格隆汇1月4日丨中油工程(600339.SH)公布，公司于2025年12月31日收到上交所出具的《关于受理中国 石油集团工程股份有限公司沪市主板上市公司发行证券申请的通知》(上证上审(再融资)〔2025〕428 号)。上交所依据相关规定对公司报送的沪市主板上市公司发行证券的募集说明书及相关申请文件进行 了核对，认为该项申请文件齐备，符合法定形式，决定予以受理并依法进行审核。 ...

Group 1 - The "Three Oil Giants" refer to China National Petroleum Corporation (CNPC), Sinopec Limited, and China National Offshore Oil Corporation (CNOOC), which are the main state-owned enterprises in China's oil exploration, extraction, refining, and supply sectors [1] - A total of 35 personnel changes occurred across 9 listed companies controlled by Sinopec, CNPC, and CNOOC, with 6 companies experiencing changes at the chairman, general manager, and vice chairman levels [3] - Sinopec saw significant personnel changes, including the resignation of Chairman Ma Yongsheng and the appointment of Liu Qiang as General Manager and Vice Chairman [4][5] Group 2 - CNPC experienced personnel adjustments with 14 changes across 3 listed companies, including the resignation of Vice Chairman Hou Qijun and President Huang Yongzhang, with Ren Lixin appointed as the new President [13][14] - CNOOC had 4 personnel changes, including the resignation of Chairman Wang Dongjin and the appointment of Zhang Chuanjiang as the new Chairman [20][21] - The personnel changes reflect a broader trend of leadership transitions within major state-owned enterprises in China's oil and gas sector [3][19]

Core Viewpoint - The oil service engineering sector experienced a decline of 0.43% on December 31, with Junyou Co., Ltd. leading the losses. The Shanghai Composite Index rose by 0.09%, while the Shenzhen Component Index fell by 0.58 [1]. Group 1: Market Performance - The closing price of Junyou Co., Ltd. was 7.40, reflecting a decrease of 3.77% with a trading volume of 171,200 shares and a transaction value of 12.7 million [2]. - The oil service engineering sector saw a net outflow of 83 million yuan from main funds, while retail investors contributed a net inflow of 63.74 million yuan [2]. Group 2: Individual Stock Performance - Qianeng Hengxin closed at 18.48, with an increase of 1.48% and a trading volume of 38,900 shares, resulting in a transaction value of 71.43 million [1]. - The stock of Zhongman Petroleum closed at 23.05, down by 1.91%, with a trading volume of 84,600 shares and a transaction value of 195 million [2]. - The stock of Huibo Yin closed at 3.19, down by 1.54%, with a trading volume of 247,500 shares and a transaction value of 7.88 million [2]. Group 3: Fund Flow Analysis - The main funds showed a net outflow of 751,820 yuan from Junyou Co., Ltd., while retail investors had a net inflow of 1,015,780 yuan [3]. - The main funds experienced a net outflow of 812,200 yuan from Keli Co., Ltd., with retail investors showing a net outflow of 167,080 yuan [3]. - The stock of Zhongyou Engineering had a net outflow of 95,510 yuan from main funds, while retail investors had a net inflow of 4,810 yuan [3].

