浙商证券此次大幅提额，其底气或来自两融业务的稳健增长。该券商2025年半年报显示，报告期末公司 两融余额为237.85亿元，较上一年同期增长32.60%；两融业务规模市场份额提升至1.29%，公司有负债 的两融客户平均维持担保比例280.87%，两融业务整体风险可控。 浙商证券在半年报中提及，上半年公司持续加强信用业务人才队伍建设，拓展融资融券客户来源渠道； 深化存量客户精细化运营，提升客户活跃度；优化业务流程与服务体验，有效提升客户综合满意度。 事实上，浙商证券并非个例，今年以来已有多家券商宣布上调信用业务总规模。华林证券在年内已两次 上调信用业务总规模上限，3月末提升至62亿元，9月初再次提升至80亿元。此外，兴业证券董事会也在 4月末审议通过了《关于调整公司信用业务总规模上限的议案》，虽未披露具体数字，但业务扩张动向 明确。 此次浙商证券"提额"，距上一案例仅相隔半月。就在9月初，华林证券刚将信用业务总规模上限提升至 80亿元。券商接连为两融业务扩容"增弹"，既传递出对后市景气度的信心，也意味着行业新一轮围绕资 本实力与风控能力的竞争拉开帷幕。 多家券商上调两融规模限额 两融余额连创历史新高之际，券商争 ...

Core Insights - The overall performance of Shenzhen state-owned enterprises' new media accounts has declined in August, with significant drops in both article output and reading volume compared to July [2][20] - The "Shenzhen State-owned Enterprises New Media Information Release Observation List" evaluates 54 accounts, including 31 primary accounts of state-owned enterprises and 23 listed companies [1][20] Group 1: New Media Performance - In August, 21 out of 31 primary accounts saw a decrease in article output, with notable reductions from Shenzhen Stock Exchange, Shenzhen Anju, and others [2][3] - Reading volume for 21 accounts also declined, with some experiencing drops of over 50%, while the Special Zone Construction Group saw a significant increase of 16,610 in reading volume [2][3] - The top three accounts by article output were Shenzhen Bus Group (71 articles), Shenzhen Energy (64 articles), and Shenzhen Metro (63 articles, with a slight increase of 1 article) [3][4] Group 2: Reading Volume and Engagement - The top three accounts by reading volume were Shenzhen Metro (361,000+), Guoxin Securities (135,000+), and Shenzhen Eastern Bus (133,000+), while some accounts had reading volumes below 1,000 [4][5] - The total number of likes was highest for Shenzhen Metro (4,079), followed by Shenzhen Bus Group (2,881) and Shenzhen Gas (1,957) [6][7] - Recommendation volume was led by Shenzhen Bus Group (1,882), Shenzhen Metro (1,252), and Shenzhen Eastern Bus (513), indicating a positive reception of their content [8][9] Group 3: Listed Companies Performance - Among the 23 listed company accounts, 14 experienced declines in reading volume and article output, indicating instability in content planning [11][20] - Shenzhen Airlines, CIMC, and China Ping An led in reading volume with 110,000+, 50,913, and 43,212 respectively, but many accounts saw significant drops [14][15] - The article output for Shenzhen Airlines was 24, while CIMC maintained a steady output, benefiting from a recent event that boosted its reading volume [14][19] Group 4: Overall Trends and Recommendations - The overall data from August indicates a disparity in performance, with top accounts maintaining strong output and engagement, while lower-tier accounts struggle [20] - Recommendations for improvement include data review, strategy adjustments, content quality enhancement, and better rhythm control to foster a more balanced development across all accounts [20]

深圳首家企业通过"绿色通道"快速登陆新三板。 近日，深圳星网信通科技股份有限公司（简称"星网信通"）正式获得全国中小企业股份转让系统（简 称"新三板"）《同意挂牌函》。 记者了解到，星网信通是深圳前海股权交易中心（简称"深圳股交"）"专精特新"专板培育的企业，也是 深圳市首家成功通过区域性股权市场"绿色通道"机制登陆新三板的企业。 据深圳股交披露，星网信通实际审核时间仅用时21个交易日，较传统路径效率提升约50%，"相较于正 常申报方式，'绿色通道'机制咨询响应快、材料受理快、问询反馈快，挂牌申报效率显著提升。" 公开信息显示，此次登陆新三板的星网信通是一家智慧融合通信综合解决方案提供商，主要面向金融机 构、党政机关及大型企事业单位客户，在融合指挥、智能客服、企业统一通信和ICT基础设施等领域提 供信息与通信综合解决方案。 那么，通过股交绿通去新三板的流程是怎样的？ 据深圳股交介绍，企业在全国股转系统挂牌需经历多个流程：首先提前2周提交书面咨询材料，全国股 转公司审核机构在5个交易日内答复后，企业结合答复修改挂牌申请文件并申报挂牌；申报后2个交易日 内会被受理，随后在5个交易日内进行首轮问询，企业需在10个交 ...

