2] - Coal prices have seen a larger year-on-year decline entering Q2 compared to Q1 [2] - Coal costs significantly impact the performance of the company's controlled power generation enterprises, with price declines positively influencing performance [2] - Expected coal consumption for Anhui units this year is projected to remain stable [2] Group 4: Financial Situation - Investment income from associated companies is under pressure due to a decline in both electricity volume and pricing [2]

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]

Core Viewpoint - In Q1 2025, the company reported a revenue of 26.577 billion yuan, a year-on-year decrease of 14.14%, while net profit attributable to shareholders increased by 3.66% to 1.930 billion yuan, indicating a mixed performance amid a challenging market environment [1][3]. Revenue and Profit Analysis - The company's Q1 2025 revenue decreased due to a relaxed supply-demand balance in electricity and a slight drop in electricity prices, with total electricity generation falling by 8.51% year-on-year to 51.384 billion kWh [1][2]. - The average on-grid electricity price in Q1 2025 was approximately 505.71 yuan per megawatt-hour, down 0.71% year-on-year, influenced by nationwide price adjustments [2]. Cost and Profitability - The company achieved a gross profit margin of 10.73% and a net profit margin of 8.52%, both showing year-on-year increases of 2.33 and 1.21 percentage points, respectively [3]. - Operating costs decreased by 16.32% year-on-year, primarily due to falling coal prices, which positively impacted profitability [3]. Cash Flow and Asset Management - The net cash flow from operating activities increased by 107.47% year-on-year, attributed to reduced fuel costs [4]. - A proposed acquisition of stakes in several companies is expected to enhance total assets by 18.37%, revenue by 25.07%, and net profit by 5.93%, significantly improving the company's asset scale and profitability [4]. Profit Forecast and Valuation - The company is projected to achieve net profits of 6.6 billion, 7.6 billion, and 8.5 billion yuan for 2025, 2026, and 2027, respectively, with year-on-year growth rates of 15.91%, 14.89%, and 11.80% [4]. - The price-to-earnings ratio for the stock is estimated to be 8.84, 7.69, and 6.88 for the years 2025, 2026, and 2027, respectively, indicating a strong investment opportunity [4].