Group 1 - The report indicates that the return on equity (ROE) for A-shares is expected to stabilize and gradually recover, driven by improvements in net profit margins, asset turnover, and an increase in equity multiplier [2][3][15] - The broad-based valuation recovery of Chinese assets is ongoing, with the CSI 800 forward P/E stabilizing around 19x, reflecting a premium of approximately 5% over MSCI Emerging Markets excluding China [4][39] - Key assets such as A50, consumer sectors, and financials are expected to lead the recovery, demonstrating strong fundamental resilience during the past three years [2][5] Group 2 - The report highlights that the profit cycle is gradually re-emerging, with A-share profit growth expected to recover, alleviating previous concerns about a long-term decline [3][15] - The report emphasizes the importance of five investment themes: RMB appreciation, technology cycles, inventory cycles, capacity cycles, and capital market reforms [6][39] - The report predicts that the non-financial A-share net profit growth rate for 2025 will be approximately 8.3%, with a reasonable valuation for the Shanghai Composite Index estimated at around 13.1x [9][45]

证券研究报告 受降雨天气影响，端午出行略显平淡 华泰研究 2025 年 6 月 02 日│中国内地 动态点评 端午假期出行较为平淡，短途增速稍好于中长途 交通部预计，2025 年端午假期（5/31-6/2）累计全社会跨区域人员流动量达 到 6.57 亿人次，同比（24 年端午假期，下同）提升 3.0%，低于交通运输 部 5 月 29 日的初步预测 7.7%，也低于五一假期（yoy+7.9%）和春节假期 （yoy+5.8%）。我们认为出行较为平淡，主要由于南方地区雨水频繁，且今 年端午假期在高考前仅约一个星期，进一步抑制旅游出行。分出行方式来看， 公路客运量同比增长 3.1%，高于铁路和民航 2.3%/1.2%的增幅，三天假期 短途旅游需求稍好。结合子行业景气趋势，考虑暑运旺季，推荐航空板块， 首推中国国航 A/H，同时推荐皖通高速 A/H、浙江沪杭甬、粤高速 A。 航空：端午假期时长较短，同比增速低于总体 据交通部预计，端午假期民航客运量日均 186.7 万人次，同比增长 1.22%， 同比增速低于铁路/公路的 2.3%/3.1%，主要由于端午假期仅三天，对于中 长 途 的 航 空 出 行 催 化 作 用 较 ...

Group 1 - The core viewpoint of the report indicates that the real estate market in China is stabilizing and undergoing transformation, with policies implemented since September 2024 showing positive effects on market recovery [1][2][3] - The report highlights that the adjustment period for housing prices has been significant, with new and second-hand housing prices decreasing by 10.1% and 17.4% respectively as of April 2025, marking a nearly four-year adjustment cycle [2][15] - The report emphasizes that the burden of home purchasing for residents is at a 20-year low, which is a positive factor for market stabilization [2][28] Group 2 - The policy environment is entering a phase of effect verification, with a series of measures aimed at stabilizing the real estate market, including urban village renovations and financial support [3][39] - The market is experiencing a recovery process characterized by differentiation, with new home sales showing a weak recovery trend and second-hand home transactions performing better due to price adjustments [4][40] - The report suggests that investment opportunities lie in the commercial real estate and property management sectors, recommending "three good" real estate stocks and companies with stable performance [5][10] Group 3 - The report identifies that the land market is seeing a moderate recovery in transaction volumes, with a 28% year-on-year increase in transaction value for residential land in the first four months of 2025 [4][43] - It notes that the concentration of land acquisition among leading real estate companies has reached a high level, indicating a shift in market dynamics [4][39] - The report forecasts a decline in new construction area, completion area, and real estate investment by 20%, 18%, and 8% respectively for the year 2025 [4][5]

