Quantitative Models and Factors Summary Quantitative Models and Construction Methods Model Name: Liquidity Factor - **Construction Idea**: The liquidity factor is based on the market's liquidity conditions and the effectiveness of the main fund factor[12] - **Construction Process**: The model selects industries such as computers, electronics, machinery, electrical equipment and new energy, communications, and automobiles based on the liquidity factor. The recommended weight for the main fund factor is 5%[12] - **Evaluation**: The effectiveness of the main fund factor has stopped declining and is beginning to recover as market liquidity becomes abundant again[11][12] Model Name: Long-term Prosperity Expectation - **Construction Idea**: This factor serves as a proxy variable for prosperity investment[16] - **Construction Process**: The model selects industries such as non-bank finance, non-ferrous metals, electric power and utilities, steel, home appliances, and electronics. The recommended weight is 10%[16] - **Evaluation**: The effectiveness of this factor has recently declined, and the clustering effect has not formed[16] Model Name: Short-term Prosperity Expectation - **Construction Idea**: This factor focuses on short-term prosperity expectations, particularly in domestic demand[20] - **Construction Process**: The model selects industries such as home appliances, basic chemicals, agriculture, forestry, animal husbandry, and fishery, automobiles, machinery, and national defense. The recommended weight is 30%[20] - **Evaluation**: The short-term prosperity expectation factor shows significant upward movement in excess returns[20] Model Name: Momentum Reversal - **Construction Idea**: This factor focuses on long-term low and short-term strong defensive sectors[23] - **Construction Process**: The model tracks one-month momentum and selects industries such as electric power and utilities, agriculture, forestry, animal husbandry, and fishery, retail, banking, real estate, and transportation. The recommended weight is 10%[23] - **Evaluation**: The model suggests tracking defensive sectors with long-term low and short-term strong performance[23] Model Backtesting Results - **Liquidity Factor**: Excess return of the long position is shown in the chart[14] - **Long-term Prosperity Expectation**: Excess return of the long position is shown in the chart[18] - **Short-term Prosperity Expectation**: Excess return of the long position is shown in the chart[22] - **Momentum Reversal**: Excess return of the long position is shown in the chart[25] Quantitative Factors and Construction Methods Factor Name: Financial Report Quality Factor - **Construction Idea**: This factor focuses on the quality of financial reports[11] - **Construction Process**: The factor is used to select industries such as banking, non-bank finance, transportation, and construction[11] - **Evaluation**: The financial report quality factor has shown concentrated absolute returns recently[11] Factor Name: Correlation Factor - **Construction Idea**: This factor focuses on the correlation between industries[11] - **Construction Process**: The factor is used to analyze industry rotation and select industries based on their correlation[11] - **Evaluation**: The correlation factor has shown concentrated absolute returns recently[11] Factor Name: Momentum Factor - **Construction Idea**: This factor focuses on the momentum of industries[11] - **Construction Process**: The factor is used to analyze industry momentum and select industries based on their momentum[11] - **Evaluation**: The momentum factor has shown concentrated absolute returns recently[11] Factor Name: Main Fund Factor - **Construction Idea**: This factor focuses on the main fund flows in the market[11] - **Construction Process**: The factor is used to analyze the effectiveness of main fund flows and select industries based on their fund flows[11] - **Evaluation**: The effectiveness of the main fund factor has stopped declining and is beginning to recover[11] Factor Backtesting Results - **Financial Report Quality Factor**: Excess return of the long position is shown in the chart[14] - **Correlation Factor**: Excess return of the long position is shown in the chart[14] - **Momentum Factor**: Excess return of the long position is shown in the chart[14] - **Main Fund Factor**: Excess return of the long position is shown in the chart[14]

