2月25日，A股三大指数全天高开高走，呈现单边上涨态势，截止收盘，上证综指上涨29.82点，涨幅 0.72%报4147.23点；深证成指上涨184.3点，涨幅1.29%报14475.87点；沪深300指数上涨28.34点，涨幅 0.6%报4735.89点；创业板指数上涨46.55点，涨幅1.41%报3354.82点；科创50指数上涨7.91点，涨幅 0.54%报1473.28点；全市场成交额2.48万亿元，较前一交易日增量2627亿元，超3700股上涨，其中101 只个股涨停，连续两日超百股涨停。 盘面上，涨价题材股全线爆发，小金属、有色金属（核心股）板块爆发，中钨高新、东方钽业等多股涨 停；锂矿概念拉升，大中矿业涨停；半导体（核心股）板块走高，和林微纳20CM涨停；磷化工（核心 股）、房地产服务、稀土永磁及钢铁等板块涨幅居前，澄星股份、六国化工、和邦生物2连板，中色股 份、包钢股份涨停。另外，影视传媒板块持续下挫，横店影视等多股跌停；CPO概念走低，罗博特科领 跌；AI应用股走弱，开普云跌近15%；通信服务、东数西算及培育钻石等板块跌幅居前。 资源股成核心领涨主线 受现货价格普涨刺激，稀土永磁（核心股）概念 ...

| 中微公司 | 5.99 | 5.57亿元 | 电子 | | --- | --- | --- | --- | | 杉杉股份 | 9.96 | 5.09亿元 | 电力设备 | | 华友钻业 | 5.88 | 4.83亿元 | 有色金属 | | 云南错业 | 10.01 | 4.68亿元 | 有色金属 | | 金风科技 | 4.64 | 4.68亿元 | 电力设备 | | 紫金矿业 | 1.14 | 4.24亿元 | 有色金属 | | 有研新材 | 10 | 4.12亿元 | 电子 | | 中钨高新 | 10 | 4.11亿元 | 有色金属 | | 拓荆科技 | 10.72 | 4.08亿元 | 电子 | *数据仅供参考，不构成投资建议 据交易所数据显示，截至2月25日午后一小时，主力资金流入前20的股票分别为： 北方稀土（30.50亿元）、 胜宏科技（17.73亿元）、 包钢股份（17.03亿 元）、 航天发展（14.72亿元）、 工业富联（13.75亿元）、 沪电股份（9.39亿元）、 菲利华（7.25亿元）、 新易盛（6.84亿元）、 神剑股份（6.76亿元）、 盛和资源（5.97亿元）、 中国稀土（5. ...

声明：市场有风险，投资需谨慎。本文为AI大模型基于第三方数据库自动发布，任何在本文出现的信 息（包括但不限于个股、评论、预测、图表、指标、理论、任何形式的表述等）均只作为参考，不构成 个人投资建议。受限于第三方数据库质量等问题，我们无法对数据的真实性及完整性进行分辨或核验， 因此本文内容可能出现不准确、不完整、误导性的内容或信息，具体以公司公告为准。如有疑问，请联 系biz@staff.sina.com.cn。 责任编辑：小浪快报 根据喜娜AI异动分析，中钨高新涨停原因可能如下，PCB刀具扩产+钨资源增储+产业链整合： 1、中钨 高新近期动作频繁，整体呈中性偏利好态势。公司新增1.3亿支微钻和3000万支PCB钻针产能，PCB刀 具总产能将从当前0.3亿支提升至1.6亿支/年，巩固了细分领域龙头地位。同时，柿竹园新增钨金属量 9.17万吨，使钨金属量增幅达23%，延长矿山服务年限15 - 20年，增强了资源储备。 2、公司以8.2亿元 现金完成远景钨业收购，完善了上游资源布局，且该交易获99.66%高票通过。此外，建设西南研发中 心解决了研发分散问题，增强了创新能力，还获得了100亿元融资额度，保障了项目资金 ...

关于我们 联系方式 网站声明 用户反馈 2026.02.23 17:51 晕期一 【盘面回顾与展望】 节前指数低开低走震荡回落，短线情绪同步走弱算是一个比较明显的冰点，除去ST之外只有一只2连板个股，上一次出现这 种情况都要追溯到924行情之前了,节后有反弹需求。节假日期间消息面偏正面,尤其是关税裁决,虽然有新关税但平均关税 水平还是比之前低。同时在港股及富时A50期指的刺激下明天高开几乎板上钉钉，虽然高开之后会有兑现但因为节前的冰点所 以兑现强度不会太高，资金做出有效承接之后有望持续走强。板块方面节假日期间发酵最厉害的还是AI，今天港股智谱、Mini Max等热门股的大幅调整是好事，由于A股没有特别出彩的大模型公司所以依然关注算力方向为主，留意大位科技的反馈。当 然如果要带动市场整体走强的话依然主要依赖算力硬件为首的科技权重，核心还是CPO，Lumentum和Coherent均迎来大 涨，至于OpenAl缩减资本开支是一个数字的误读所以影响不大。除了Al之外需要大宗商品也有所发酵，受多种因素刺激国际 油价、金价、银价等同步拉升，涨价品种在节前经历连续两日的调整之后有回流预期，依旧关注景气度品种为主，如钨、 ...

