报 告 摘 要 一、基金仓位监控 普通股票型基金 仓位中位数为90.62%， 偏股混合型基金 仓位中位数为89.21%，与上一季 度相比基本持平，自2020年以来持续围绕在90%仓位震荡。普通股票型基金仓位处在历史 72.13%分位点，偏股混合型基金仓位处在历史78.69%分位点。 普通股票型和偏股混合型基金 港股仓位 均值分别为12.07%和15.3%，均较上一季度明显提 升。普通股票型配置港股基金数量为233只，偏股混合型配置港股基金数量为1572只，普通 股票型以及偏股混合型基金中配置港股的基金数量占比为57.85%。 二、基金持股集中度监控 基金重仓股占权益配置比重为53.21%，上一期为52.61%，有所提升；另一方面，基金持股 数量在2025年一季度相较于上一季度略有增加，基金经理总体持股数量为2331只，这意味 着，基金经理持仓的股票差异化有所提升。 三、板块配置监控 2025年一季报中披露的主板配置权重为55.08%、创业板配置权重为13.52%、科创板配置权 重为12.27%，港股配置权重为19.12%。 在2025年一季度内， 科技板块配置减仓较多 ，减少了1.73%，而 消费和医药板块配 ...

2025年一季报中披露的主板配置权重为55.08%、创业板配置权重为13.52%、科创板配置权 重为12.27%，港股配置权重为19.12%。 报 告 摘 要 一、基金仓位监控 普通股票型基金 仓位中位数为90.62%， 偏股混合型基金 仓位中位数为89.21%，与上一季 度相比基本持平，自2020年以来持续围绕在90%仓位震荡。普通股票型基金仓位处在历史 72.13%分位点，偏股混合型基金仓位处在历史78.69%分位点。 普通股票型和偏股混合型基金 港股仓位 均值分别为12.07%和15.3%，均较上一季度明显提 升。普通股票型配置港股基金数量为233只，偏股混合型配置港股基金数量为1572只，普通 股票型以及偏股混合型基金中配置港股的基金数量占比为57.85%。 二、基金持股集中度监控 基金重仓股占权益配置比重为53.21%，上一期为52.61%，有所提升；另一方面，基金持股 数量在2025年一季度相较于上一季度略有增加，基金经理总体持股数量为2331只，这意味 着，基金经理持仓的股票差异化有所提升。 三、板块配置监控 绝对市值配置最高 的三只股票为腾讯控股、宁德时代、贵州茅台，其配置绝对市值分别为 68 ...