证券研究报告 银行 把握资金脉络，掘金优质区域 华泰研究 2025 年 6 月 03 日│中国内地 中期策略 把握资金脉络，掘金优质区域 年初以来中信银行指数取得 9.2%绝对收益+11.6%相对收益（截止 5/30）， 排名市场第二，银行板块凭借红利底色与避险属性，投资价值仍持续凸显， 公募基金改革落地、中国资产重估有望进一步推升板块配置热情。银行基本 面逐步筑底回稳，板块内部分化或持续，经济新旧动能转型过程中，预计优 质区域基建、新兴产业有望成为稳信贷重要抓手，当地区域行有望充分受益。 个股推荐：1）经济大省挑大梁政策导向下，发达区域优质银行业绩韧性较 强，如南京、杭州、成都、重庆 AH、渝农 AH 等；2）资金低配、经营稳健 的银行，如兴业、招行等。3）港股大行股息优势突出，如农行 H、工行 H。 资金观察：红利为底，权重为势 多维资金助推板块行情，近一年险资、ETF 持续买入，公募、外资为新增量。 一方面，险资普遍加大红利股配置力度，银行股盈利稳健、股息回报较高， 为增持优选。除享受红利收益、资本利得之外，长股投方式可享受并表收益 与银保合作生态附加值，配置吸引力较强；中央汇金等资金增持以沪深 300 ...

Group 1 - The report highlights that the scheduled interest rate cut is expected to improve the cost structure of life insurance products, potentially enhancing sales momentum in the second half of the year [1][3][46] - The current valuation of insurance stocks is at historical lows, with A-share PEV ranging from 0.51x to 1.03x and H-share PEV from 0.22x to 1.15x, indicating a favorable entry point for investors [4][36] - The liquidity in the market is improving, driven by the expectation of RMB appreciation and public fund reforms, which is beneficial for insurance stock valuations [2][15][26] Group 2 - The scheduled interest rate cut is anticipated to lower the predetermined interest rate for traditional insurance from 2.5% to 2.0%, which will help alleviate the cost-revenue mismatch faced by life insurance products [3][48][56] - The dynamic adjustment mechanism for predetermined interest rates will allow for quarterly updates based on market interest rates, which is expected to enhance the overall performance of the life insurance sector [62][63] - The report emphasizes the importance of asset-liability matching to mitigate interest rate risk, with companies like China Pacific Insurance and Ping An having relatively better matching levels [5][60] Group 3 - The report notes that the sales performance of the agent channel has been under pressure due to the cost-revenue mismatch, but the expected interest rate cut may improve sales dynamics [58][60][61] - The insurance sector has seen a year-to-date increase in new premium income, primarily driven by the bancassurance channel, indicating a potential recovery in sales [58][61] - The report suggests that the public fund reforms may lead to increased liquidity in the A-share market, which could further support insurance stock valuations [43][44] Group 4 - The report identifies key companies to watch, including China Pacific Insurance, Ping An, AIA Group, and China Life, all of which are expected to benefit from the anticipated changes in the market [10][37][38] - The overall market sentiment has improved following the easing of tariff tensions, which has positively impacted the performance of insurance stocks in both A and H-share markets [22][35][36] - The report indicates that the insurance sector's performance is closely tied to macroeconomic factors, including interest rates and currency fluctuations, which will continue to influence valuations [36][29][30]

证券研究报告 基础材料 金价或偏强，基本金属关注库存拐点 华泰研究 2025 年 6 月 02 日│中国内地 行业周报（第二十二周） 本周观点：金价或偏强震荡，基本金属关注库存拐点 上周美国国际贸易法庭驳回特朗普依据 IEEPA 进行单方面加关税的行政命 令，关税政策扰动有所缓和，但由于目前关税仍未暂停，且不排除特朗普政 府或有进一步提升关税的预期（已对钢铁关税提升至 50%），因此我们认 为金价短期或偏强震荡。基本金属方面，现实端依旧偏强，铜供给端扰动叠 加需求偏强，铝全球可统计库存降至历史低位，伴随淡季来临，建议投资者 关注基本金属的库存拐点。 重点公司及动态 关税博弈、美国债务财政扩张扰动，黄金仍有上行空间，建议配置行业龙头 山金国际。 子行业观点 1）基本金属：近端需求依旧强势，关注库存拐点；2）贵金属：美国关税 政策扰动或推升金价偏强震荡。 风险提示：经济形势不及预期、政策调整、需求低迷、价格波动等。 | 有色金属 | 增持 (维持) | | --- | --- | | 基本金属及加工 | 增持 (维持) | | 研究员 | 李斌 | | SAC No. S0570517050001 | libin ...

