Overview - The A-share market experienced fluctuations in the first half of 2025, with the overall trend being a recovery after a rapid decline at the beginning of the year. The market indices showed positive performance, with the Wind All A, Shanghai Composite Index, and CSI 300 increasing by 5.83%, 2.76%, and 0.03% respectively [1][10][15]. Style - In the first half of 2025, the market style was relatively stable, with micro-cap stocks outperforming small-cap, which in turn outperformed mid-cap and large-cap stocks. The micro-cap index rose by 36.41%, while the large-cap index only increased by 0.36% [2][22][23]. Industry & Theme - The industry rotation speed in the A-share market showed a fluctuating trend, with a peak in rotation intensity in March. Out of 31 primary industries, 20 experienced gains, with notable increases in non-ferrous metals (up 18.12%), banking (up 13.10%), defense and military (up 12.99%), and media (up 12.77%). Conversely, coal, food and beverage, real estate, and oil and petrochemicals performed poorly [3][31][30][31]. - The second-tier industry of ground weaponry saw a rise of over 60%, while sectors like coal mining, photovoltaic equipment, liquor, and hotel catering underperformed [3][36]. Monthly Performance - Monthly performance showed that no industry recorded gains in all six months. Non-ferrous metals performed well in January, March, and June, with a notable 9.3% increase in June. The banking sector remained stable with minimal drawdowns, while the defense and military sector showed significant volatility [31][32]. Themes - Excluding certain speculative themes, 15 thematic concepts achieved over 40% growth, with servers, stock trading software, GPUs, electric vehicles, and equipment upgrades leading the way [37].

Market Overview - The Shanghai Composite Index increased by 0.20% as of 13:58, with a trading volume of 869.87 million shares and a turnover of 10,555.06 billion yuan, representing a decrease of 5.71% compared to the previous trading day [1] - A total of 3,346 stocks rose, with 60 hitting the daily limit, while 1,784 stocks fell, including 6 hitting the lower limit [1] Industry Performance - The top-performing sectors included Electronics (up 2.16%), Electric Equipment (up 1.34%), and Pharmaceutical Biology (up 1.27%) [1] - The sectors with the largest declines were Coal (down 1.63%), Oil & Petrochemicals (down 0.40%), and Transportation (down 0.33%) [1] Detailed Industry Data - **Electronics**: - Trading volume: 1,536.56 billion yuan - Leading stock: Jiu Zhi Yang, up 16.58% [1] - **Electric Equipment**: - Trading volume: 1,043.13 billion yuan - Leading stock: Zhong Yi Technology, up 19.99% [1] - **Pharmaceutical Biology**: - Trading volume: 885.16 billion yuan - Leading stock: Guang Sheng Tang, up 20.00% [1] - **Coal**: - Trading volume: 59.60 billion yuan - Leading stock: China Shenhua, down 2.72% [1] - **Oil & Petrochemicals**: - Trading volume: 69.04 billion yuan - Leading stock: Qian Neng Heng Xin, down 3.10% [1] - **Transportation**: - Trading volume: 161.18 billion yuan - Leading stock: Ningbo Shipping, down 3.88% [1]

Market Overview - The overall trading activity in the market has significantly increased, with the average daily trading volume rising from 1.2 trillion to 1.5 trillion CNY[1] - The Shanghai Composite Index turnover rate has increased to the 85th percentile, while the STAR Market turnover rate has reached the 40th percentile[1] - The proportion of stocks rising has increased to 88.6%, with a median weekly return of 4.4%[3] Capital Flow Insights - Net inflow of southbound funds has risen to 28.4 billion CNY, marking a 96th percentile since 2022[3] - Foreign capital has seen a net outflow of 3.74 million USD from the A-share market[39] - Financing funds have net bought 25.6 billion CNY, with the total margin balance increasing to over 1.8 trillion CNY[3] Fund Issuance and Performance - The issuance scale of new equity funds has decreased to 15.9 billion CNY, down from 25.7 billion CNY[31] - The private equity confidence index has slightly declined, while the positions have marginally increased[37] - The average return of funds has shown a significant improvement, with most funds reporting positive returns year-to-date[33] Sector Performance - The trading concentration in certain sectors has increased, with seven industries having turnover rates above 90%, including comprehensive finance and defense[2] - The electronic and computer sectors have the highest average daily trading volumes, at 1829.61 billion CNY and 1684.80 billion CNY respectively[20] - Notable inflows in financing funds were observed in the computer sector (+4.94 billion CNY) and non-bank financials (+3.93 billion CNY), while real estate saw outflows (-0.24 billion CNY)[3] Risk Considerations - There are potential risks related to data collection methods and measurement errors, as well as biases from third-party data sources[3]