【天风建筑建材 & 新材料】周观点 20260223 节前1-2周涨幅较好的主线为：①AI 算力相关电子材料主线，以特种电子布为核心的玻纤领涨建材板块；PCB 基材、半导体封装材料、液冷相关标的领涨新材料板块；②AI + 建筑主线，VR/AR 应用、算力 + 工程咨询设计相 关标的领涨建筑板块；③外围市场 PCB 核心基材、半导体设备/材料主线领涨。 下周重点关注： 1、科技主线持续回归，核心推荐【电子布】赛道：①供需格局持续失衡，行业整体供需缺口约 20%，26 年 1 月 起全品类电子布均出现供应紧张，企业在手订单已达 2 个月水平，预计26 年全年将维持供应偏紧格局；②产能供 给刚性收缩，普通电子布产能向高端转移带来60% 产能损失，全品类供给持续收缩；③涨价节奏加快、弹性充 足，25 年电子布行业普遍提价 4-5 次，26 年 已提价10%，高端 DK 布、Q 布、CTE布价格仍处上行通道；④扩产 瓶颈短期无法突破，高端产品生产依赖的丰田高端织布机交付周期长达 1-2 年，但需关注池窑法突破（单个池窑 年产3000吨VS坩埚36吨）带来的供应增加（29年有可能供过于求）；⑤库存与需求端共振，CCL及电 ...

Key Insights - The global AI industry is advancing through a collaborative push in computing power, models, and applications, laying a foundation for the scaling of AI video generation technology and the practical deployment of humanoid robots [2][3] - Major AI companies are announcing substantial long-term capital expenditure plans, with OpenAI projecting around $600 billion in computing power spending by 2030, indicating a significant commitment to infrastructure development [3][4] - The recent launch of Seedance 2.0 at the Spring Festival Gala demonstrates the potential of domestic AI models in cultural content creation, marking a significant step towards industrialization in the video generation sector [5][6] Computing Power and Infrastructure - There is a notable acceleration in global AI capital expenditures, with OpenAI initiating a financing round potentially exceeding $100 billion to support its computing power goals [3][4] - In India, Google announced a $15 billion investment in infrastructure, while OpenAI collaborates with Tata to build a 1000 MW data center, showcasing the global expansion of computing resources [3] - Domestic AI companies, such as Moonlight Dark Side, have secured over $1.2 billion in financing, reflecting strong market confidence in Chinese AI enterprises [4] Model Technology - Recent advancements in model technology include the transition to multimodal architectures and cost-effective intelligent models, enhancing performance while restructuring cost frameworks [4][5] - Alibaba's release of the Qwen3.5-Plus model marks a significant upgrade, shifting from pure text training to native multimodal unified modeling, improving performance in long text and multimodal reasoning scenarios [5] - The competitive landscape is shifting from parameter scale competition to architecture efficiency optimization, as demonstrated by Anthropic's Claude Sonnet 4.6 achieving flagship model performance at a lower price point [5] Application Layer - The application of AI in real-world scenarios is advancing, as evidenced by the successful integration of AI video generation technology in the Spring Festival Gala, validating the industrial potential of domestic models [5][6] - Humanoid robots are transitioning from demonstration phases to real-world task execution, with platforms like Volcano Engine and Doubao participating in the Gala, showcasing their capabilities [5] - The AI application landscape is moving towards commercial validation, with content generation and physical execution paths entering a critical phase of market readiness [6] Industry Trends - The AI industry is expected to maintain its upward trajectory, with favorable market conditions supporting a second phase of spring market activity [6] - The successful application of AI during the Spring Festival Gala may act as a catalyst for the current market rally, reinforcing the importance of practical AI applications [6]

