消息面 本周PTA工厂库存在3.74天，较上周+0.16天，较去年同期+0.08天。 聚酯供需来看，目前PX与PTA加工利润均处于相对高位，但PX与PTA短期开工预期变化不大，对PX利 润高位形成支撑，PX基本面短期带来的驱动不强；而下游聚酯及终端处于需求淡季，相关装置开工率 持续走低，需求的减弱可能会导致PTA进一步累库，PTA加工利润偏压缩看待，PTA短期价格承压。 东海期货： 聚酯板块受负反馈影响回落，PTA仓位基本稳定，前期主力对前高进行突破测试过程中，资金持仓逐渐 减量，向上驱动减弱。下游开工进一步减少，除去年前正常降负荷外，减产存续也进一步降低对PTA采 购需求，基差近期持续缓慢走低，近期价格将进一步有回调驱动。 数据显示，PTA装置暂无明显变化，PTA负荷维持在76.6%。西南一套100万吨PTA装置重启准备中，预 计近日恢复正常，该装置11月上旬停车检修。 机构观点 迈科期货： 数据显示，2月4日华东地区精对苯二甲酸（PTA）现货价格报5150元/吨，较上一日上涨65元/吨，当日 涨幅为1.28%。最近一周，华东地区精对苯二甲酸（PTA）价格累计下跌100元/吨，下跌幅度为1.90%； 最近一 ...

截至午间收盘，中证石化产业指数下跌2.1%，中证稀土产业指数下跌4.7%。Wind数据显示，化工行业ETF易方达（516570）已连续14个交易日获资金净流 入，合计超14亿元。 市场分析认为，石化化工行业正迎来基本面复苏的关键布局期。具体来看，产能周期筑顶叠加碳排放双控政策推进，供给格局有望优化；行业"反内卷"措施 趋于立体，有望提升复苏斜率；海外产能退出与需求回暖，驱动出口迈向量价齐升；同时，化工新材料受益于新旧动能转换，将持续为行业增长注入弹性。 每日经济新闻 ...

资金面：25Q4主动偏股+灵活配置型基金对化工石化板块持仓明显回升，2025年Q4末基础化工行业公 募持仓比例从2.4%提升至3.2%，石油石化行业公募持仓比例从0.4%提升至0.6%。 产业趋势：石化化工行业是我国资源—制造业再通胀的核心环节，正逐步迎来产业基本面右侧起步阶段 的布局窗口期： 1、长周期固定资产投资转负，产能周期筑顶有望释放盈利空间， 2、政策力度超预期，"十五五"期间在全面实施碳排放双控政策的积极引领下，高耗能企业产能天花板 逐步显现，化工供给端有望率先受益， 3、"控增量、减存量、管过程"，石化化工"反内卷" "稳增长"措施趋于立体化，提升产业复苏斜率， 4、海外需求向上伴随产能退出，出口有望从以价换量转到量价齐升，中国工业力迎来估值重塑， 5、需求端受益于新旧动能转换，化工新材料有望为产业需求改善注入弹性。 相关产品：化工行业ETF易方达（516570，场外联接A/C: 020104/020105）一键打包石油石化、基础化 工产业龙头，2023年以来收益表现在可比化工行业指数中保持领先。化工行业ETF管理+托管费率 0.15%+0.05%/年，显著低于石化化工板块的同类ETF产品，较低 ...

双碳新政对石化化工行业影响解析 20260204 摘要 中国碳市场以行业管理为主，初期对电力、钢铁、有色、水泥四大行业 实施碳排放强度管控，剩余石化、化工等行业预计 2027-2028 年纳入。 企业超配额需购买，违规面临罚款，如宁夏某热电厂因未履行清算要求 被罚款 4.23 亿元。 存量高能耗项目在 2027-2028 年前暂不受年度重新考核影响，但出口 可能受欧盟碳边境调节税（CBAM）影响。新增项目需符合国家发改委 碳评价管理办法，对煤化工密集地区如新疆、内蒙等地影响较大。 碳排放配额由生态环境部根据企业实际情况核定，超出额度需购买或受 罚。目前仅电力、钢铁、电解铝和水泥行业获具体配额，其余行业预计 2027-2028 年完成分配。 中国碳排放权交易市场分为国家生态环境部负责的强制排放权交易市场 （ETS）和国家发改委对地方政府的管理。化工行业纳入预计在 2027- 2028 年，企业配额根据地区平均排放水平确定。 石化化工行业中，炼油和煤化工受碳市场影响较大，尤其是煤制甲醇， 其生产过程碳排放量高。绿色化工项目审批具优势，但竞争力取决于碳 价格，200-300 元/吨是与传统化工的平衡点。 Q&A 2 ...

