【中泰金工】市场整体情绪修复，传统行业走强而科技承压 ——行业轮动全景观察（2025.06） 分析师：李倩云 执业证书编号：S0740520050001 Email：liqy02@zts.com.cn 分析师：熊婧妍 执业证书编号：S0740523110005 Email：xiongjy01@zts.com.cn 全景观察（2025.05）》2025-05-05 2、《【中泰金工】资源型行业拥挤 （2025.04）》2025-04-02 证券研究报告/金融工程定期报告 2025 年 06 月 04 日 报告摘要 风险提示：结论基于公开的历史数据进行统计、测算，文中部分数据有一定滞后性，同时 存在第三方数据提供不准确风险；对基金产品和基金管理人的研究分析结论并不预示其未 来表现，也不能保证未来的可持续性，亦不构成投资收益的保证或投资建议；产品的表现 受宏观环境、行业基本面超预期变动、市场波动、风格转换等多重因素影响，存在一定波 动风险。 请务必阅读正文之后的重要声明部分 行业月度收益：本月 A 股市场在超长期特别国债发行、LPR 降息预期等政策及内需复 苏（"五一"消费数据超预期）推动下结束调整，主要指数震荡上 ...

Investment Insights - The report indicates an increase in the risk of "herding" behavior in the market, suggesting a cautious approach until the risk is released [3][4] - Current market focus remains on defensive sectors such as banking, pharmaceuticals, nuclear power, and new consumption themes, with a recommendation to wait for adjustment pressure to ease before making further investments [4] Stock Market Analysis - In the past week, small-cap growth stocks outperformed, while volatility in both large and small-cap styles increased, indicating instability in market styles [6] - The dispersion of excess returns among industry indices has decreased to a near one-year low, with a slight decline in the proportion of rising constituent stocks [6] - Market activity showed a slight increase in volatility, but turnover rates continued to decline, particularly in the Shanghai Stock Exchange 50, which reached historically low turnover levels [6] Commodity Market Overview - The commodity market displayed divergent trends, with energy and black metal sectors maintaining their momentum, while precious metals and non-ferrous metals showed upward trends [15] - The basis momentum for the black metal sector increased, while agricultural products remained at a low basis momentum [15] - Volatility was high in the energy sector, while other sectors experienced low-level fluctuations [15] Options Market Insights - Implied volatility for the Shanghai Stock Exchange 50 and CSI 1000 showed no significant trend before the Dragon Boat Festival, with long-term contracts experiencing a relative increase in implied volatility compared to short-term contracts [20] - The skew of put options relative to call options for the CSI 1000 maintained an advantage, with a noticeable increase in open interest, indicating market expectations of potential adjustments in small-cap stocks [20] Convertible Bond Market Trends - The convertible bond market saw a slight rebound, with the premium rate for bonds convertible at 100 yuan recovering, although the proportion of low-premium convertible bonds increased slightly [23] - Market transaction volume remained stable, and credit spreads significantly narrowed [23]

港股证券也涨回来了，A股的证券也可以加油了。不想参与个股，所以没有选择港股的地产！A股的股票，小凡不是很有兴趣，大家都知道的。 成交量不是问题，随时可能重返3400点，银行回调之时，也是其他权重行业补涨之日。中小盘股票也不要割肉，只要没有退市，可能2~3个交易日就涨回来 了。 今日，三大指数明显上涨，股票约4000家红盘。港股的医疗、证券、地产都涨幅不错。 这个位置的行情，依旧需要白酒、证券、地产、保险等拉升指数，A股的行情太落后港股了，小凡港股的仓位目前减仓后比A股略少，内心很慌乱，在专属 订阅或者公号都分享了。 希望A股快点补涨，之后港股回调了，继续建仓港股的筹码。没有50%以上的持仓就会心慌，大家是否也有同样的感觉。 系好安全带 不出意外，接下来的行情很简单，白酒、银行只要没有大涨的情况下，午后也不会大回调。市场拉升指数的压力越来越小了。 港股依旧是牛市的核心，本轮牛市在港股，大家一定要港股的仓位略重。小凡目前只能等回调增仓或者右侧运营了，上次恒科5400点附近大幅减仓后，一直 没有机会建仓…… 对行情乐观，对指数乐观，对股票也乐观。今年的A股行情不会比去年差，只是大多数人也许等不到大涨就离场了。 这个 ...