Group 1 - Tungsten prices have surged significantly since the beginning of the year, with black tungsten concentrate (≥65%) averaging 696,000 yuan/ton, reflecting a year-to-date increase of approximately 51.6% [3] - The rapid price increase is attributed to supply constraints in the mining sector and increased demand for inventory replenishment from downstream industries, exacerbated by strict crackdowns on illegal mining [2][8] - Major tungsten companies, including Xiamen Tungsten (600549.SH), Zhongtung High-tech (000657.SZ), and Xianglu Tungsten (002842.SZ), have issued multiple price increase notices this year [2][6] Group 2 - The tightening supply of tungsten has led to a situation where some downstream companies are struggling to cope with high prices, resulting in a "no rice to cook" scenario [7] - The crackdown on illegal mining has reduced the market supply of raw materials by approximately one-third to one-fourth, impacting the overall availability of tungsten [7][9] - The current supply-demand imbalance raises questions about whether the rapid price increase is a temporary phenomenon or indicative of a longer-term structural bull market [2][15] Group 3 - The transmission of price increases from the tungsten mining sector to downstream industries is generally smooth but may weaken over time, particularly affecting lower-end processing sectors [11][12] - High-end tungsten products, such as hard alloys and cutting tools, are experiencing increased demand, with lead times for orders extending from over a month to 2-3 months [14] - The cost of tungsten raw materials constitutes a small portion of the overall production costs for tools, which limits the impact of price increases on end-user pricing [14] Group 4 - The long-term outlook for tungsten prices remains strong due to ongoing supply constraints and increasing demand from traditional industries and emerging sectors [15][16] - Analysts suggest that while there may be short-term price adjustments, the overall trend is expected to maintain a high price level due to limited new mining capacity and stringent domestic regulations [15][16] - The market sentiment has become extreme due to the rapid price increases, indicating potential for a correction in the near future [17]

Core Viewpoint - The tungsten price has surged significantly since the beginning of the year, driven by supply constraints and increased demand from downstream industries, leading to a "jumping price mode" in the market [1][2]. Supply and Demand Dynamics - As of February 12, the average price of black tungsten concentrate (≥65%) reached 696,000 yuan per ton, reflecting a year-to-date increase of approximately 51.6% [2]. - The domestic supply of tungsten has decreased by about one-third to one-fourth due to intensified crackdowns on illegal mining activities, which has contributed to the current price surge [5][6]. - The actual annual supply of tungsten ore in China is estimated to be around 120,000 to 130,000 tons, with about 20% of this supply being unregulated and thus not circulating in the market [6][7]. Impact on Downstream Industries - The rapid price increase has led to a trust crisis in the spot market, with some downstream companies facing difficulties in fulfilling contracts due to soaring prices [4][9]. - Major tungsten companies, including Xiamen Tungsten (600549.SH) and Zhongtung High-tech (000657.SZ), have issued multiple price increase notifications this year, reflecting the upward pressure on prices [1][5]. - The cost of tungsten in the manufacturing of tools is relatively low, accounting for about 10%-15% of the total cost, which may limit the impact of price increases on end products [12]. Market Sentiment and Future Outlook - Industry experts express mixed sentiments about the sustainability of the current price levels, with some predicting potential adjustments in the near future due to extreme market emotions [14][15]. - The ongoing supply constraints, coupled with the increasing demand from traditional and emerging sectors, suggest that tungsten prices may remain elevated in the medium to long term [13][14]. - The tightening of mining quotas and the limited new production capacity are expected to keep the supply-demand imbalance unresolved in the short term [13][14].