证券研究报告 华泰研究 2025 年 6 月 03 日│中国内地 中期策略 资本市场改革建设"新气象" 近年来资本市场改革持续深化，新"国九条"绘制改革路线图谱，围绕投资 者保护、健全投资融资相协调的功能展开，以内生的高质量发展应对外部的 不确定性环境。引入中长期资金、大力发展权益基金、推动公募基金改革落 地，均有助于打造利于长期投资的市场生态，构建"资金-投资-资产"的正 向反馈循环。当前资本市场持续扩容，股票总市值突破 100 万亿元、证券化 率进一步提升。证券行业为资本市场的重要参与者，各项业务的成长均与资 本市场发展息息相关，未来有望迎来更为广阔的扩表和展业空间。当前板块 低估低配，看好头部券商修复机会。 行业格局进一步向龙头集中 在资本市场深化改革与竞争格局重构的双重驱动下，证券行业集中度呈现加 速提升态势。2024 年行业营收/净利润 CR10 分别达 74%/63%，较 2010 年 提升 22/11pct。同时，行业资产规模集中度持续提升，头部券商在扩表周期 中扩张更快、用表能力更强、杠杆率持续领先。且伴随客户需求日趋复杂， 证券行业竞争已从单一业务转向全业务链综合服务能力的比拼。龙头券商凭 ...

证券研究报告 宏观 2026 年美国财政赤字和美债供需压 力或进一步上升 华泰研究 2025 年 6 月 02 日│中国内地 专题研究 2025 财年以来，美国财政赤字规模整体超预期，而关税以及美丽大法案也 会对未来的赤字路径产生影响。我们认为，考虑关税收入和美丽大法案对财 政收支影响，预计 2026 财年美国财政赤字规模可能达到 2.2 万亿美元，赤 字率上升至 7%，超过市场预期。这一预测对美国宏观走势和资产价格变化 均有重大意义。赤字规模上升加大美债供给压力，短期内财政部仍有腾挪空 间，避免付息国债供给明显增加。但中长期看，美债财政可持续担忧推高美 债利率、并进一步加剧财政负担的"负循环"或成为美元资产持续的波动源。 1.预计 2026 财年美国财政赤字规模可能超预期 2025 财年以来（2024 年 10 月到 2025 年 4 月），美国累计赤字规模为 1.05 万亿美元，同比增速达到 13%，超过此前 CBO 预测。背后主要原因是强制 性支出以及利息支出的高增长。美国未来财政赤字规模主要受到关税以及美 丽大法案影响。一方面，特朗普加征的关税有助于增加财政收入降低赤字， 关税收入每年可能增加 210 ...

证券研究报告 金工 6 月指数定期调样的影响估算 华泰研究 2025 年 6 月 02 日│中国内地 专题研究 0% 10% 20% 30% 40% ≤-3 (-3, -2] (-2, -1] (-1, -0.5] (-0.5, 0] (0, 0.5] (0.5, 1] (1, 2] (2, 3] >3 个股冲击系数分布 资料来源：Wind，中证指数有限公司，深圳证券信息有 限公司，华泰研究 被动市场大幅扩容，指数定期调整或带来短期影响 A 股被动市场持续扩容，近年来增长尤为迅速，截至 2025 年 Q1 已经达到 约 3.26 万亿元。对于部分跟踪产品规模较大的指数而言，产品调整会对被 调动成分带来一定的短期影响；而随着被动市场的扩容，该影响可能变得愈 发明显。从测算结果来看，资金净流入的高冲击系数股票中，有 10 只股票 冲击系数超过 2 倍，或在短期内对价格提供支撑；而呈现净流出的股票中， 有 26 只股票系数绝对值在 2 倍以上，可能面临一定的潜在压力。 近年来被动市场呈现高速扩张趋势，总规模突破 3 万亿元 作为资本市场的核心投资渠道之一，被动基金近年来在国内呈现较为强劲的 发展趋势。一方面，被动产 ...