摘要 5 月小盘股表现优异，获得 2 个百分点以上的绝对收益，验证了模型判 断的准确性。6 月观点进一步倾向小盘，主要受益于宏观、市场情绪和 市场状态三个方面，其中情绪指标如天弘基金募资额、创新高个股占比 和期权 PCR 均利好小盘。 资产配置方面，当前对国内商品资产相对看好，股票资产持中性乐观态 度，而对债券则相对谨慎。宏观预期差模型显示，股票偏谨慎，债券中 性，商品乐观。左侧择时维度显示，股票偏乐观，债券偏谨慎，商品中 性。 行业轮动模型显示，市场轮动速度较快，采用价量因子为主，包括流动 性、动量和调研信息。5 月持仓行业包括银行、家电、综合金融、有色 金属、电科芯片公司和钢铁，组合涨幅 3.7%，跑赢基准 0.7%。 6 月推荐行业包括综合、消费者服务、通信、农林牧渔、钢铁和电子。 综合行业流动性得分靠前，农林牧渔与钢铁行业在调研信息维度有所优 势。综合金融因调研信息与流动性得分回落，未进入最终推荐持仓。 主动量化选股策略中，5 月初预测景气成长型策略与小盘掘金类策略将 表现更佳，小盘掘金类策略表现最佳。2025 年 5 月，小盘掘金类策略 表现最为优异，低关注度掘金策略收益率 9.6%，次新股掘金策略 ...

展望未来，我们预期上证指数将迎来一轮小级别的反弹行情，且有望在6月底之前实现拉升。尽管对于 暑假的行情我们持谨慎乐观态度，但若有突发利好消息出现，市场走势或将另有一番天地。在行业轮动 的过程中，只需抓住一轮快速上涨的机遇便已足够。对于缺乏耐心的投资者而言，他们或许难以等到最 终的上涨时刻，但节后的几个交易日或将迎来市场的积极变化。 节前市场已经历了多轮洗盘，节后有望迎来拉升行情。期间虽有回调，但月底有望再次拉升。中报披露 的数据将备受关注，特别是机构持仓情况的变化。尽管大盘指数整体表现稳健，但个股分化行情依旧明 显。在此背景下，我们更应专注于指数的分析，而非盲目追逐个股。只有清晰把握市场的节奏，我们才 能在股市的浪潮中稳健前行。 在股市的征途中，左侧投资者往往展现出与众不同的心态：上涨时他们可能感到不安，而下跌时却愈发 兴奋。每个人的交易逻辑都是基于自身的交易体系构建，而非盲目追随他人的脚步。对于指数行情的看 好，我们同样坚守自己的判断逻辑，不受外界干扰。 谈及市场的中坚力量，白酒、证券、地产无疑是行情启动时的关键角色。它们如同市场的节奏大师，总 能在关键时刻引领市场风向。没有它们的强势拉升，市场的成交量难以 ...

证 券 研 究 报 告 【债券日报】 转债市场日度跟踪 20250529 ❖ 市场概况：今日转债增量上涨，估值环比抬升 指数表现：中证转债指数环比上涨 0.58%、上证综指环比上涨 0.70%、深证成 指环比上涨 1.24%、创业板指环比上涨 1.37%、上证 50 指数环比上涨 0.29%、 中证 1000 指数环比上涨 1.76%。 市场风格：小盘成长相对占优。大盘成长环比上涨 0.62%、大盘价值环比下降 0.03%、中盘成长环比上涨 1.48%、中盘价值环比上涨 0.62%、小盘成长环比 上涨 1.53%、小盘价值环比上涨 0.84%。 资金表现：转债市场成交情绪升温。可转债市场成交额为 571.54 亿元，环比 增长 12.24%；万得全 A 总成交额为 12134.10 亿元，环比增长 17.37%；沪深 两市主力净流入 74.33 亿元，十年国债收益率环比上升 0.45bp 至 1.69%。 转债价格：转债中枢提升，高价券占比提升。转债整体收盘价加权平均值为 118.69 元，环比昨日上升 0.59%。其中偏股型转债的收盘价为 162.71 元，环比 上升 0.07%；偏债型转债的收盘价为 11 ...