力星股份今日上涨7.05%，全天换手率38.69%，成交额17.65亿元，振幅10.77%。龙虎榜数据显示，机构 净买入1.13亿元，营业部席位合计净卖出1.05亿元。 深交所公开信息显示，当日该股因日换手率达38.69%上榜，机构专用席位净买入1.13亿元。 证券时报·数据宝统计显示，上榜的前五大买卖营业部合计成交5.18亿元，其中，买入成交额为2.63亿 元，卖出成交额为2.55亿元，合计净买入794.70万元。 具体来看，今日上榜的营业部中，共有4家机构专用席位现身，即买一、买二、买三、买四、卖二、卖 三，合计买入金额2.32亿元，卖出金额1.19亿元，合计净买入1.13亿元。 资金流向方面，今日该股主力资金净流出1.66亿元，其中，特大单净流出9081.09万元，大单资金净流出 7508.63万元。近5日主力资金净流入3923.46万元。（数据宝） 力星股份9月25日交易公开信息 | 买/卖 | 会员营业部名称 | 买入金额（万元） | 卖出金额（万元） | | --- | --- | --- | --- | | 买一 | 机构专用 | 7746.60 | 4579.25 | | 买二 | 机构专用 ...

Core Points - The Shenzhen State-Owned Enterprises Shareholder Return Index (470064) closed at 2208.54 points, down 0.26% with a trading volume of 29.484 billion yuan and a turnover rate of 1.28% [1] - Among the index constituents, 13 stocks rose while 37 stocks fell, with Tongling Nonferrous Metals leading the gainers at an 8.12% increase and Shanjin International leading the decliners at a 2.71% decrease [1] Index Constituents Summary - The top ten constituents of the Shenzhen State-Owned Enterprises Shareholder Return Index are as follows: - BOE Technology Group (sz000725) with a weight of 9.90%, latest price at 4.17 yuan, down 0.95%, total market value of 156.016 billion yuan [1] - Wuliangye Yibin (sz000858) with a weight of 8.57%, latest price at 121.52 yuan, down 0.69%, total market value of 471.693 billion yuan [1] - Hikvision (sz002415) with a weight of 7.86%, latest price at 31.24 yuan, up 0.87%, total market value of 286.311 billion yuan [1] - Luzhou Laojiao (sz000568) with a weight of 6.86%, latest price at 129.46 yuan, down 1.86%, total market value of 190.559 billion yuan [1] - XCMG Machinery (sz000425) with a weight of 5.27%, latest price at 10.36 yuan, down 1.71%, total market value of 121.761 billion yuan [1] - Changan Automobile (sz000625) with a weight of 4.02%, latest price at 12.08 yuan, down 0.74%, total market value of 119.762 billion yuan [1] - Shenwan Hongyuan (sz000166) with a weight of 3.91%, latest price at 5.17 yuan, down 0.58%, total market value of 129.457 billion yuan [1] - Yanghe Brewery (sz002304) with a weight of 3.59%, latest price at 68.35 yuan, down 1.10%, total market value of 102.966 billion yuan [1] - Guosen Securities (sz002736) with a weight of 3.30%, latest price at 13.25 yuan, down 0.23%, total market value of 135.703 billion yuan [1] - Yunnan Aluminum (sz000807) with a weight of 3.28%, latest price at 19.41 yuan, up 0.31%, total market value of 67.313 billion yuan [1] Capital Flow Analysis - The index constituents experienced a net outflow of 1.399 billion yuan from institutional investors, while retail investors saw a net inflow of 1.023 billion yuan [1] - The detailed capital flow for selected stocks includes: - Hualing Steel (000932) with a net inflow of 95.616 million yuan from institutional investors [2] - HeSteel (000709) with a net inflow of 29.287 million yuan from institutional investors [2] - XCMG Machinery (000425) with a net inflow of 12.895 million yuan from institutional investors and a net inflow of 14.169 million yuan from speculative funds [2]