Quantitative Models and Construction Methods 1. Model Name: Volume Timing Signal - **Model Construction Idea**: The model uses volume-based signals to determine market timing, identifying bullish or cautious market views based on volume trends[23][24] - **Model Construction Process**: 1. Analyze the volume trends of major broad-based indices 2. Assign a "bullish" or "cautious" signal based on the volume dynamics 3. For example, as of April 11, 2025, the Beixin 50 index showed a "bullish" signal, while other indices like the Shanghai Composite and CSI 300 showed "cautious" signals[23][24] - **Model Evaluation**: The model provides a straightforward and intuitive approach to market timing but may lack robustness in highly volatile markets[23][24] 2. Model Name: Momentum Sentiment Indicator - **Model Construction Idea**: This model captures market sentiment by analyzing the proportion of stocks with positive returns in the CSI 300 index over a specific period[24][25] - **Model Construction Process**: 1. Calculate the proportion of CSI 300 constituent stocks with positive returns over the past N days $ \text{CSI 300 N-day Upward Proportion} = \frac{\text{Number of stocks with positive returns in N days}}{\text{Total number of stocks in CSI 300}} $ 2. Smooth the indicator using two moving averages with different windows (N1 and N2, where N1 > N2) 3. Generate signals: - If the short-term moving average (fast line) exceeds the long-term moving average (slow line), the market is considered bullish - If the fast line falls below the slow line, the market sentiment is turning cautious[27] - **Model Evaluation**: The indicator is effective in capturing upward opportunities but may fail to avoid risks in declining markets[25][27] 3. Model Name: Moving Average Sentiment Indicator - **Model Construction Idea**: This model uses an eight-moving-average system to assess the trend state of the CSI 300 index[32][33] - **Model Construction Process**: 1. Calculate the closing prices of the CSI 300 index for eight moving averages (parameters: 8, 13, 21, 34, 55, 89, 144, 233) 2. Assign values to the indicator based on the number of moving averages above or below the current price: - If the current price exceeds five or more moving averages, the market is considered bullish - Otherwise, the market is neutral or bearish[32][33] - **Model Evaluation**: The model provides a clear trend-following signal but may lag in rapidly changing markets[35] --- Model Backtesting Results 1. Volume Timing Signal - Beixin 50 Index: Bullish signal[23][24] - Other indices (e.g., Shanghai Composite, CSI 300): Cautious signal[23][24] 2. Momentum Sentiment Indicator - CSI 300 Upward Proportion: Approximately 53% in the most recent week[25] 3. Moving Average Sentiment Indicator - CSI 300 Index: Currently in a non-bullish sentiment zone[35] --- Quantitative Factors and Construction Methods 1. Factor Name: Cross-Sectional Volatility - **Factor Construction Idea**: Measures the dispersion of stock returns within an index to assess the alpha environment[37] - **Factor Construction Process**: 1. Calculate the cross-sectional volatility of constituent stocks in indices like CSI 300, CSI 500, and CSI 1000 2. Compare the recent quarter's average volatility with historical periods to determine the alpha environment[41] - **Factor Evaluation**: Higher cross-sectional volatility indicates a better alpha environment for stock selection[37][41] 2. Factor Name: Time-Series Volatility - **Factor Construction Idea**: Measures the volatility of index returns over time to assess the alpha environment[41][44] - **Factor Construction Process**: 1. Calculate the time-series volatility of indices like CSI 300, CSI 500, and CSI 1000 2. Compare the recent quarter's average volatility with historical periods to evaluate the alpha environment[44] - **Factor Evaluation**: Higher time-series volatility suggests a favorable alpha environment for active strategies[41][44] --- Factor Backtesting Results 1. Cross-Sectional Volatility - CSI 300: 1.90% (recent quarter), 77.80% of the past six months' percentile[41] - CSI 500: 2.16% (recent quarter), 42.06% of the past six months' percentile[41] - CSI 1000: 2.52% (recent quarter), 64.54% of the past six months' percentile[41] 2. Time-Series Volatility - CSI 300: 0.63% (recent quarter), 78.84% of the past six months' percentile[44] - CSI 500: 0.48% (recent quarter), 55.56% of the past six months' percentile[44] - CSI 1000: 0.29% (recent quarter), 70.12% of the past six months' percentile[44]

Group 1: Tariff Policy Overview - Trump signed an executive order imposing a 10% "minimum baseline tariff" on all trade partners, with an additional 34% tariff specifically on China[1] - This is the largest new tariff policy announced since Trump took office in January 2025, affecting numerous countries and regions[1] - Certain goods, including copper, pharmaceuticals, semiconductors, and energy, are exempt from these tariffs[1] Group 2: Economic Implications - The tariffs are expected to significantly exceed market expectations, potentially leading to a collapse of the global trade order and a slowdown in economic growth[2] - The U.S. economy may face short-term stagflation, while a mid-term global economic slowdown is increasingly likely[3] - China's reliance on exports has increased since 2018, making it vulnerable to the pressures from Trump's tariffs[3] Group 3: Domestic Policy Response - In response to the tariffs, domestic policies may shift towards monetary easing, including potential interest rate cuts and liquidity measures[4] - The focus will be on managing expectations rather than fiscal stimulus, with a priority on maintaining market confidence[4] Group 4: Investment Strategy - Investment strategies should shift from high-risk tech stocks to defensive and safe assets, such as bonds and utilities[5] - Key sectors to focus on include gold, non-ferrous metals, and military industries due to the geopolitical instability caused by the tariffs[5]

