Report Industry Investment Rating - Not provided in the content Core Viewpoints - The inventory cycle of the entire industrial sector continues in the "active restocking" phase. Although the inventory growth rate of the entire industrial sector remained flat compared to last month, the largest number of industries, 16 in total, are in the "active restocking" state, so it is determined that the industry inventory cycle is in the "active restocking" state [16][17]. Summary by Directory 1. Inventory Cycle Overview - In March 2025, the year-on-year growth rate of finished - product inventories of industrial enterprises remained flat at 4.2% compared to last month [9][10]. - The inventory cycle of the entire industrial sector continues in the "active restocking" state [16][17]. 2. Inventory Cycle Overview (by Industry) - **Upstream Industry**: The upstream industry (mining, accounting for only 2% of total inventory) has returned to the "active restocking" state in March 2025 [18]. - **Mid - stream Industry**: The mid - stream industry (mid - upstream manufacturing, accounting for 54% of total inventory) is in the "active restocking" state in March 2025 [19]. - **Downstream Industry**: The downstream industry (downstream manufacturing and utilities, accounting for 43% of total inventory) has returned to the "active restocking" state in March 2025 [20]. - **Specific Industries**: - Electronics is in the "passive destocking" state in March 2025 [21]. - Electrical machinery is in the "active restocking" state in March 2025 [21]. - Chemicals is in the "passive restocking" state in March 2025 [23]. - Paper is in the "passive destocking" state in March 2025 [23]. - Automobiles is in the "active destocking" state in March 2025 [28]. - Non - ferrous metals is in the "passive restocking" state in March 2025 [28]. - Instrumentation is in the "active restocking" state in March 2025 [33]. - General equipment is in the "passive destocking" state in March 2025 [33].

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints The report comprehensively tracks the supply and trading of local government bonds, including an overview of the stock market, the rhythm of primary supply, and the characteristics of secondary trading, presenting a detailed picture of the local government bond market in the current period [11]. 3. Summary by Directory 3.1 Stock Market Overview - As of May 9, 2025, the local government bond stock reached 50.72 trillion yuan, indicating a continuous expansion of the market [11]. - Among the outstanding local bonds, the proportion of new special-purpose bonds exceeded 43%, and the proportion of refinancing special-purpose bonds was 21% [11]. - In terms of the investment direction of special-purpose bonds, shantytown renovation, park and new district construction, and rural revitalization were the areas with relatively large scales, with stock balances all exceeding 1 trillion yuan. The stock balance of toll roads exceeded 870 billion yuan, and the stock balance of water conservancy and ecological projects also exceeded 200 billion yuan [11]. - As of May 9, 2025, Guangdong, Jiangsu, and Shandong ranked among the top three in terms of local government bond stock, with each province's stock exceeding 3 trillion yuan. Other major GDP - provinces such as Sichuan, Zhejiang, Hunan, Henan, Hebei, and Hubei also had stock scales above 2 trillion yuan [11]. 3.2 Primary Supply Rhythm - Last week, local government bonds worth 105.459 billion yuan were issued, including 100.556 billion yuan of new special - purpose bonds and 367 million yuan of refinancing special - purpose bonds. "Ordinary/project revenue" and "repayment of local bonds" were the main investment areas for special - purpose bond funds [18]. - As of May 14, 2025, the issuance of special refinancing special - purpose bonds in May had reached 12.695 billion yuan, accounting for 2.81% of the monthly local government bond issuance scale [18]. - In terms of the issuance term structure, the issuance proportion of 10 - 20 - year local government bonds was relatively high last week, reaching 35.42%. The average coupon rates of local government bonds for each major term were basically the same as those two weeks ago. The spread between the issuance rate of 30 - year local government bonds and the same - term treasury bonds slightly widened to 21.49BP, and the spread of 20 - year local government bonds over the same - term treasury bonds slightly widened to 15.34BP [27]. - From the perspective of new bond subscription, the upper limit of the bid rate last week was slightly higher than that two weeks ago, and the primary tender sentiment significantly recovered [27]. - Five provinces issued new bonds last week. Fujian had the largest issuance volume this month, with terms mainly concentrated within 7 years and 10 - 20 years. Guangdong followed, with terms mainly concentrated in 7 - 10 years and 10 - 20 years. Jiangxi, Inner Mongolia, and Dalian had relatively small new issuance amounts. Except for Inner Mongolia, the issuance rates of other provinces were below 2% [35]. 