Quantitative Models and Construction Methods 1. Model Name: Commodity Term Structure Simulation Portfolio - **Model Construction Idea**: This is a long-short strategy that dynamically holds long positions in commodities with high roll yields and short positions in commodities with low roll yields. The strategy aims to capture the term structure premium in commodity markets while reducing dependency on single market trends[33][35][34]. - **Model Construction Process**: 1. **Roll Yield Factor**: The roll yield is calculated to measure the contango or backwardation state of a commodity. 2. **Dynamic Positioning**: Commodities with high roll yields are dynamically allocated long positions, while those with low roll yields are allocated short positions. 3. **Portfolio Balancing**: The portfolio is rebalanced periodically to maintain the desired exposure to the roll yield factor[35][38]. - **Model Evaluation**: The strategy demonstrates flexibility in adapting to market risks and provides stable returns even in weak market trends[34]. 2. Model Name: Commodity Time-Series Momentum Simulation Portfolio - **Model Construction Idea**: This strategy captures medium- to long-term trends in commodity prices using multiple technical indicators. It dynamically allocates long positions to upward-trending assets and short positions to downward-trending assets[33][35]. - **Model Construction Process**: 1. **Trend Indicators**: Technical indicators such as moving averages and momentum are used to identify price trends. 2. **Dynamic Positioning**: Commodities with upward trends are allocated long positions, while those with downward trends are allocated short positions. 3. **Portfolio Rebalancing**: Positions are adjusted periodically based on updated trend signals[35][45]. - **Model Evaluation**: The strategy effectively tracks price trends but may underperform in volatile or trendless markets[45]. 3. Model Name: Commodity Cross-Sectional Inventory Simulation Portfolio - **Model Construction Idea**: This strategy uses inventory data to capture fundamental changes in commodity markets. Commodities with declining inventories are allocated long positions, while those with increasing inventories are allocated short positions[33][35]. - **Model Construction Process**: 1. **Inventory Factor**: Changes in inventory levels are calculated to assess supply-demand dynamics. 2. **Dynamic Positioning**: Commodities with declining inventories are dynamically allocated long positions, while those with increasing inventories are allocated short positions. 3. **Portfolio Rebalancing**: Positions are adjusted periodically based on updated inventory data[35][49]. - **Model Evaluation**: The strategy is effective in capturing fundamental supply-demand imbalances but may be sensitive to data accuracy and reporting delays[49]. --- Model Backtesting Results 1. Commodity Term Structure Simulation Portfolio - **Annualized Return**: 3.03% (YTD 2025)[33][38] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 2. Commodity Time-Series Momentum Simulation Portfolio - **Annualized Return**: -1.33% (YTD 2025)[45] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 3. Commodity Cross-Sectional Inventory Simulation Portfolio - **Annualized Return**: 2.88% (YTD 2025)[49] - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned --- Quantitative Factors and Construction Methods 1. Factor Name: Roll Yield Factor - **Factor Construction Idea**: Measures the contango or backwardation state of a commodity to capture the term structure premium[35]. - **Factor Construction Process**: 1. Calculate the roll yield as the difference between the spot price and the futures price. 2. Normalize the roll yield across commodities to ensure comparability. 3. Rank commodities based on their roll yields and allocate positions accordingly[35]. 2. Factor Name: Trend Factor - **Factor Construction Idea**: Captures medium- to long-term price trends using technical indicators[35]. - **Factor Construction Process**: 1. Use moving averages, momentum, and other technical indicators to identify trends. 2. Normalize trend signals across commodities to ensure comparability. 3. Rank commodities based on their trend strength and allocate positions accordingly[35]. 3. Factor Name: Inventory Factor - **Factor Construction Idea**: Measures changes in inventory levels to capture supply-demand imbalances[35]. - **Factor Construction Process**: 1. Calculate the percentage change in inventory levels over a specified period. 2. Normalize inventory changes across commodities to ensure comparability. 3. Rank commodities based on their inventory changes and allocate positions accordingly[35]. --- Factor Backtesting Results 1. Roll Yield Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 2. Trend Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned 3. Inventory Factor - **Annualized Return**: Not explicitly mentioned - **Annualized Volatility**: Not explicitly mentioned - **Maximum Drawdown**: Not explicitly mentioned - **Sharpe Ratio**: Not explicitly mentioned - **Calmar Ratio**: Not explicitly mentioned