Quantitative Models and Construction Methods 1. Model Name: 250-Day New High Distance Model - **Model Construction Idea**: This model tracks the distance of stock prices or indices from their 250-day high to identify market trends and hotspots. It is based on the momentum and trend-following strategy, which has been proven effective in various studies[11][18]. - **Model Construction Process**: The 250-day new high distance is calculated as follows: $ 250\text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ Where: - $ Close_t $ is the latest closing price - $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days If the latest closing price reaches a new high, the distance is 0. If the price falls from the high, the distance is a positive value, representing the degree of decline[11]. - **Model Evaluation**: The model effectively identifies stocks and indices with strong momentum and highlights market leaders, aligning with the principles of momentum investing[11][18]. 2. Model Name: Stable New High Stock Selection Model - **Model Construction Idea**: This model focuses on selecting stocks that exhibit stable price paths and consistent momentum, as smoother price trajectories tend to yield stronger momentum effects[24]. - **Model Construction Process**: Stocks are filtered from the pool of those that hit a 250-day high in the past 20 trading days. The selection criteria include: - Analyst attention: At least 5 buy or overweight ratings in the past 3 months - Relative strength: Top 20% in 250-day price performance - Price stability: Evaluated using the following metrics: - Absolute value of price changes over the past 120 days - Sum of absolute daily price changes over the past 120 days - Momentum continuity: - Average 250-day new high distance over the past 120 days - Average 250-day new high distance over the past 5 days The top 50 stocks based on these criteria are selected[24][26]. - **Model Evaluation**: The model emphasizes smooth price trajectories and consistent momentum, which are less likely to attract excessive attention, thereby enhancing the momentum effect[24]. --- Model Backtesting Results 1. 250-Day New High Distance Model - **Indices' 250-Day New High Distance (as of February 13, 2026)**: - Shanghai Composite Index: 2.00% - Shenzhen Component Index: 2.35% - CSI 300: 2.72% - CSI 500: 3.51% - CSI 1000: 3.14% - CSI 2000: 2.54% - ChiNext Index: 3.32% - STAR 50 Index: 5.50%[12][13]. 2. Stable New High Stock Selection Model - **Selected Stocks**: 50 stocks were identified, including Zhongtung High-tech, Dike Co., and Xiechuang Data. - **Sector Distribution**: - Technology: 21 stocks (most from the electronics industry) - Manufacturing: 16 stocks (most from the machinery industry)[27][32]. --- Quantitative Factors and Construction Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the relative position of a stock's price to its 250-day high, capturing momentum and trend-following characteristics[11]. - **Factor Construction Process**: $ 250\text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ Where: - $ Close_t $ is the latest closing price - $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days[11]. - **Factor Evaluation**: The factor effectively identifies stocks with strong momentum and aligns with established momentum strategies[11][18]. 2. Factor Name: Price Stability - **Factor Construction Idea**: Evaluates the smoothness of a stock's price trajectory, as smoother paths are associated with stronger momentum effects[24]. - **Factor Construction Process**: - Absolute value of price changes over the past 120 days - Sum of absolute daily price changes over the past 120 days[24]. - **Factor Evaluation**: The factor highlights stocks with stable price movements, which are less likely to attract excessive attention, enhancing the momentum effect[24]. --- Factor Backtesting Results 1. 250-Day New High Distance Factor - **Indices' 250-Day New High Distance (as of February 13, 2026)**: - Shanghai Composite Index: 2.00% - Shenzhen Component Index: 2.35% - CSI 300: 2.72% - CSI 500: 3.51% - CSI 1000: 3.14% - CSI 2000: 2.54% - ChiNext Index: 3.32% - STAR 50 Index: 5.50%[12][13]. 2. Price Stability Factor - **Selected Stocks**: 50 stocks were identified, including Zhongtung High-tech, Dike Co., and Xiechuang Data. - **Sector Distribution**: - Technology: 21 stocks (most from the electronics industry) - Manufacturing: 16 stocks (most from the machinery industry)[27][32].

- The report introduces a quantitative model called "250-day new high distance" to track market trends and identify market hotspots. The model is based on momentum and trend-following strategies, emphasizing the effectiveness of stocks reaching new highs as market indicators. The formula for calculating the 250-day new high distance is: $ 250\text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ where $ Close_t $ represents the latest closing price, and $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days. If the latest closing price reaches a new high, the distance is 0; otherwise, it is a positive value indicating the degree of fallback from the new high[11][12][13] - The report evaluates the model positively, citing its ability to capture market trends and identify leading stocks that perform well during market uptrends. It references studies by [George@2004], William O'Neil, and Mark Minervini, which support the idea that stocks near their 52-week highs tend to outperform those far from their highs[11][18][21] - The report provides backtesting results for the 250-day new high distance model. As of February 13, 2026, major indices such as the Shanghai Composite Index, Shenzhen Component Index, CSI 300, CSI 500, CSI 1000, CSI 2000, ChiNext Index, and STAR 50 Index have respective 250-day new high distances of 2.00%, 2.35%, 2.72%, 3.51%, 3.14%, 2.54%, 3.32%, and 5.50%[12][31] - The report introduces a quantitative factor called "Stable New High Stocks" to identify stocks with smooth price paths and consistent momentum. The factor construction involves screening stocks that have reached a 250-day new high in the past 20 trading days and applying criteria such as analyst attention (at least five buy or overweight ratings in the past three months), relative price strength (top 20% in 250-day returns), price path smoothness (measured by price displacement ratio), and sustained new high performance (average 250-day new high distance over the past 120 days and past 5 days)[24][26][27] - The report evaluates the factor positively, citing research by [Turan G Bali, Nusret et al@2011] and [Da, Gurun et al@2012], which highlight the superior performance of stocks with smooth price paths and strong momentum. The factor is designed to capture these characteristics effectively[24][26][27] - Backtesting results for the "Stable New High Stocks" factor show that 50 stocks were selected based on the criteria, with the highest representation in the technology and manufacturing sectors. Specifically, 21 stocks from the technology sector (dominated by the electronics industry) and 16 stocks from the manufacturing sector (dominated by the machinery industry) were included[27][32][30]