3.3 Secondary Trading Characteristics - Since mid - to late March this year, the yield of local government bonds has been on a continuous downward trend. As of May 9, 2025, the yield of 10 - year local government bonds was 1.86%, with a spread of 22.49BP from the same - term treasury bonds, at the 72.6% quantile since 2024. The quantiles of the price spreads for the 15 - year and 30 - year varieties were 90% and 88.2% respectively [36]. - Last week, the turnover rate of local government bonds rebounded. The turnover rates of all term varieties significantly increased compared to two weeks ago. The variety with the highest weekly turnover rate was the one within 7 years, with a reading of 0.62% [42]. - In terms of regions, the number of transactions in Jiangsu and Shandong last week exceeded 100. The average transaction term of local government bonds last week was 15.73 years, and the average yield was 1.92% [42]. - In terms of the investor structure, commercial banks, insurance companies, securities proprietary departments, and broad - based funds were the most active institutions in local government bond trading. Insurance companies remained the main undertakers of local government bond supply, with a total net purchase of local government bonds reaching 20.906 billion yuan, of which the purchase proportion of 20 - 30 - year and above varieties reached 81.78%. Funds had a net purchase of 527.7 million yuan last week, mainly in the 10 - 20 - year varieties. Wealth management products had a net purchase of 72.7 million yuan, a decline compared to two weeks ago [5].

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - In April 2025, the growth rate of social financing increased due to the low base, mainly contributed by government bonds, while credit performance was sluggish [2][9]. - The negative growth of residents' short - term loans exceeded the seasonal level, and the demand for enterprises' short - term loans was overdrawn in March, with weak performance of medium - and long - term loans under internal and external pressures [3][4]. - Recently, the credit cycle has a greater impact on interest rates than the export cycle, and the export chain is not the main factor disturbing the credit cycle [5][6]. - The interest rate point corresponding to the financing data is around 1.8%, and the credit cycle may reverse at the bottom within the year [7][25]. 3. Summaries Based on Related Catalogs 3.1 Social Financing and Credit Situation - **Social Financing Growth Driven by Government Bonds**: In April 2025, the stock social financing growth rate rose by 0.3 percentage points to 8.7%. Government bonds contributed 84% of the new social financing, with an increase of 1.07 trillion yuan year - on - year to 976.2 billion yuan. In contrast, RMB loans in the social financing caliber decreased by 250.5 billion yuan year - on - year to 84.4 billion yuan, hitting a record low for the same period [2][9]. - **Residents' Credit**: In April, residents' sector credit decreased by 5 billion yuan year - on - year to - 521.6 billion yuan. Short - term loans decreased by 50.1 billion yuan year - on - year to - 401.9 billion yuan, a record low for the same period. The potential unemployment pressure increased, which affected residents' short - term loans. Medium - and long - term loans decreased by 12.31 billion yuan, and the sales volume growth rate of commercial housing in 30 large and medium - sized cities improved compared with the same period last year [3][14]. - **Enterprise Credit**: In April, new enterprise credit decreased by 25 billion yuan year - on - year to 61 billion yuan. Short - term loans decreased by 7 billion yuan year - on - year to - 48 billion yuan, and medium - and long - term loans decreased by 16 billion yuan year - on - year to 25 billion yuan. The negative growth of short - term loans exceeded the seasonal level, possibly due to the over - borrowing in March. The medium - and long - term loan balance growth rate continued to decline by 0.18 percentage points to 8.8% [4][18]. 3.2 Impact of Credit and Export Cycles on Interest Rates - **Greater Impact of Credit Cycle on Interest Rates**: Since 2024, the new export order index has performed well, but the 10 - year treasury bond yield has gradually declined. The decline trend of enterprise medium - and long - term loan growth rate is more consistent with the treasury bond trend, indicating that the domestic credit cycle has a greater impact on interest rates than the export cycle [5][19]. - **Limited Impact of Export Chain on Credit**: After detailed calculations, the proportion of credit directly and indirectly related to exports in the overall enterprise credit scale is about 20% in recent years, suggesting that domestic factors are the main forces affecting credit [6][24]. 3.3 Interest Rate and Credit Outlook - **Equilibrium Interest Rate Point**: As of April, the growth rate of the stock social financing excluding government bonds was 6.02%, slightly up 0.1 percentage point from March, corresponding to an interest rate point of 1.82%. The suspension of tariff shocks may have two - sided effects, and the credit cycle may reverse at the bottom within the year [7][25].