Quantitative Models and Construction Methods 1. Model Name: GAN_GRU - **Model Construction Idea**: The GAN_GRU model combines Generative Adversarial Networks (GAN) for feature generation and Gated Recurrent Unit (GRU) for time-series feature encoding to construct a stock selection factor[4][13][14] - **Model Construction Process**: 1. **GAN Component**: - The generator (G) learns the real data distribution and generates realistic samples from random noise \( z \) (Gaussian or uniform distribution). The generator's loss function is: $$ L_{G} = -\mathbb{E}_{z\sim P_{z}(z)}[\log(D(G(z)))] $$ where \( D(G(z)) \) represents the discriminator's probability of classifying generated data as real[24][25][26] - The discriminator (D) distinguishes real data from generated data. Its loss function is: $$ L_{D} = -\mathbb{E}_{x\sim P_{data}(x)}[\log D(x)] - \mathbb{E}_{z\sim P_{z}(z)}[\log(1-D(G(z)))] $$ where \( D(x) \) is the probability of real data being classified as real, and \( D(G(z)) \) is the probability of generated data being classified as real[27][29][30] - GAN training alternates between optimizing \( G \) and \( D \) until convergence[30] 2. **GRU Component**: - Two GRU layers (GRU(128, 128)) are used to encode time-series features, followed by a Multi-Layer Perceptron (MLP) with layers (256, 64, 64) to predict returns. The final output \( pRet \) is used as the stock selection factor[22] 3. **Feature Input and Processing**: - Input features include 18 price-volume characteristics (e.g., closing price, turnover, etc.) sampled over the past 400 days, with a shape of \( 40 \times 18 \) (40 days of features)[18][19][37] - Features undergo outlier removal, standardization, and cross-sectional normalization[18] 4. **Training Details**: - Training-validation split: 80%-20% - Semi-annual rolling training (June 30 and December 31 each year) - Hyperparameters: batch size equals the number of stocks, Adam optimizer, learning rate \( 1e-4 \), IC loss function, early stopping (10 rounds), max training rounds (50)[18] 5. **Stock Selection**: - Stocks are filtered to exclude ST stocks and those listed for less than six months[18] - **Model Evaluation**: The GAN_GRU model effectively captures price-volume time-series features and demonstrates strong predictive power for stock returns[4][13][22] --- Model Backtesting Results 1. GAN_GRU Model - **IC Mean**: 0.1119*** (2019-2025)[4][41] - **ICIR (non-annualized)**: 0.89[42] - **Turnover Rate**: 0.83X[42] - **Recent IC**: 0.0331*** (December 2025)[4][41] - **1-Year IC Mean**: 0.0669***[4][41] - **Annualized Return**: 37.40%[42] - **Annualized Volatility**: 23.39%[42] - **IR**: 1.60[42] - **Maximum Drawdown**: 27.29%[42] - **Annualized Excess Return**: 22.42%[4][42] --- Quantitative Factors and Construction Methods 1. Factor Name: GAN_GRU Factor - **Factor Construction Idea**: The GAN_GRU factor is derived from the GAN_GRU model, leveraging GAN for price-volume feature generation and GRU for time-series encoding[4][13][14] - **Factor Construction Process**: - The GAN generator processes raw price-volume time-series features (\( Input\_Shape = 40 \times 18 \)) and outputs transformed features with the same shape (\( Input\_Shape = 40 \times 18 \))[37] - The GRU component encodes these features into a predictive factor for stock selection[22] - The factor undergoes industry and market capitalization neutralization and standardization[22] - **Factor Evaluation**: The GAN_GRU factor demonstrates robust performance across various industries and time periods, with significant IC values and excess returns[4][41] --- Factor Backtesting Results 1. GAN_GRU Factor - **IC Mean**: 0.1119*** (2019-2025)[4][41] - **ICIR (non-annualized)**: 0.89[42] - **Turnover Rate**: 0.83X[42] - **Recent IC**: 0.0331*** (December 2025)[4][41] - **1-Year IC Mean**: 0.0669***[4][41] - **Annualized Return**: 37.40%[42] - **Annualized Volatility**: 23.39%[42] - **IR**: 1.60[42] - **Maximum Drawdown**: 27.29%[42] - **Annualized Excess Return**: 22.42%[4][42] 2. Industry-Specific Performance - **Top 5 Industries by Recent IC (October 2025)**: - Social Services: 0.4243*** - Coal: 0.2643*** - Environmental Protection: 0.2262*** - Retail: 0.1888*** - Steel: 0.1812***[4][41][42] - **Top 5 Industries by 1-Year IC Mean**: - Social Services: 0.1303*** - Steel: 0.1154*** - Non-Bank Financials: 0.1157*** - Retail: 0.1067*** - Building Materials: 0.1017***[4][41][42] 3. Industry-Specific Excess Returns - **Top 5 Industries by December 2025 Excess Returns**: - Banking: 4.30% - Real Estate: 3.51% - Environmental Protection: 2.18% - Retail: 1.76% - Machinery: 1.71%[2][45] - **Top 5 Industries by 1-Year Average Excess Returns**: - Banking: 2.12% - Real Estate: 1.93% - Environmental Protection: 1.50% - Retail: 1.46% - Machinery: 1.23%[2][46]