Economic Performance - In the first quarter, Shandong's GDP reached 23,466 billion yuan, with a year-on-year growth of 6.0% [1] - The primary industry added value was 754 billion yuan, growing by 3.7%; the secondary industry added value was 9,073 billion yuan, growing by 6.3%; and the tertiary industry added value was 13,639 billion yuan, growing by 6.0% [1] - Agricultural production showed stability, with total output value in agriculture, forestry, animal husbandry, and fishery reaching 143.64 billion yuan, a growth of 4.2% [1] Industrial Growth - Shandong's industrial added value above designated size grew by 8.2% year-on-year in Q1, with March seeing a growth of 8.3% [2] - Among 41 industrial categories, 36 reported growth, with a growth rate of 87.8%, and 14 industries achieved double-digit growth [2] Service Sector - The revenue of Shandong's service industry above designated size increased by 8.2% year-on-year from January to February, improving by 1.0 percentage point compared to the previous year [2] - Out of 32 service industry categories, 27 reported revenue growth, resulting in a growth rate of 84.4% [2] Cultural and Tourism Development - The 2025 Shandong Cultural and Tourism Industry High-Quality Development Conference was held, emphasizing the province's commitment to enhancing its cultural and tourism sectors [3][4] - Strategic cooperation agreements were signed, and key tourism projects were launched to promote Shandong as an international cultural tourism destination [3] Film Industry - The 20th China Film Huabiao Awards commenced in Qingdao, highlighting the city's role as a hub for film production and technology [5][6] - Qingdao has become a significant location for major film productions, benefiting from government incentives for filming [6] Agricultural Promotion - The "Good Products Shandong Special Agricultural Products" promotional event was launched in Shanghai, aiming to enhance the market competitiveness of Shandong's agricultural products [7][8] - The event featured various agricultural product categories and aimed to strengthen supply chain integration and market access [7][8] Investment and Collaboration - The fifth "Shandong Enterprises Entering Gansu" investment conference was held, with over 300 Shandong enterprises participating, marking a record high [9] - The conference focused on collaboration in various sectors, including agriculture and tourism, and has led to significant investment growth in Gansu [9]

（原标题：25Q1 全 A 业绩同比显著增长，科创增速亮眼） 以下是为您生成的中文快讯： 国泰海通策略团队的方奕、田开轩发布报告指出，截至目前，全 A 24 年 报披露率达 70.3%，年报+预告披露率达 88.3%；25Q1 季报+预告披露率达 41.3%。24 年全 A 业绩小幅 下滑，双创业绩压力大，沪深 300 有韧性。消费板块中农林牧渔、商贸表现较好；科技里电子、汽车及 金融中非银增长快；周期行业中交运、公用占优，地产建筑链跌幅居前。25Q1 全 A 业绩同比显著增 长，科创增速亮眼。科技成长复苏，传媒、电子、军工、电新等大幅增长；消费中农牧、社服增长较 快；周期行业回暖，钢铁、建材、有色增速居前，地产业绩明显提升，非银延续增长。但需注意数据统 计口径差异及已披露数据对行业代表性有限的风险。 和讯自选股写手 风险提示：以上内容仅作为作者或者嘉宾的观点，不代表和讯的任何立场，不构成与和讯相关的任何投 资建议。在作出任何投资决定前，投资者应根据自身情况考虑投资产品相关的风险因素，并于需要时咨 询专业投资顾问意见。和讯竭力但不能证实上述内容的真实性、准确性和原创性，对此和讯不做任何保 证和承诺。 股票名称 ...

在复杂多变的国际大环境下，A股上市公司陆续交出2024年业绩成绩单，一批高韧性行业和龙头企业率先突围，科技硬核创新加速突破，消费复苏蹄疾步 稳，央企价值重估成效显著，为2025年市场注入强劲信心。 根据Wind数据，截至4月15日，A股共有2426家上市公司披露2024年报，合计实现归母净利润4.64万亿元，同比增长5.3%。其中，超700家公司实现归母净利 润超20%增长，约223家公司实现业绩翻倍。 上证50企业成为全市场盈利的"稳定器"，39家已披露业绩的上证50企业合计实现归母净利润2.41亿元，同比增长10.65%；分行业看，农林牧渔、非银金融、 电子、汽车、交通运输等多行业实现2024业绩同比超20%增长。 过半上市公司2024年业绩增长，龙头企业"压舱石"作用明显 上述已发布2024年报的2426家上市公司中，有963家公司实现营业收入同比增长，占比约40%，1252家实现归母净利润同比增长，占比超50%。 归母净利润增速方面，934家公司实现双位数增长，396家公司实现超50%增长，223家公司实现超100%增长；归母净利润规模方面，365家公司超10亿元， 104家公司超50亿元，66家公司 ...