Quantitative Models and Construction Methods - **Model Name**: Neutral Constraint Maximum Factor Exposure Portfolio **Construction Idea**: Maximize the exposure of the target factor in the portfolio while maintaining neutrality in industry and style exposures relative to the benchmark index[60][61][63] **Construction Process**: 1. **Objective Function**: Maximize portfolio exposure to the target factor $ \text{Max}\quad w^{\prime}X_{\text{target}} $ 2. **Constraints**: - Industry neutrality: $ (w - w_b)^{\prime}X_{\text{inad}} = 0 $ - Style neutrality: $ (w - w_b)^{\prime}X_{\text{Beta}} = 0 $ - Weight deviation limit: $ |w - w_b| \leq 1\% $ - No short selling: $ w \geq 0 $ - Full allocation: $ w^{\prime}1 = 1 $ - Constituents from benchmark index: $ w^{\prime}B = 1 $ **Evaluation**: The model ensures that the portfolio remains neutral to industry and style biases while maximizing factor exposure[60][61][63] Factor Construction and Definitions - **Factor Name**: Beta Factor **Construction Idea**: Capture the sensitivity of individual stock returns to market returns[14][15] **Construction Process**: - Calculate the regression coefficient of individual stock daily returns against the market index (CSI All Share Index) over the past 252 trading days using a half-life weighting of 63 days **Formula**: $ \text{Beta} = \text{Regression Coefficient} $ **Evaluation**: Reflects market risk sensitivity, useful for identifying high-risk or low-risk stocks[14][15] - **Factor Name**: Book-to-Price (BP) **Construction Idea**: Measure valuation by comparing book equity to market capitalization[14][15] **Construction Process**: - $ \text{BP} = \frac{\text{Shareholders' Equity}}{\text{Market Capitalization}} $ **Evaluation**: Indicates undervaluation or overvaluation of stocks, commonly used in value investing[14][15] - **Factor Name**: Sales Growth (SGRO) **Construction Idea**: Assess growth potential by analyzing historical revenue trends[14][15] **Construction Process**: - Perform regression on annual revenue data from the past five fiscal years - Divide the regression slope by the average revenue to calculate growth rate **Formula**: $ \text{SGRO} = \frac{\text{Regression Slope}}{\text{Average Revenue}} $ **Evaluation**: Useful for identifying companies with strong growth trajectories[14][15] Factor Backtesting Results - **Beta Factor**: Weekly long-short return of 7.50%, monthly return of 8.74%[16] - **Book-to-Price (BP)**: Weekly return of -0.27%, monthly return of 0.39%[21][26][30] - **Sales Growth (SGRO)**: Not explicitly tested in the report[14][15] Portfolio Backtesting Results - **Neutral Constraint Maximum Factor Exposure Portfolio**: - **CSI 300 Enhanced Portfolio**: Weekly excess return of 0.03%, monthly return of 1.91%, annual return of 1.34%[57][58] - **CSI 500 Enhanced Portfolio**: Weekly excess return of -1.29%, monthly return of -1.24%, annual return of -2.54%[57][58] - **CSI 800 Enhanced Portfolio**: Weekly excess return of -0.32%, monthly return of 1.68%, annual return of 1.19%[57][58] - **CSI 1000 Enhanced Portfolio**: Weekly excess return of -0.95%, monthly return of 1.33%, annual return of 13.01%[57][58] - **CSI 300 ESG Enhanced Portfolio**: Weekly excess return of 0.51%, monthly return of 2.44%, annual return of 7.72%[57][58] Factor Performance in Different Stock Pools - **CSI 300 Stock Pool**: - Weekly top-performing factors: Log Market Cap (0.83%), Single Quarter Operating Profit Growth (0.72%), 20-Day Specificity (0.71%)[21][23] - Monthly top-performing factors: Single Quarter EP (3.19%), EP_TTM (2.93%), Single Quarter ROE (2.63%)[24] - **CSI 500 Stock Pool**: - Weekly top-performing factors: 20-Day Specificity (1.39%), 60-Day Volume Ratio (1.13%), 60-Day Reversal (1.00%)[26][28] - Monthly top-performing factors: Single Quarter Revenue Growth (3.31%), Single Quarter Operating Profit Growth (2.73%), Single Quarter ROE Growth (2.72%)[28] - **CSI 800 Stock Pool**: - Weekly top-performing factors: Log Market Cap (1.59%), Single Quarter ROE Growth (1.20%), Single Quarter Operating Profit Growth (1.06%)[30][32] - Monthly top-performing factors: Single Quarter EP (4.36%), Single Quarter ROE Growth (3.90%), Single Quarter ROE (3.90%)[33] - **CSI 1000 Stock Pool**: - Weekly top-performing factors: 60-Day Reversal (1.40%), Single Quarter SP (1.30%), SP_TTM (1.29%)[35][37] - Monthly top-performing factors: Log Market Cap (3.66%), 60-Day Reversal (3.43%), Single Quarter Net Profit Growth (3.24%)[38] - **CSI 300 ESG Stock Pool**: - Weekly top-performing factors: Log Market Cap (1.05%), 20-Day Volume Ratio (0.63%), 20-Day Specificity (0.60%)[40][41] - Monthly top-performing factors: Log Market Cap (4.20%), Single Quarter ROE (2.55%), EP_TTM (2.49%)[42] - **All-Market Stock Pool**: - Weekly top-performing factors: Log Market Cap (24.81% Rank IC), 20-Day Specificity (21.07% Rank IC), 60-Day Reversal (19.50% Rank IC)[44][45] - Monthly top-performing factors: 20-Day Specificity (11.25% Rank IC), 20-Day Three-Factor Model Residual Volatility (10.96% Rank IC), 60-Day Specificity (10.73% Rank IC)[45]