Investment Rating - The report suggests a positive outlook for C-end stock trading software companies and recommends focusing on companies like Zhina Zhen and Jiufang Zhitu Holdings, while also highlighting the potential recovery of IT investments in securities firms and banks, recommending attention to companies such as Hengsheng Electronics, Top Point Software, and Yuxin Technology [1][3]. Core Viewpoints - The capital market IT sector showed signs of recovery in 2024, with a notable increase in A-share average daily trading volume by 21.2% year-on-year, leading to improved trading sentiment and revenue growth for C-end trading software companies [9][11]. - The banking IT sector faced challenges, with a decline in financial technology investments from major state-owned banks and a drop in revenue for listed banking IT companies [24][26]. - The report identifies three main growth drivers for financial IT companies in 2025: Xinchuang (domestic innovation), AI, and international expansion [1][3]. Summary by Sections 1. Capital Market IT Performance - In 2024, 150 securities firms achieved a total revenue of 451.2 billion yuan, a year-on-year increase of 11.2%, with net profit rising by 21.3% to 167.3 billion yuan [9][11]. - C-end capital market IT companies performed well, with total revenue of 23.58 billion yuan, although B-end companies faced revenue declines [22][23]. - The overall revenue for 10 capital market IT companies decreased by 3.3% year-on-year, while net profit fell by 28.7% [22][23]. 2. Banking IT Sector - The total revenue for 19 banking IT companies in 2024 was 67.459 billion yuan, down 4.55% year-on-year, with a decline in net profit by 47.61% [30][26]. - The report notes a slowdown in IT investment growth among major state-owned banks, with total financial technology investment at 124 billion yuan, a slight decrease of 0.15% [25][26]. - The number of banking IT employees increased by 3.66% to 168,109, but revenue per employee decreased by 7.35% [27][30]. 3. Growth Drivers for 2025 - Financial IT companies are actively exploring growth points in Xinchuang, AI, and international markets, with a positive outlook for the first quarter of 2025 [1][3]. - The report anticipates that 2025 will be a pivotal year for AI commercialization, with financial IT companies focusing on integrating AI capabilities into existing products [38][39]. - Companies like Yuxin Technology and Tianyang Technology are developing integrated AI solutions to enhance operational efficiency and customer engagement [38][39].

Investment Rating - The report suggests a positive outlook for C-end stock trading software companies and recommends focusing on companies like Zhinancai and Jiufang Zhituo Holdings, while also highlighting the potential recovery in IT investments for securities firms and banks, recommending attention to companies such as Hengsheng Electronics, Dingdian Software, and Yuxin Technology [1]. Core Viewpoints - The capital market IT sector showed signs of recovery in 2024, with a notable increase in A-share average daily trading volume by 21.2% year-on-year, leading to improved trading sentiment and revenue growth for C-end trading software companies [9][11]. - The banking IT sector faced challenges, with a decline in financial technology investments from major state-owned banks and a decrease in revenue for listed banking IT companies [24][26]. - The financial IT companies are expected to leverage new growth drivers such as domestic innovation (Xinchang), AI, and international expansion in 2025 [1][32]. Summary by Sections 1. Capital Market IT Performance - In 2024, the total revenue of 150 securities firms reached 451.2 billion yuan, a year-on-year increase of 11.2%, with net profit rising by 21.3% to 167.3 billion yuan [9][11]. - The average daily trading volume of A-shares was 1,063.4 billion yuan, reflecting a significant improvement in trading activity [9]. - C-end capital market IT companies performed well, with revenue growth exceeding 15% for companies like Zhinancai and Tonghuashun, while B-end companies faced revenue declines [22][23]. 2. Banking IT Sector Overview - The total revenue of 19 listed banking IT companies in 2024 was 67.459 billion yuan, down 4.55% year-on-year, indicating a slowdown in revenue growth [26][30]. - The overall IT investment from the six major state-owned banks slightly decreased to 124 billion yuan, with a year-on-year decline of 0.15% [25][24]. - The number of IT personnel in banking IT companies increased by 3.7% to 168,109, but revenue per employee decreased by 7.35% [27][30]. 3. Growth Drivers for Financial IT Companies - Financial IT companies are actively exploring growth opportunities in domestic innovation, AI, and international markets, with expectations for significant demand growth in 2025 [1][32]. - The report identifies three categories of AI deployment: providing integrated machines for rapid model deployment, enhancing existing product lines with AI capabilities, and developing code assistants to improve efficiency [38][39]. - The report highlights the ongoing progress in domestic innovation projects, with several companies achieving significant milestones in adapting their products to meet domestic standards [36][37].