Group 1 - A total of 36 companies were investigated by institutions on April 24, with 26 companies specifically targeted by funds [1] - Among the companies, Zhongchong Co., Ltd. attracted the most attention, with 44 funds participating in the investigation [1] - The companies investigated span 13 industries, with the pharmaceutical and biological sector having the highest representation, featuring 5 companies [1] Group 2 - In the past five days, 18 of the investigated stocks have risen, with the highest increases seen in Erkang Pharmaceutical (31.65%), Kailaiying (19.20%), and Zhongchong Co., Ltd. (14.19%) [1][2] - 12 stocks experienced net inflows of funds, with Kailaiying receiving the most significant net inflow of 254 million yuan [2] - Among the companies that have reported Q1 earnings, Erkang Pharmaceutical and Jingce Electronics showed the highest net profit growth rates of 868.91% and 336.06%, respectively [2]

周四早盘冲高回落后窄幅震荡，多空围绕"关税跳空缺口"反复争夺。周四 A 股早盘出现冲高回落，市场一度出现快速下跌，但午盘企稳后维持窄幅 震荡，多空双方围绕"关税缺口"反复争夺。周四收盘距离所谓"对等关税"宣布前的跳空缺口 3319 点仅一步之遥，市场分歧有所加大，追涨意愿下降，但 A 股的修复行情仍然在延续。从中期角度来看，在中央汇金等三家国资开始增持，叠加多家上市公司宣布回购增持后，市场已经迎来拐点。尽管 "对等关 税"的后续影响还存在一定不确定性，但市场交易开始克服恐慌心理，指数在波折中继续修复行情。 后市展望：关税事件的冲击最高峰已经过去，A 股将在波折中继续修复。4 月 7 日的极端下跌是对近期所谓"对等关税"事件的一次性反映，随着市场 情绪逐渐平稳和以中央汇金为代表的国资以及多家上市公司宣布回购增持后，目前 A 股已经进入修复性回升。但修复过程并非一帆风顺，美国对全球范 围加征所谓"对等关税"的后续变化对中国和全球经济产生的影响目前仍存在较大不确定性，市场预期变化也存在反复。后市争议较大的仍然是对海外业务 依赖性较高的行业，如消费电子、CXO 等会受到"对等关税"多大程度的影响。确定性较高的是内需和 ...

4月24日融资余额增加居前的北交所股票 | 代码 | 简称 | 4月24日涨跌幅 | 最新融资余额 | 较上一日增加 | 占流通市值比例 | 所属行 | | --- | --- | --- | --- | --- | --- | --- | | | | （%） | （万元） | （万元） | （%） | 业 | | 838227 | 美登科 技 | -1.52 | 6039.49 | 802.93 | 5.50 | 计算机 | | 833523 | 德瑞锂 | -4.93 | 5060.96 | 556.96 | 2.33 | 电力设 | | | 电 | | | | | 备 | | 832522 | 纳科诺 | -3.71 | 11149.42 | 539.04 | 2.19 | 电力设 | | | 尔 | | | | | 备 | | 920106 | 林泰新 材 | -2.24 | 3260.65 | 513.21 | 2.06 | 汽车 | | 832023 | 田野股 | -5.10 | 3827.50 | 372.12 | 2.39 | 农林牧 | | | 份 | | | | | 渔 | | 8310 ...