Core Insights - The report emphasizes the need for a multi-dimensional, AI-driven framework to effectively predict and manage risks associated with short-term market surges, particularly in the context of the A-share market [2][3] - It introduces a comprehensive multi-factor system based on four core dimensions: trend, momentum, capital flow, and valuation, which collectively enhance market state characterization [2][4] - The AI-enhanced multi-factor timing strategy is expected to provide investors with an objective risk warning tool, reducing losses from blind chasing of high prices [3][4] Trend Analysis - The report illustrates that traditional indicators often fail to provide timely warnings for rapid market fluctuations driven by emotions rather than fundamentals [2][6] - The analysis of the "9·24" market surge shows that moving averages indicated a bullish trend before the surge, while subsequent signals indicated a weakening momentum [5][6][8] Momentum Indicators - The report highlights that extreme values in momentum indicators like KDJ and RSI often signal the end of a price surge, as seen during the "9·24" event where both indicators reached overbought levels [8][9] - The KDJ and RSI thresholds serve as critical points for identifying market cycles, aiding investors in timing their trades effectively [9] Capital Flow Insights - The report notes a strong correlation between trading volume and price movements during the "9·24" surge, indicating that volume often precedes price increases [11][12] - A decline in trading volume following price peaks serves as a warning signal for potential market corrections, as evidenced in the analysis [12] Valuation Metrics - The report discusses how valuation metrics, such as PE ratios, can indicate market risk accumulation, particularly when they exceed historical high thresholds [15][16] - The combination of high valuation levels and overbought momentum indicators has historically signaled market tops and subsequent corrections [15] AI-Driven Quantitative Strategy - The report outlines a comprehensive AI-driven quantitative strategy that automates the process of factor selection, modeling, and execution, enhancing the robustness of trading signals [19][20] - The strategy employs a closed-loop system that continuously optimizes itself based on real-time performance feedback, ensuring adaptability to changing market conditions [19][20] Factor Processing and Model Selection - The report emphasizes the importance of factor processing, including standardization and ranking, to ensure comparability and robustness of the indicators used in the model [30][33] - The HistGradientBoosting model is selected for its ability to capture non-linear relationships among factors, providing a more accurate timing signal for trades [39][40] Performance Evaluation - Backtesting results indicate that the AI-driven strategy significantly outperforms the market benchmark, achieving an annualized return of approximately 36.41% with a Sharpe ratio of 2.30 [41][42] - The strategy demonstrates strong risk management capabilities, maintaining a maximum drawdown of -19.51%, which is notably lower than the benchmark during volatile periods [45][46]

证券研究报告 | 2025年09月25日 AI 赋能资产配置（十七） AI 盯盘： "9·24"行情案例 策略研究·策略解读 | 证券分析师： | 王开 | 021-60933132 | wangkai8@guosen.com.cn | 执证编码：S0980521030001 | | --- | --- | --- | --- | --- | | 证券分析师： | 陈凯畅 | 021-60375429 | chenkaichang@guosen.com.cn | 执证编码：S0980523090002 | 事项： 金融市场中的短期内快速上涨行情往往因情绪驱动而非基本面改善，容易导致阶段性追高。传统技术分析 （如 KDJ、RSI、MACD、均线体系、成交量、换手率及估值水平等单一指标）虽能提供部分洞察，但其 信号纷杂、滞后性强且受主观经验影响较大，难以有效预警此类脉冲式行情的风险。 为系统性地解决这一问题，本研究旨在构建一个多维度、量化、由人工智能驱动的综合研判框架。研究首 先从趋势、动量、资金流向、估值四个核心维度出发，构建了十二个关键原始指标，形成一个全面刻画市 场状态的多因子体系，并初步判断和市场趋势的关 ...