PPI：油价强势反弹 生产：轮胎开工率降至年内次低 需求：集运运价指数止跌 CPI：猪价低位拉锯 统计口径误差。数据统计大多为抽样，恐与现实情况有些许出入。 敬请参阅最后一页特别声明 1 (1) 电厂日耗季节性下行。5 月 13 日，6 大发电集团的平均日耗为 74.7 万吨，较 5 月 6 日的 75.1 万吨下降 0.6%。5 月 7 日，南方八省电厂日耗为 173.7 万吨，较 4 月 28 日的 186.7 万吨下降 7.0%。 (2) 高炉开工率维持高位。5 月 9 日，全国高炉开工率 84.6%，较 5 月 2 日上升 0.3 个百分点；产能利用率 92.1%， 较 5 月 2 日上升 0.1 个百分点。5 月 9 日，唐山钢厂高炉开工率 94.3%，较 5 月 2 日持平。 (3) 轮胎开工率降至年内次低。5 月 8 日，汽车全钢胎（用于卡车）开工率 44.8%，较 5 月 1 日下降 11.5 个百分点； 汽车半钢胎（用于轿车）开工率 58.4%，较 5 月 1 日下降 14.1 个百分点。 (4) 江浙地区织机开工率小幅回升。5 月 8 日，江浙地区涤纶长丝开工率 92.0%，较 5 月 1 ...

Report Industry Investment Rating No relevant content provided. Core Viewpoints - The yield of ultra-long credit bonds continues to decline, and the number of outstanding ultra-long credit bonds with a yield below 2.2% has increased to 261 compared to last week [2][13]. - The subscription enthusiasm for ultra-long credit bonds has reached a high level. The supply of new ultra-long credit bonds in the first week after the holiday was still slow, with a weekly issuance volume of less than 9 billion. The average issuance rate of ultra-long industrial bonds has decreased marginally to 2.35%, while the average coupon rate of ultra-long urban investment bonds has continued to rise to 2.78% [3][21]. - The growth of the ultra-long credit bond index is weak. After the holiday, the ultra-long credit bond index had a slight catch-up increase, but the growth was still conservative, with the weekly increase of AA+ credit bonds over 10 years being only 0.37%. The scenario of rushing to buy ultra-long credit bonds is unlikely to occur, and the willingness of the market to extend the duration of credit bonds is weak [4][30]. Summary by Directory 1. Stock Market Characteristics - The yield of ultra-long credit bonds continues to decline. Due to the early implementation of interest rate cuts and reserve requirement ratio cuts, long-term interest rates have rapidly declined to a low level, further pushing down the yield of ultra-long credit bonds. The number of outstanding ultra-long credit bonds with a yield below 2.2% has increased to 261 compared to last week [2][13]. 2. Primary Issuance Situation - The subscription enthusiasm for ultra-long credit bonds has reached a high level. The supply of new ultra-long credit bonds in the first week after the holiday was still slow, with a weekly issuance volume of less than 9 billion. The average issuance rate of ultra-long industrial bonds has decreased marginally to 2.35%, while the average coupon rate of ultra-long urban investment bonds has continued to rise to 2.78%. Driven by loose expectations and the low new issuance scale this week, the subscription enthusiasm for new ultra-long credit bonds has risen to a high level of over 70% since 2024 [3][21]. 3. Secondary Trading Performance - The growth of the ultra-long credit bond index is weak. After the holiday, the ultra-long credit bond index had a slight catch-up increase, but the growth was still conservative, with the weekly increase of AA+ credit bonds over 10 years being only 0.37% [30]. - The scenario of rushing to buy ultra-long credit bonds is unlikely to occur. As the yields of government bonds over 10 years and medium- and short-term coupon assets approach the lowest levels of the year, investors should theoretically shift part of their bond allocation focus to long-term credit bonds. However, judging from the trend of trading volume, the willingness of the market to extend the duration of credit bonds is weak. Although the weekly trading volume of ultra-long industrial bonds in the mainstream 7 - 10-year maturity has increased, the figure is still lower than that in late March, and the trading sentiment is not sufficient to support the ultra-long bond market [4][33]. - The proportion of new ultra-long credit bond trading in May has continued to rise compared to the previous period, with the figure exceeding 40% in the latest week. The low valuation deviation of ultra-long credit bonds in the latest week is also relatively conservative, and the increase in holdings is restricted by the low spread protection. The proportion of TKN transactions in ultra-long credit bonds this week has also dropped below 70% [4][37]. - In terms of investor structure, public funds have increased their holdings of 5 - 10-year credit bonds by more than 2.4 billion in a single week, and wealth management products have also increased their allocation of general long-term bonds within 10 years. However, insurance companies did not show any buying volume for ultra-long credit bonds this week, possibly shifting some positions to chase equity assets [4][40].