Market Overview - The Shanghai Composite Index rose by 1.04% and the ChiNext Index increased by 3.11% on June 25, 2025, with sectors like comprehensive finance, non-bank finance, and defense industry leading the gains at 5.7%, 4.4%, and 3.49% respectively, while oil and petrochemicals, coal, and transportation sectors lagged behind with changes of -0.15%, -0.04%, and 0.25% [1] Reasons for Market Fluctuation - The market experienced a significant increase in volume, with brokerage, computer, and military sectors showing the highest gains, contributing to the Shanghai Composite Index reaching a new high for the year. Recent improvements in the international market environment, including dovish signals from the Federal Reserve and a potential ceasefire agreement between Israel and Iran, have positively influenced global risk assets. Additionally, the domestic economic fundamentals are improving, supported by steady capital market reforms [2] Future Market Outlook - The outlook for the second half of the year remains moderately optimistic, driven by ongoing growth stabilization policies, accelerated infrastructure investment, and effective consumption stimulus measures. Industrial profits are expected to recover in the latter half of the year. Capital market reforms, such as relaxing insurance capital market entry ratios and optimizing dividend repurchase systems, are set to enhance the A-share market ecosystem. The strong policy intent to stabilize the capital market suggests limited chances for significant market corrections. Two asset categories are highlighted: high-elasticity new productivity sectors, including new technologies and materials, and stable industries focusing on core operations and shareholder returns, which are less affected by economic downturns in developed economies [3] Factors to Monitor - Key factors to watch include geopolitical situations, upcoming US-China trade negotiations in early August, EU-US trade talks in early July, and marginal changes in domestic real estate sales data [4]

Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is based on the principle of price momentum, aiming to capture upward trends in industry performance[27][28] - **Model Construction Process**: The diffusion index is calculated for each industry, ranking them based on their momentum. Industries with higher diffusion index values are considered to have stronger upward trends. The model selects industries with the highest diffusion index values for allocation. - Formula: Not explicitly provided in the report - **Model Evaluation**: The model has shown mixed performance over the years. It performed well in 2021 and 2022 but faced significant drawdowns in 2023 and 2024 due to market reversals and failure to adjust to cyclical changes[27] 2. Model Name: GRU Factor Model - **Model Construction Idea**: This model leverages GRU (Gated Recurrent Unit) deep learning networks to process high-frequency price and volume data, aiming to identify industry trends and generate excess returns[34][39] - **Model Construction Process**: The GRU network is trained on historical minute-level price and volume data to predict industry rankings. The model then allocates to industries with the highest GRU factor scores. - Formula: Not explicitly provided in the report - **Model Evaluation**: The model has shown strong adaptability in short-term cycles but struggles in long-term trends and extreme market conditions. It has faced challenges in capturing excess returns in 2025 due to concentrated market themes[34][39] --- Model Backtesting Results 1. Diffusion Index Model - **2025 YTD Excess Return**: 0.37%[26][31] - **June 2025 Excess Return**: 1.99%[31] - **Weekly Average Return (June 2025)**: -0.65%[31] - **Weekly Excess Return (June 2025)**: 0.79%[31] 2. GRU Factor Model - **2025 YTD Excess Return**: -3.83%[34][37] - **June 2025 Excess Return**: 0.25%[37] - **Weekly Average Return (June 2025)**: -1.18%[37] - **Weekly Excess Return (June 2025)**: 0.25%[37] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: Measures the momentum of industries by ranking them based on their upward trends[28] - **Factor Construction Process**: The diffusion index is calculated for each industry weekly. Industries are ranked based on their index values, with higher values indicating stronger momentum. - Example Values (as of June 20, 2025): - Top Industries: Comprehensive Finance (1.0), Non-Bank Finance (0.973), Banking (0.97)[28] - Bottom Industries: Coal (0.174), Food & Beverage (0.313), Oil & Gas (0.387)[28] - **Factor Evaluation**: The factor effectively captures upward trends but may underperform during market reversals[27][28] 2. Factor Name: GRU Factor - **Factor Construction Idea**: Utilizes GRU deep learning to analyze high-frequency trading data and rank industries based on predicted performance[34][39] - **Factor Construction Process**: The GRU network processes minute-level price and volume data to generate factor scores for each industry. Industries are ranked based on these scores. - Example Values (as of June 20, 2025): - Top Industries: Coal (3.48), Non-Bank Finance (3.15), Utilities (2.65)[35] - Bottom Industries: Communication (-17.95), Media (-15.45), Defense (-11.87)[35] - **Factor Evaluation**: The factor is effective in short-term trend identification but struggles with long-term stability and extreme market conditions[34][39] --- Factor Backtesting Results 1. Diffusion Index Factor - **Top Weekly Changes (June 20, 2025)**: - Oil & Gas: +0.09 - Textiles: +0.044 - Metals: +0.036[30] - **Bottom Weekly Changes (June 20, 2025)**: - Agriculture: -0.229 - Defense: -0.086 - Building Materials: -0.078[30] 2. GRU Factor - **Top Weekly Changes (June 20, 2025)**: - Non-Bank Finance: Significant increase - Consumer Services: Significant increase - Comprehensive: Significant increase[35] - **Bottom Weekly Changes (June 20, 2025)**: - Communication: Significant decrease - Electronics: Significant decrease - New Energy Equipment: Significant decrease[35]