证券代码：600339 证券简称：中油工程 公告编号：2025-072 中国石油集团工程股份有限公司 关于 2025 年 11 月份担保发生情况的公告 本公司董事会及全体董事保证本公告内容不存在任何虚假记载、误导性陈述 或者重大遗漏，并对其内容的真实性、准确性和完整性承担法律责任。 重要内容提示： | 被担保人名称 | | 本次担保金额 | 实际为其提供的担 | | 是否在 | 本次担 | | --- | --- | --- | --- | --- | --- | --- | | | | | 保余额（不含本次担 | | 前期预 | 保是否 | | | | | 保金额） | | 计额度 | 有反担 | | | | | | | 内 | 保 | | 中国石油天然气第七建设有限公司 | 91.66 | 万元 | 20,890.59 | 万元 | 是 | 否 | | 中国石油天然气第一建设有限公司 | 425.56 | 万元 | 35,691.91 | 万元 | 是 | 否 | | 中油（新疆）石油工程有限公司 | 822.80 | 万元 | 48,917.12 | 万元 | 是 | 否 | | 青岛中油岩土工程有限公 ...

证券代码：600339 证券简称：中油工程 公告编号：2025-071 中国石油集团工程股份有限公司 2025年第二次临时股东会决议公告 | 1.出席会议的股东和代理人人数 | 346 | | --- | --- | | 2.出席会议的股东所持有表决权的股份总数（股） | 4,319,260,607 | | 3.出席会议的股东所持有表决权股份数占公司有表决权股 | 77.3625 | | 份总数的比例（%） | | (四) 表决方式是否符合《公司法》及《公司章程》的规定，股东会主持情况等。 本次会议由公司董事会召集，会议由董事长白雪峰先生主持，会议采用现场 投票和网络投票相结合的方式表决。本次会议的召集、召开、表决符合《公司法》 和《公司章程》有关规定。 (一) 股东会召开的时间：2025 年 12 月 30 日 (二) 股东会召开的地点：北京市朝阳区安立路 101 号名人大厦 0903 会议室 (五) 公司董事和董事会秘书的出席情况 1. 公司在任董事9人，出席9人，董事长白雪峰先生，董事王新革女士、薛枫先 生、宋少光先生、张红斌先生、宋官武先生，独立董事张克华先生、张占魁 先生、王雪华先生出席了会议。 2 ...

北京市金杜律师事务所 关于中国石油集团工程股份有限公司 2025 年第二次临时股东会的法律意见书 致：中国石油集团工程股份有限公司 北京市金杜律师事务所（以下简称本所）接受中国石油集团工程股份有限公 司（以下简称公司）的委托，根据《中华人民共和国证券法》（以下简称《证券 法》）、《中华人民共和国公司法》（以下简称《公司法》）、中国证券监督管 理委员会《上市公司股东会规则》（以下简称《股东会规则》）等中华人民共和 国境内（以下简称中国境内，为本法律意见书之目的，不包括中国香港特别行政 区、中国澳门特别行政区和中国台湾省）现行有效的法律、行政法规、部门规章、 规范性文件和现行有效的《中国石油集团工程股份有限公司章程》（以下简称《公 司章程》）有关规定，指派律师出席了公司于 2025 年 12 月 30 日召开的 2025 年第二次临时股东会（以下简称本次股东会），并就本次股东会相关事项出具本 法律意见书。 为出具本法律意见书，本所律师审查了公司提供的以下文件，包括但不限于： 1. 经公司 2024 年年度股东大会审议通过的《公司章程》； 2. 公司于 2025 年 12 月 13 日刊登于上海证券交易所网站的《中 ...