Group 1: Dify Overview - Dify is a specialized workflow application development tool designed to address the challenges of implementing large models in financial research, such as long processing times and high data dependency[2]. - Dify offers high flexibility, modularity, and low-code features, significantly improving efficiency compared to previous frameworks like LangChain[2]. - Dify allows integration with specialized knowledge bases like RAGFlow, enhancing its application capabilities[2]. Group 2: Key Features - Dify supports diverse tool sources, enabling users to connect various tools, including custom-built workflows, enhancing reusability[3]. - The platform allows for low-code application development, making it accessible for non-technical users to build complex workflows[3]. - Dify's Agent feature enables models to actively engage in tasks, such as querying databases or retrieving information, rather than just generating text[53]. Group 3: Application Cases - The "Time Extraction" tool can automatically identify and resolve ambiguous time references in user queries, enhancing data accuracy[4]. - A specialized "Financial Analyst" Agent categorizes user inquiries into stock, industry, concept, or macroeconomic questions, facilitating targeted analysis[4]. - The "Geographic Information Retrieval" Agent can locate addresses in annual reports and search for nearby relevant locations, showcasing Dify's integration capabilities[4]. Group 4: Competitive Advantage - Compared to competitors like FastGPT and Coze, Dify offers a more flexible and customizable platform, suitable for users with specific needs in workflow and knowledge base integration[26]. - Dify's knowledge base supports various data sources and allows for structured processing, enhancing the accuracy and relevance of responses[27].

- The micro-cap stock index rotation signal indicates that the micro-cap stock index relative net value crossed above the annual line on October 14, 2024, and this trend has continued since then[29] - The 20-day closing price slopes of both the micro-cap stock index and the Moutai index are positive, suggesting a favorable outlook for the micro-cap index's relative performance[29] - In the micro-cap timing model, the volatility congestion indicator, which reflects market trading sentiment, fell below the threshold on October 15, 2024, lifting the risk warning signal[29] - The interest rate year-on-year indicator, which is more fundamental, was -20.45%, not triggering the interest rate risk control threshold of 0.3[29] - The micro-cap timing model has not triggered any risk controls, so investors who prefer to hold micro-cap stocks long-term are advised to continue holding[29] Quantitative Factors and Construction Methods 1. Factor Name: Size Factor; Construction Idea: Measures the impact of company size on stock returns; Construction Process: Calculated as the logarithm of the market capitalization (LN_MktCap)[40][51] 2. Factor Name: Value Factor; Construction Idea: Evaluates the stock's valuation; Construction Process: Includes metrics like book-to-price ratio (BP_LR), earnings-to-price ratio (EP_FTTM), and sales-to-enterprise value ratio (Sales2EV)[40][51] 3. Factor Name: Growth Factor; Construction Idea: Assesses the company's growth potential; Construction Process: Includes metrics like single-quarter operating income growth (OperatingIncome_SQ_Chg1Y) and single-quarter revenue