Group 1 - The core point of the report indicates that the profit growth rate for Q1 2025 turned positive primarily due to a low base effect rather than an inherent improvement in the profit cycle [2][13][21] - The report highlights that the A-share market is currently in the longest historical negative growth period, which has resulted in a very low base for comparison [2][15] - The analysis of Q1 2025 shows that overall demand has not yet shown signs of recovery, with revenue growth remaining weak [2][13] Group 2 - The report identifies that the profit growth rate in Q1 2025 exhibited structural differentiation, with significant contributions from the non-bank financial sector, non-ferrous metals, and agriculture, forestry, animal husbandry, and fishery sectors [3][33] - Non-bank financials contributed 51.4% to the profit growth, followed by non-ferrous metals at 33.4%, and agriculture, forestry, animal husbandry, and fishery at 30.4% [3][34] - Excluding these three sectors, the remaining industries continued to experience negative growth, with a decline of -0.61% [3][33] Group 3 - The report predicts that the inherent profit bottom for A-shares is not expected to occur before Q3 2025, considering the repair of corporate balance sheets and the impact of medium to long-term loans on industrial profits [4][36] - The analysis suggests that the difference in year-on-year growth rates between non-financial enterprises and household deposits serves as a leading indicator for A-share earnings performance [4][36][40] - The report also notes that the growth of new medium to long-term loans typically leads to an increase in corporate capital expenditures and profit expansion, although the current trend shows a decline [4][37][39] Group 4 - The report outlines that several industries are expected to maintain a growth rate of over 20% in Q1 2025, excluding base effects, including optical electronics, feed, aquaculture, marine equipment, and others [41][42] - The report emphasizes that the overall confidence of enterprises has not yet recovered, with both capacity and inventory cycles remaining at low levels [26][31] Group 5 - The investment strategy suggests focusing on domestic consumption sectors such as clothing, automobiles, and food, as well as technology and military sectors [5][47] - The report recommends attention to cost improvement-driven sectors like aquaculture and precious metals, and structural opportunities in overseas markets due to improved trade relations [5][47]

1 五维行业比较框架介绍。股价表现受多重因素影响，单一指标难以有效指导行业比较。想要做好行业比较，需要对各种可能 影响股价的因素均进行分析并做出综合判断，并且对于未来可能的市场主导因素，应该赋予更高的权重。基于此，我们综合 市场风格、基本面、资金面、交易面、估值五个维度，构建了"五维行业比较框架" ，在非财报季时期，我们对于五个维 度进行等权打分，而在财报季，则给予基本面维度更高权重，并降低市场风格及估值维度的权重。 历史回测来看，五维行业比较框架表现优异，得分越高的行业表现往往更好。通过复盘2016年至2025年2月期间五维行业比 较框架的历史表现，可以发现该框架下得分越高的行业股价表现往往更好，按得分高低将行业依次分为第1组、第2组 、第3 组、第4组、第5组，各组的年化收益率分别为11.8%、1.3%、-1.4%、-7.5%及-10.5%，年化夏普比率分别为0.53、0.06、 -0.07、-0.35及-0.51。若通过做多第1组行业，做空第5组行业构建多空组合，多空组合的年化收益率为23.7%，年化夏普比 率为1.69。 6月主观因素判断。五维行业比较框架中，有三个维度涉及到一些主观判断，这三个维度分 ...

周二 A 股窄幅震荡，假日效应导致市场窄幅波动。周二 A 股小幅低开后进入窄幅震荡，全天波幅 有限，中小市值个股表现相对较好。上证指数距离所谓"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。临近五一长假，市场担心长 假期间出现突发事件影响节后表现，因此总体表现相对谨慎。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。尽管所谓"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 ...

Market Overview - The A-share market experienced narrow fluctuations with slight declines in major indices, with the Shanghai Composite Index closing at 3286.65, down 0.05% [1] - The Shenzhen Component Index and the ChiNext Index also saw minor declines of 0.05% and 0.13% respectively, while the North Exchange 50 Index increased by 1.24% [1] Sector Performance - The top-performing sectors included Beauty Care (+2.60%), Machinery Equipment (+1.44%), and Media (+1.27%), while the worst-performing sectors were Utilities (-1.78%) and Oil & Petrochemicals (-0.55%) [2] - Concept sectors showed strong performance in PEEK materials (+5.60%) and dyes (+3.85%), while sectors like supercritical power generation and controlled nuclear fusion faced declines [2] Future Outlook - The market is expected to stabilize after a brief adjustment, supported by positive economic data from Q1, including better-than-expected export figures and credit data indicating total expansion [5] - The report suggests focusing on sectors such as Finance, Food & Beverage, Utilities, Retail, Non-ferrous Metals, and TMT for potential investment opportunities [5] - The National Development and Reform Commission has announced strong demand for the consumer goods replacement market, with plans to allocate an additional 81 billion yuan in special bonds to support this initiative [4]