Group 1 - The Shanghai Stock Exchange's Sci-Tech Innovation Board semiconductor materials and equipment index fell by 1.62% as of September 25, 2025, with mixed performance among constituent stocks [1] - The Sci-Tech Semiconductor ETF (588170) decreased by 1.75%, with the latest price at 1.46 yuan, while its trading volume was active with a turnover of 18.85% and a total transaction value of 267 million yuan [1] - The latest scale of the Sci-Tech Semiconductor ETF reached a new high of 1.43 billion yuan, with the number of shares also hitting a record of 967 million [1] Group 2 - According to data from SEMI, global silicon wafer shipments in Q2 2025 reached 3.327 billion square inches, marking four consecutive quarters of year-on-year growth and the highest level since Q3 2023 [2] - The semiconductor equipment and materials industry is a key area for domestic substitution, benefiting from the expansion of semiconductor demand driven by the AI revolution and advancements in lithography technology [2] - The Sci-Tech Semiconductor ETF (588170) and its linked funds focus on semiconductor equipment (59%) and materials (25%), indicating a strong emphasis on the upstream semiconductor sector [2]

Core Insights - The report from Guosen Securities highlights the increasing power of data centers and the role of liquid cooling solutions in addressing high energy consumption and heat dissipation challenges [1][2] Group 1: Industry Overview - The liquid cooling sector is in its early development stage, with various solutions having distinct advantages and disadvantages, and no established optimal solution yet [1] - According to SemiAnalysis, the global installed capacity of AI data centers is expected to reach 59 GW by 2028, potentially generating a demand for approximately 89,000 tons of cooling liquid [1] - Traditional server installations are projected to contribute an additional demand of 19,000 tons of cooling liquid [1] Group 2: Energy Consumption and Efficiency - By 2024, the total electricity consumption of computing centers in China is expected to reach 166 billion kWh, accounting for 1.68% of the total electricity consumption in society [2] - The average Power Usage Effectiveness (PUE) for ultra-large data centers in China is currently 1.46, while for large data centers, it is 1.55 [2] - New standards set by the Ministry of Finance, Ministry of Ecology and Environment, and Ministry of Industry and Information Technology require that the energy ratio of data centers not exceed 1.4 starting June 2023, and 1.3 by 2025 [2] Group 3: Liquid Cooling Technologies - The main liquid cooling technologies include cold plate and immersion cooling, with cold plate cooling being the most widely used due to its mature technology [3] - Liquid cooling offers multiple advantages such as high heat exchange efficiency, energy savings, and reduced noise [3] - Cold plate cooling is categorized into indirect and direct cooling, with indirect cooling typically being cold plate and direct cooling including immersion and spray cooling [3] Group 4: Cooling Liquid Types and Applications - Different types of cooling liquids are suited for various applications, with water-based cooling liquids used in single-phase cold plate cooling and refrigerants used in dual-phase systems [3] - Oil-based and fluorinated cooling liquids can be used in both single-phase and multi-phase immersion cooling [3] - Water-based cooling liquids are cost-effective but may promote algae and bacteria growth, while oil-based liquids have good insulation but higher viscosity [3] - Fluorinated cooling liquids, including perfluoropolyether and perfluoroamines, offer good flow properties and low toxicity but are relatively expensive [3]

2、在暂停本基金大额申购及定期定额投资业务期间，本基金单日单个基金账户累计金额1000元（含 1000元）以下的申购及定期定额投资业务以及赎回等业务正常办理。 公告送出日期：2025年09月25日 1.公告基本信息 ■ 2.其他需要提示的事项 1、本基金管理人决定自2025年09月26日起暂停接受单个基金账户对本基金日累计金额超过1000元（不 含1000元）的申购及定期定额投资业务申请，如单个基金账户日累计申请金额超过1000元，则本基金管 理人有权拒绝。 3、关于恢复本基金大额申购及定期定额投资业务的时间，基金管理人将另行公告。 4、投资者可以登录富国基金管理有限公司网站www.fullgoal.com.cn或拨打富国基金管理有限公司客户 服务热线95105686、4008880688（全国统一，均免长途费）进行相关咨询。 2025年09月25日 关于新增国信证券股份有限公司为富国沪深300交易型开放式指数证券投资基金流动性服务商的公告 为促进富国沪深300交易型开放式指数证券投资基金的市场流动性和平稳运行，根据《深圳证券交易所 证券投资基金业务指引第2号一一流动性服务》等有关规定，自2025年9月25日 ...