Core Viewpoint - The article emphasizes the importance of ETFs as a tool for investors to navigate the fluctuating capital markets, highlighting the need to understand economic cycles for effective investment strategies [1][3]. Group 1: ETF Strategy - ETFs serve as a conductor's score, allowing ordinary investors to participate in industry rotations [1]. - A suggested ETF allocation strategy includes 50% in broad-based ETFs, 30% in sector-specific ETFs, and 20% for opportunistic investments [1]. - The "seasonal rotation model" recommends adjusting ETF allocations quarterly based on economic indicators and seasonal trends [3]. Group 2: Risk Management - Industry ETFs typically exhibit 1.5-2 times the volatility of broad indices, necessitating dynamic stop-loss strategies [3]. - The negative correlation between Hong Kong financial ETFs and U.S. regional bank ETFs can help smooth out volatility in a portfolio [3]. - Caution is advised regarding "pseudo-liquidity" traps in niche ETFs with low daily trading volumes, which may lead to price pressure during urgent sell-offs [3]. Group 3: Data-Driven Insights - Monitoring fund inflow intensity, relative strength indicators (RSI), and valuation percentiles can enhance the timing of ETF switches [5]. - Current indicators suggest that the Hong Kong medical ETF's PEG ratio is below its ten-year average, while institutional holdings in U.S. cloud computing ETFs are rising [5]. - The article stresses that superior returns come from a deep understanding of industry changes and efficient use of tools, distinguishing professional institutions from retail investors [5].

Group 1: Consumer Sector Performance - The consumer sector in A-shares is actively leading the market, with companies like Pop Mart and Mixue Group reaching historical highs in stock prices, with Pop Mart's stock price at 231.60 HKD and a market cap exceeding 310 billion HKD, while Mixue Group's stock price is at 571 HKD with a market cap surpassing 210 billion HKD [1][1] - The report highlights the strong performance of various segments within the consumer sector, including dairy, cultivated diamonds, beer, liquor, and millet economy [1] Group 2: Banking and Internship Opportunities - A recent initiative by Industrial Bank allows clients with over 10 million CNY in new deposits to secure internship opportunities for their children at prestigious companies like JPMorgan, CICC, Google, and Microsoft, with confirmation from bank staff that the program exists but is currently closed for applications [1][1] Group 3: Salary Trends in Industries - The National Bureau of Statistics reported that the highest average annual salaries in 2024 are in the information transmission, software and IT services, and financial sectors, with the information transmission and IT services sector having a 34.60% increase in average salary over the past five years [1][1] Group 4: A-share Market Dynamics - The A-share market is experiencing increased volatility and accelerated sector rotation, with a focus on technology growth opportunities as the technology sector's crowdedness has decreased, making it more attractive for investment [2][2] - The TMT sector's trading volume has dropped to about 23%, lower than levels seen in 2023 and 2024 during previous adjustments, indicating potential for recovery [2][2] Group 5: Beverage Market Trends - The market for traditional Chinese herbal drinks has seen significant growth, with the market size increasing from 0.1 million CNY in 2018 to 4.5 million CNY in 2023, and projected to exceed 10 billion CNY by 2028, driven by younger consumers [2][2] Group 6: Education and Training Industry - The competitive landscape in the education and training sector for exams like graduate school entrance and civil service has led to a proliferation of training institutions, which are increasingly focusing on marketing their teaching staff as "famous teachers" to attract students [3][3] Group 7: Robotics Market Growth - The domestic market for robotic vacuum cleaners is expected to experience explosive growth by 2025, with online sales increasing by 67.0% and offline sales by 100.5% in the first four months of the year, indicating strong market vitality [3][3] - Major brands like Roborock and Ecovacs have reported significant revenue increases of 86.2% and 11.1% respectively in the first quarter, showcasing robust performance in the sector [3][3]