growth (Revenues_SQ_Chg1Y)[40][51] 4. Factor Name: Quality Factor; Construction Idea: Measures the company's financial health; Construction Process: Includes metrics like operating cash flow to current debt (OCF2CurrentDebt) and gross margin (GrossMargin_TTM)[40][51] 5. Factor Name: Consensus Expectation Factor; Construction Idea: Reflects market expectations; Construction Process: Includes metrics like expected return on equity change over three months (ROE_FTTM_Chg3M) and target return over 180 days (TargetReturn_180D)[40][51] 6. Factor Name: Technical Factor; Construction Idea: Based on stock price and volume trends; Construction Process: Includes metrics like 20-day turnover mean (Turnover_Mean_20D) and 60-day return volatility (Volatility_60D)[40][51] 7. Factor Name: Volatility Factor; Construction Idea: Measures stock price volatility; Construction Process: Includes metrics like CAPM model residual volatility (IV_CAPM) and Fama-French three-factor model residual volatility (IV_FF)[40][51] 8. Factor Name: Reversal Factor; Construction Idea: Captures the tendency of stock prices to revert to the mean; Construction Process: Includes metrics like 40-day return (Price_Chg40D) and 60-day return (Price_Chg60D)[40][51] Factor Backtesting Results 1. Size Factor, IC Mean: 35.37% (All A-shares), -9.73% (CSI 300), 13.63% (CSI 500), 17.13% (CSI 1000); Long-Short Return: 8.09% (All A-shares), -3.21% (CSI 300), 3.16% (CSI 500), 4.01% (CSI 1000)[42][43] 2. Value Factor, IC Mean: 2.40% (All A-shares), 14.21% (CSI 300), 15.32% (CSI 500), 8.40% (CSI 1000); Long-Short Return: 3.53% (All A-shares), 1.74% (CSI 300), 3.00% (CSI 500), 3.33% (CSI 1000)[42][44] 3. Growth Factor, IC Mean: -4.85% (All A-shares), 0.05% (CSI 300), -5.97% (CSI 500), -17.08% (CSI 1000); Long-Short Return: 2.23% (All A-shares), 4.13% (CSI 300), 1.21% (CSI 500), 0.56% (CSI 1000)[42][43] 4. Quality Factor, IC Mean: -8.43% (All A-shares), -10.63% (CSI 300), -8.60% (CSI 500), -11.51% (CSI 1000); Long-Short Return: 2.07% (All A-shares), 1.47% (CSI 300), 2.50% (CSI 500), 0.71% (CSI 1000)[42][44] 5. Consensus Expectation Factor, IC Mean: -0.33% (All A-shares), 12.78% (CSI 300), -4.34% (CSI 500), 0.08% (CSI 1000); Long-Short Return: 2.76% (All A-shares), 4.51% (CSI 300), 4.52% (CSI 500), 3.72% (CSI 1000)[42][43] 6. Technical Factor, IC Mean: 4.13% (All A-shares), 2.37% (CSI 300), 3.13% (CSI 500), 11.63% (CSI 1000); Long-Short Return: 8.36% (All A-shares), 4.02% (CSI 300), 6.42% (CSI 500), 8.53% (CSI 1000)[42][44] 7. Volatility Factor, IC Mean: 2.14% (All A-shares), 5.04% (CSI 300), 16.85% (CSI 500), 15.33% (CSI 1000); Long-Short Return: 8.14% (All A-shares), 3.35% (CSI 300), 6.02% (CSI 500), 8.12% (CSI 1000)[42][44] 8. Reversal Factor, IC Mean: 11.17% (All A-shares), 17.06% (CSI 300), 30.80% (CSI 500), 31.65% (CSI 1000); Long-Short Return: 6.60% (All A-shares), 2.81% (CSI 300), 6.37% (CSI 500), 7.58% (CSI 1000)[42][43]

中美日内瓦经贸会谈达成重要突破，双方同意将中国对美反制关税从 125%降至 10%，美国对华加征关税从 145%降至 30%，其中 24%关税设 90 天缓冲期。这一结果远超市场预期，反映出美国在谈判中处于更被动立场，其急于取得成果 源于国内经济压力和政治反噬风险，而中国通过与东盟、欧盟等非美国家深化合作争取了谈判主动权。 谈判成功的关键在于中美双方的现实考量。美国面临关税持久战下的供应链中断风险和盟友拖延策略压力，中国则需 避免高关税对出口的长期冲击，同时利用关税战窗口期完成与非美经济体的战略布局。双方在相互经济压力下选择阶 段性妥协，既缓解了短期经贸摩擦，也为后续磋商机制奠定基础。 协议落地后，预计中国 6-7 月出口将因前期抢出口透支需求而回落，但降幅较 145%关税情景明显缓和。政策层面关注 财政对冲工具，市场层面电子产品、纺织等出口链企业压力减轻，国产替代和出海逻辑仍具长期价值。全球风险偏好 回升利好美股，黄金短期波动加剧，人民币贬值压力有所缓解。 风险提示 中美贸易博弈磋商多次反复；美国经济下行加速超预期；国内出口放缓超预期。 敬请参阅最后一页特别声明 1 宏观经济点评 中美关税超预期降级。5 月 ...