Core Insights - The oil service engineering sector experienced a 0.59% increase on December 30, with Junyou Co., Ltd. leading the gains [1] - The Shanghai Composite Index closed at 3965.12, showing no change, while the Shenzhen Component Index rose by 0.49% to 13604.07 [1] Sector Performance - Junyou Co., Ltd. (002207) closed at 7.69, up 3.22% with a trading volume of 240,600 shares and a transaction value of 182 million yuan [1] - Tongyuan Petroleum (300164) closed at 5.71, up 2.51% with a trading volume of 732,600 shares and a transaction value of 409 million yuan [1] - Zhongman Petroleum (603619) closed at 23.50, up 1.64% with a trading volume of 112,500 shares and a transaction value of 263 million yuan [1] - Other notable performances include Haiyou Development (600968) up 1.58% and Yingtai History (601808) up 0.72% [1] Capital Flow - The oil service engineering sector saw a net outflow of 43.23 million yuan from institutional investors, while retail investors contributed a net inflow of 63.65 million yuan [2] - The main capital inflow was observed in Junyou Co., Ltd. with a net inflow of 13.43 million yuan, while Haiyou Development and Tongyuan Petroleum also saw significant inflows [3] - Conversely, companies like Beiken Energy (002828) and Huibo Yin (002554) experienced notable net outflows from both institutional and retail investors [3]

Market Overview - The oil service engineering sector experienced a slight decline of 0.08% on December 29, with Huibo leading the drop [1] - The Shanghai Composite Index closed at 3965.28, up 0.04%, while the Shenzhen Component Index closed at 13537.1, down 0.49% [1] Stock Performance - Notable stock performances in the oil service engineering sector included: - Zhongman Petroleum (603619) closed at 23.12, up 1.05% with a trading volume of 100,500 shares and a turnover of 233 million yuan [1] - Bomaike (603727) closed at 14.04, up 0.79% with a trading volume of 18,500 shares [1] - Tongyuan Petroleum (300164) closed at 5.57, up 0.54% with a trading volume of 741,800 shares and a turnover of 414 million yuan [1] - Huibo (002554) closed at 3.29, down 2.95% with a trading volume of 311,500 shares and a turnover of 103 million yuan [2] Capital Flow - The oil service engineering sector saw a net inflow of 4.147 million yuan from institutional investors, while retail investors experienced a net outflow of 1.2712 million yuan [2][3] - The capital flow for specific stocks included: - Zhongman Petroleum had a net inflow of 27.1129 million yuan from institutional investors, but a net outflow of 34.9077 million yuan from retail investors [3] - Tongyuan Petroleum had a net inflow of 25.8586 million yuan from institutional investors, with a net outflow of 44.3007 million yuan from retail investors [3] - Huibo experienced a significant net outflow of 30.448 million yuan from retail investors [3]

Core Viewpoint - The company has signed an EPC contract worth $424 million for the ethane and propane pipeline project in Kazakhstan, which is expected to enhance its market presence in Central Asia [4][5]. Group 1: Project Details - The contract involves the construction of a 209.4 km ethane pipeline with a diameter of 406.4 mm, a 208.1 km ethane pipeline with a diameter of 323.8 mm, and a 5.5 km propane connection pipeline with a diameter of 219.1 mm [5]. - The project is a recognition of the company's capabilities in total contracting for construction by KMG PetroChem, a subsidiary of Kazakhstan's national oil and gas company [5]. Group 2: Market Expansion - The company has achieved a cumulative new contract amount of 99.216 billion yuan in the first three quarters of 2025, representing a year-on-year growth of 5.25% [7]. - Domestic contracts accounted for 73.95 billion yuan (74.54% of total new contracts), while overseas contracts reached 25.264 billion yuan (25.46% of total new contracts), with a year-on-year growth of 9.4% in overseas contracts [7]. - The company has consistently ranked among the top 250 international contractors and the top ten global oil and gas engineering companies for eight consecutive years, indicating strong construction capabilities and a rich project portfolio [7]. Group 3: Opportunities in Domestic and International Markets - The global upstream capital expenditure remains high, with China’s oil sector expected to achieve 210 billion yuan in upstream capital expenditure by 2025, which is likely to support the company's oil and gas field engineering business [8]. - The domestic refining industry is accelerating its transformation, with capital expenditures for high-end new materials projects continuing to grow, while the Middle East has seen active capital expenditures exceeding $100 billion [8]. - The company is expected to benefit significantly from the "Belt and Road" initiative, which integrates exploration, pipeline operation, refining, engineering services, and financial trade into a complete industrial chain [8].