Market Overview - The overall trading heat in the market has slightly decreased, with a decline in market sentiment and a drop in the average daily trading volume from 12.7 trillion to 11.7 trillion CNY [1] - The average daily number of stocks hitting the daily limit has decreased to 69, with the maximum consecutive limit hits being 5 [1] - The proportion of stocks that rose has dropped to 30%, and the median weekly return for all A-shares has fallen to -1.44% [1] Fund Flows - Financing funds continue to flow in, while ETF funds are experiencing outflows [2] - The new issuance scale of equity funds has increased to 9.5 billion CNY, with existing public fund positions rising by 0.2% [2] - Foreign capital has seen a net outflow of 700 million USD, with the inflow scale of A-shares dropping to a historical percentile of 7.6% [2] - The net inflow of financing has been 2 billion CNY, with the transaction volume proportion rising to 8.2% [2] Industry Allocation - There is a significant divergence in funding between foreign capital and margin financing in the automotive and electric new energy sectors, with financing funds increasing while foreign capital is decreasing [3] - The net inflow in the automotive sector is 2.79 billion CNY, while the computer sector has seen a net outflow of 1.41 billion CNY [3] - In the ETF market, the defense and military industry has seen a net inflow of 1.74 billion CNY, while the medical and electric new energy sectors have experienced outflows of 3.71 billion CNY and 1.75 billion CNY, respectively [3] Hong Kong and Global Fund Flows - Southbound capital inflow has accelerated, with a net inflow of 19 billion CNY, ranking in the 73rd percentile since 2022 [4] - Foreign capital has seen a net outflow of 721 million USD from Hong Kong stocks [4] - Developed markets have generally attracted foreign capital inflows, with the US and France leading in net inflows of 2 billion USD and 760 million USD, respectively [4]

- Model Name: Diffusion Index Model; Model Construction Idea: The model is based on the observation of industry diffusion indices; Detailed Construction Process: The model tracks the weekly changes in diffusion indices for various industries, ranking them based on their performance. The formula used is $ \text{Diffusion Index} = \frac{\text{Number of Advancing Stocks}}{\text{Total Number of Stocks}} $; Model Evaluation: The model has shown varying performance over the years, with significant returns in some periods and notable drawdowns in others[6][14][27] - Model Name: GRU Factor Model; Model Construction Idea: The model utilizes GRU (Gated Recurrent Unit) deep learning networks to analyze minute-level price and volume data; Detailed Construction Process: The model ranks industries based on GRU factor scores, which are derived from the GRU network's analysis of trading data. The formula used is $ \text{GRU Factor Score} = \text{GRU Network Output} $; Model Evaluation: The model has achieved substantial excess returns by capturing trading information, though it has faced challenges in certain market conditions[7][14][34] Model Backtest Results - Diffusion Index Model, Average Weekly Return: 0.72%, Excess Return: 0.11%, Year-to-Date Excess Return: -2.26%[32] - GRU Factor Model, Average Weekly Return: 1.07%, Excess Return: 0.44%, Year-to-Date Excess Return: -3.71%[37] Factor Construction and Evaluation - Factor Name: GRU Industry Factor; Factor Construction Idea: The factor is constructed using GRU deep learning networks to analyze minute-level trading data; Detailed Construction Process: The factor scores are calculated based on the GRU network's output, which evaluates the trading data to rank industries. The formula used is $ \text{GRU Factor Score} = \text{GRU Network Output} $; Factor Evaluation: The factor has shown significant improvements in certain industries, indicating its effectiveness in capturing trading information[7][14][35] Factor Backtest Results - GRU Industry Factor, Top Industries: Automotive (2.84), Steel (1.85), Media (1.48), Power Equipment and New Energy (1.35), Communication (0.88), Coal (0.66)[7][14][35]