金融工程 | 金工定期报告 金融工程 证券研究报告 在当前市场中，分析师报告数量众多，以行业报告为例，每周通常有超过 500 篇的报告。而阅读这些报告通常要花费大量的时间和成本。针对这一 需求，我们利用 DeepSeek-V3 大模型的总结能力对分析师行业报告进行智 能总结和整合，提炼出核心观点和关键信息。 利用大模型衡量景气度 行业研究报告通常提供分析师对行业趋势的深入分析与总体评价，但其应 用性较弱，主要有两个原因。首先，行业评级是行业研报中的标准化输出， 但其并非连续指标，通常仅分为三类，缺乏足够的区分度。因此，分析师 细微的态度和用词变化可能不会导致行业评级的调整。其次，不同证券公 司采用的行业分类标准并不一致，这些差异使得行业比较变得困难。 大模型普及之前，并不容易解决这些问题，而大模型的应用可能为此提供 更有效的支持。为了深入挖掘行业研报的信息，我们对其进行了进一步的 整理与标准化。我们构造了一个能够提取行业研报所涉具体中信一级、二 级行业名称以及对应行业景气度的提示词，并使用 DeepSeek-V3 模型，将 研报摘要作为输入文本得到该研报所属行业、景气度等指标结果。 最新行业研报文本景气度 我 ...

点击注册小程序 查看完整报告 特别申明： 本订阅号中所涉及的证券研究信息由光大证券研究所编写，仅面向光大证券专业投资者客户，用作新媒体形势下研究 信息和研究观点的沟通交流。非光大证券专业投资者客户，请勿订阅、接收或使用本订阅号中的任何信息。本订阅号 难以设置访问权限，若给您造成不便，敬请谅解。光大证券研究所不会因关注、收到或阅读本订阅号推送内容而视相 关人员为光大证券的客户。 今 日 聚 焦 【钢铁】高度重视供给侧政策预期下钢铁行业的投资机会——金属周期品高频数据周报（2025.3.3- 3.9） 2025年2月8日，工信部对《钢铁行业规范条件（2015年修订）》进行了修订，形成《钢铁行业规范条件 （2025年版）》，规范条件对钢铁企业实施"规范企业"和"引领型规范企业"两级评价，在发改委"供给侧更 好适应需求变化"的大政策目标下，我们认为钢铁板块的盈利有望修复到历史均值水平，钢铁股的PB也有 望随之修复。 （王招华/戴默） 2025- 03-10 您可点击今日推送内容的第1条查看 【石油化工】OPEC+将开启增产，地缘政治风险犹存——石油化工行业周报第393期（20250303- 20250309） 3月3 ...

英大证券研究所·证券研究报告 行 业 研 究 40% 30% 20% 10% 0% -10% -20% 沪深300 电力及公用事业指数 电力设备及新能源指数 数据来源: iFind,英大证券研究所 分析师:游虎 执业证书编号: S0990523060001 电话: 0755-83007019 邮箱: youhu@ydzq.sgcc.com.cn 相关报告 电力能源行业周报 (2025.2.3-2025.2.9) 电力能源行业周报 (2025.1.20-2025.1.27) 电力能源行业周报 (2025.1.13-2025.1.19) 电力能源行业周报 (2025.1.6-2025.1.12) 电力能源行业周报 (2024.12.30-2024.1.5) 电力能源行业周报(2024.12.23-2024.12.29) 电力能源行业周报(2024.12.16-2024.12.22) 电力能源行业周报 (2024.12.9-2024.12.15) 电力能源行业周报 (2024.12.2-2024.12.8) 电力能源行业周报 (2024.11.25-2024.12.1) 电力能源行业周报(2024.11.18-20 ...