股市潜在风险提示： 截至2025年4月20日，中泰资管风险系统对各大资本市场的系统评分情况如下： 沪深300指数的中泰资管风险系统评分为45.53，较上月47.51略有下降，市场情绪出现一定波动，整体风险 评分仍处于中等偏低风险区间。 沪深300估值较上月有所下降（本月38.93，上月45.01），显示出市场整体估值水平有所回落。从行业分布 来看，部分前期估值较高的行业如电子、计算机等，估值有所调整，而部分防御性板块或低估值板块的估 值相对稳定。 行业间估值分化有所减小。 目前，28个申万一级行业中钢铁、房地产、国防军工、计算机 的行业估值高于历史60%分位数；农林牧渔、纺织服装、公共事业、非银金融等行业的估值低于历史10% 分位数。 市场整体估值的调整，有超预期的关税冲击的影响，也反映了市场对经济复苏节奏和企业盈利 预期的重新评估。 市场预期分数较上月有所下降（本月48.00，上月56.00）。分析师认为，政策层面持续发力，财政政策和 货币政策协同配合，为经济复苏提供了有力支持。财政方面，当月地方基建支出有所改善，土地市场的恢 复虽不均衡，但政府债发行提速，继续支撑政府性基金支出。预计二季度财政仍将保持积极 ...

截至2025年4月20日，中泰资管风险系统对各大资本市场的系统评分情况如下： 沪深300指数的中泰资管风险系统评分为45.53，较上月47.51略有下降，市场情绪出现一定波动，整体风险 评分仍处于中等偏低风险区间。 沪深300估值较上月有所下降（本月38.93，上月45.01），显示出市场整体估值水平有所回落。从行业分布 来看，部分前期估值较高的行业如电子、计算机等，估值有所调整，而部分防御性板块或低估值板块的估 值相对稳定。 行业间估值分化有所减小。 目前，28个申万一级行业中钢铁、房地产、国防军工、计算机 的行业估值高于历史60%分位数；农林牧渔、纺织服装、公共事业、非银金融等行业的估值低于历史10% 分位数。 市场整体估值的调整，有超预期的关税冲击的影响，也反映了市场对经济复苏节奏和企业盈利 预期的重新评估。 市场预期分数较上月有所下降（本月48.00，上月56.00）。分析师认为，政策层面持续发力，财政政策和 货币政策协同配合，为经济复苏提供了有力支持。财政方面，当月地方基建支出有所改善，土地市场的恢 复虽不均衡，但政府债发行提速，继续支撑政府性基金支出。预计二季度财政仍将保持积极。但全球经济 复苏的 ...

关税作为政策工具的历史演变 1、1930年代：斯穆特-霍利法案与全球⼤萧条的教训 1930年出台的《斯穆特-霍利关税法》在全球经济已显疲态之际，将超过两万种商品的进口税率显著上调，使美国平均关税水平从1929年的13.5%提升至 1933年的19.8%。 历史数据显示，在该法案实施后， 美国名义GDP在四年间下滑了45%，出口总额骤降67%，失业率攀升至近25% 。这一历史时期的经验深刻表明，在 全球经济高度关联的背景下，大幅度、非协商性的关税措施极易触发链式反应，最终对本国经济造成深远的负面影响。 图片来源于：广发证券 然而，相对1930年代，当前世界贸易以国际价值链为特征，强行推进贸易壁垒会使得供应链紊乱甚至断裂， 真实落地的难度更大 ； 同时，对美国本身经济来说，当前 贸易战的冲击会远小于1930年代 ，原因在于：一是当前经济过热程度不如1920年代末期，二是美联储 有更灵活的货币政策空间，以应付可能产生的衰退或通缩。但鉴于美国当前进出口占GDP比重显著高于1930年代， 波及的人群和国家或 更广 。 2、2018年：特朗普"关税优先"政策的阶段性演绎 2018年起，美国对华发起多轮关税制裁，涵盖金额从 ...