（来源：东北新闻网） 2月4日，由省工业和信息化厅、中国工商银行辽宁省分行举办的重点行业稳增长实施方案专题解读会在沈阳举行。会议围绕国家出台的稳增长系列政策， 重点解读汽车、机械、电力装备、电子信息、石化化工、钢铁、轻工等行业政策。全省12家金融机构、21个新型工业化院、30个重点县区、近50户企业、 33个行业协会共300余人参加会议。 会议现场 本次会议邀请了工业和信息化部相关司局及事业单位负责同志，围绕稳增长系列政策，结合辽宁产业结构特点与现实困境，就政策内涵、落实路径、行业 预期及企业纾困等方面进行深度讲解与现场指导。同时深化政银企协同，发挥金融支撑作用，精准把握政策导向，力求为行业、企业提供金融支持。 以汽车行业为例，会议对国家稳增长工作方案中着力扩大国内消费、提升供给质量、优化发展环境、深化国际合作等举措进行深入解读，并结合我省产业 实际提出具体发展建议。与会专家认为，辽宁应统筹优化全省产能，强化整车与零部件企业协同发展，推动整车企业持续上规模、增效益；依托我省科 教、场景、产业、区位及数据资源等优势，加强低温高寒环境下的动力电池、固态电池、自动驾驶等关键技术攻关与示范应用，拓展公交、物流、扫雪等 ...

（文章来源：每日经济新闻） 市场分析认为，石化化工行业正迎来基本面复苏的关键布局期。具体来看，产能周期筑顶叠加碳排放双 控政策推进，供给格局有望优化；行业"反内卷"措施趋于立体，有望提升复苏斜率；海外产能退出与需 求回暖，驱动出口迈向量价齐升；同时，化工新材料受益于新旧动能转换，将持续为行业增长注入弹 性。 中证石化产业指数既覆盖"三桶油"等炼化龙头，也包括万华化学、恒力石化等细分化工领军企业，其 PX-PTA-长丝产业链含量高，直接受益于产品涨价预期与行业估值修复。化工行业ETF易方达 （516570）管理费率仅为0.15%/年，处于全市场ETF中最低水平，为投资者把握行业发展机遇提供了低 成本工具。 2月4日早盘，A股市场走势分化，石油、化工板块涨跌互现。截至10:45，中证石化产业指数上涨 0.3%，成分股中，三棵树、中国石化涨超3%。相关ETF近期受到资金青睐。Wind数据显示，化工行业 ETF易方达（516570）近一周合计资金净流入达11亿元。 上周聚酯产业链价格全面上涨，上游成本端支撑力度增强，对市场情绪形成提振，拉动PX、MEG、 PTA市场持续走高，短纤及瓶片价格也有明显上涨。 ...

Group 1: Market Overview - The market sentiment is currently high, with over 60% of stocks in the CSI 300 index showing an upward trend, indicating a bullish outlook for the near future [2] - The momentum sentiment indicators are trending upwards, suggesting a sustained positive market environment [2] Group 2: Industry Insights - In the coal, steel, float glass, cement, and fuel refining sectors, profit sentiment is expected to decline year-on-year [3] - The inventory of breeding sows is decreasing significantly, leading to a tighter supply forecast for Q2 2026, which may support a recovery in pig prices [3] - The PMI remains stable, indicating no significant changes in the cyclical industries monitored [3] Group 3: Automotive Sector - The performance of new energy vehicles in January was weak, prompting automakers to increase purchase incentives [4] - Recommended stocks include Geely Automobile for whole vehicles and Fuyao Glass for components, alongside Top Group and Shuanglin Co. for humanoid robots [4] Group 4: Real Estate Sector - Multiple cities have initiated old housing buyback programs, accelerating the "old for new" exchange, which is expected to stabilize the housing market [5] - Notable companies recommended include China Merchants Shekou and China Jinmao, which are positioned as leading brands in the real estate sector [5] Group 5: Chemical Industry - Qicai Chemical and Huanliang Technology have established an AI laboratory to enhance product development efficiency, marking a shift from experience-driven to model-driven approaches in the chemical industry [6] - Companies like Sinopec, Wanhua Chemical, and Qicai Chemical are highlighted for their potential in leveraging AI for cost reduction and efficiency improvements [6]

Core Viewpoint - The collaboration between Qicai Chemical and Deepverse aims to establish an AI-driven laboratory to enhance the research and development of high-performance materials, transitioning from traditional trial-and-error methods to data-driven predictive models [4][5]. Group 1: Collaboration Details - Qicai Chemical, a leader in high-performance organic pigments, is expanding into high-end new materials, focusing on complex chemical products like MXD6 nylon and PPDI polyurethane elastomers [5]. - Deepverse leverages materials informatics, artificial intelligence, and high-throughput experimentation to accelerate the development of new materials by integrating cross-domain data [5]. - The partnership aims to create a long-term collaborative research mechanism, enhancing efficiency, quality, and iterative processes in material development [5]. Group 2: Policy and Industry Context - Since the second half of 2025, the Chinese government has been actively promoting the integration of AI in various industries, including chemicals, through a series of policies aimed at enhancing productivity and innovation [6][7]. - The policies emphasize the need for AI to improve quality and efficiency in the petrochemical and new materials sectors, marking a shift towards intelligent transformation as a foundation for high-quality development [6][7]. Group 3: Industry Challenges and Opportunities - The chemical industry is currently navigating a phase of "stabilizing growth" and "anti-involution," facing weak macro demand despite attempts to improve profitability through collaboration [8]. - Companies are encouraged to adopt AI technologies to shorten product development cycles and optimize production processes, which can mitigate cost fluctuations and enhance operational quality [8]. - Firms that successfully implement intelligent transformations are expected to maintain resilience during industry downturns and capitalize on recovery phases [8].

Group 1: Market Overview - The market sentiment is currently high, with over 60% of stocks in the CSI 300 index showing an upward trend, indicating a slight decrease in the proportion of rising stocks compared to the previous month [5] - Momentum indicators suggest a bullish outlook for the near future, with both fast and slow lines trending upwards [5] - The CSI 300 index is currently in a sentiment boom zone, reflecting positive market conditions [5] Group 2: Real Estate Sector - Multiple regions have initiated old housing buyback programs, accelerating the "old for new" strategy, which is expected to stabilize the real estate market [6] - Shanghai's Fengxian district has completed the first batch of registrations for 50 families under the "old for new" program, while Hangzhou's Fuyang district has also launched similar initiatives [6] - The government’s direct purchase of second-hand homes is aimed at promoting sales and reducing inventory, signaling a potential recovery in the housing market [6] Group 3: Automotive Sector - In January, the performance of new energy vehicles was weak, with various automakers increasing purchase incentives [8] - Li Auto's delivery volume decreased by 7.5% year-on-year and 37.5% month-on-month to 27,668 units; NIO's deliveries increased by 96.1% year-on-year but fell by 43.5% month-on-month to 27,182 units; Xpeng's deliveries dropped by 34.1% year-on-year and 46.6% month-on-month to 20,011 units [8] Group 4: Chemical Sector - Qicai Chemical and Huanliang Technology have established an AI laboratory to significantly shorten product development cycles, marking a shift from experience-driven to model-driven approaches in the chemical industry [7] - The implementation of AI in the chemical sector is becoming essential due to national policies and the need to reduce competition [7] Group 5: Company Performance - Zhongxin Fluorine Materials expects to turn a profit in 2025, projecting a net profit of 16-20 million yuan, and plans to raise 186 million yuan for expanding its BPEF projects [8] - Baihehua plans to invest up to 100 million yuan in a project to produce 1,000 tons of PEEK materials annually, capitalizing on the growing market for high-end applications [8] - Great Wall Motors reported a 10.2% increase in revenue to 222.79 billion yuan for 2025, but net profit fell by 21.7% to 9.91 billion yuan, indicating pressure on profitability [9]

Investment Rating - The report maintains an "Overweight" rating for the basic chemical industry, indicating a projected investment return exceeding the market benchmark index by 5% to 15% over the next 6-12 months [5]. Core Insights - The collaboration between Qicai Chemical and Deepverse to establish an AI laboratory aims to enhance the R&D capabilities in high-performance materials, transitioning from traditional trial-and-error methods to data-driven predictive models [2][4]. - National policies are increasingly promoting the integration of AI in the chemical industry, with specific guidelines aimed at enhancing efficiency and innovation in both the petrochemical and new materials sectors [3]. - The current economic environment emphasizes the need for chemical companies to leverage AI technologies to improve operational efficiency and reduce costs, thereby enhancing resilience during periods of low industry demand [4]. Summary by Sections AI Collaboration - Qicai Chemical and Deepverse have signed an agreement to jointly build an AI laboratory, focusing on high-performance materials R&D [1]. - The partnership aims to create a long-term collaborative R&D mechanism, utilizing AI to enhance efficiency and quality in material development [2]. Policy Support - Since the second half of 2025, the government has introduced multiple policies to facilitate the implementation of AI in the chemical sector, with a vision for widespread adoption by 2030 [3]. - The policies emphasize the need for adaptive optimization in petrochemical processes and deeper integration of AI in new materials R&D [3]. Industry Dynamics - The chemical industry is currently navigating a phase of "stabilizing growth" and "anti-involution," necessitating the adoption of AI to strengthen internal capabilities [4]. - Companies that successfully implement AI-driven transformations are expected to maintain stronger operational resilience and capitalize on recovery phases in the market [4]. Investment Recommendations - The report suggests focusing on leading companies that can leverage data for cost reduction and efficiency gains, such as China National Petroleum, Sinopec, and Wanhua Chemical [5]. - It also highlights the potential of Qicai Chemical in the AI domain and its implications for sectors like semiconductors and fine chemicals [5].