Core Insights - The report emphasizes the ongoing supply-side reform aimed at the orderly exit of backward production capacity, marking a significant policy shift from self-regulation to higher-level government intervention [6][7] - The market is expected to experience a "pulse-like" behavior due to unclear demand-side conditions, contrasting with the more robust demand seen during the 2016 supply-side reforms [7][9] - There is a notable focus on the differentiation between "old industries" (e.g., steel, coal, cement) and "new industries" (e.g., new energy vehicles, lithium batteries, photovoltaic sectors), with a recommendation to prioritize sectors with external demand [7][8] Market Performance - The report provides a snapshot of market indices, with the Shanghai Composite Index closing at 3472.32, reflecting a 0.32% increase, while the Shenzhen Component Index decreased by 0.25% [4] - The banking sector showed a strong performance with a 1.84% increase, while the beauty care sector declined by 1.87% [5] Industry Analysis - The report indicates a marginal recovery in production and demand expectations for June, with the PMI showing slight improvement, suggesting a potential stabilization in industrial profits [9][10] - It highlights that the price pressures are expected to ease, and inventory levels are likely to remain resilient, indicating a positive outlook for the second half of the year [9][10] - The report suggests that the profitability factors are anticipated to improve, with a focus on high profitability, small-cap, and high-valuation stocks expected to outperform in the coming month [10]

Investment Rating - The report rates the chemical industry as "Outperform" [2] Core Views - The industry has been significantly impacted by tariff-related policies and fluctuations in crude oil prices this year. Key areas to focus on in July include safety regulations, supply changes in the pesticide and intermediate sectors, performance fluctuations due to "export rush," the importance of self-sufficiency in electronic materials, and stable dividend policies in energy companies [2][12] Summary by Sections Industry Dynamics - In the week of June 30 to July 6, among 100 tracked chemical products, 25 saw price increases, 56 saw declines, and 19 remained stable. The average price of TDI increased by 7.02% week-on-week, while the average price of acrylic acid rose by 3.65% [11][36] Investment Recommendations - The report suggests focusing on safety regulations and supply changes affecting the pesticide and intermediate sectors, performance fluctuations from the first half of the year, the growing importance of self-sufficiency in electronic materials, and stable dividend policies in energy companies. Long-term investment themes include sustained high crude oil prices benefiting the oil and gas extraction sector, rapid development in downstream industries, and policy support for demand recovery [12][19] Key Products and Price Changes - TDI prices increased to 12,013 CNY/ton, while acrylic acid prices reached 7,100 CNY/ton, reflecting a 14.52% year-on-year increase. The average price of crude oil also saw slight increases, with WTI at 66.50 USD/barrel and Brent at 68.30 USD/barrel [11][35][36] Company Highlights - Satellite Chemical and Anji Technology are highlighted as "gold stocks" for July, with both companies showing strong revenue and profit growth in 2024. Satellite Chemical reported a revenue of 45.648 billion CNY, a 10.03% increase year-on-year, while Anji Technology achieved a revenue of 1.835 billion CNY, a 48.24% increase year-on-year [13][19]

宏观经济 | 证券研究报告 — 总量周报 2025 年 7 月 6 日 周度金融市场跟踪 财经委会议"反内卷"，钢铁建材领涨 A 股；债 券市场收益率整体小幅震荡下行 （ 6 月 30 日 -7 月 4 日） 股票方面，本周 A 股震荡上涨，全周累计看，沪深 300 上涨 1.5%，中证 2000 上涨 0.6%。本周港股走势弱于 A 股，恒生指数下跌 1.5%，恒生科技指数下跌 2.3%。行业方面，本周钢铁、建筑材料和银行领涨，计算机、非银金融和美容 护理领跌。周内看，周一（6 月 30 日）上午，6 月制造业 PMI 指数发布，连续 2 个月回升。当天市场超 4000 只股票上涨。周二（7 月 1 日）市场震荡上涨。 周二盘后中央财经委第六次会议新闻发布，会议强调依法依规治理企业低价无 序竞争。受此影响，周三（7 月 2 日）钢铁、煤炭和建筑材料等传统周期类行业 领涨 A 股。周四（7 月 3 日）盘前美国解除对中国芯片设计类软件出口限制新 闻发出，当天市场超 3200 家公司上涨，创业板指数上涨 1.9%。周五（7 月 4 日） 市场有所分化，以沪深 300 为代表的大盘股上涨，但以中证 2000 为代 ...

Core Insights - The report indicates that the A-share market is likely to experience a gradual upward shift in its central tendency, supported by a classic structure of "weight on the platform, technology growth in the spotlight" [3][25] - The "anti-involution" trend in various industries is expected to improve nominal economic growth from the supply side, although the sustainability of style switching remains to be observed [12][27] - The IPO market has shown positive changes, with a significant increase in the number of new projects and financing amounts, benefiting the brokerage sector [42][43] Market Overview - The A-share market is currently supported by ample liquidity, and as the third quarter approaches, expectations for domestic demand are likely to recover with the acceleration of policy implementation [13][35] - The report notes that the banking sector's dividend yield has declined significantly, reaching a three-year low, which historically indicates potential volatility or adjustment risks in the banking market [32][35] Industry Analysis - The medical and pharmaceutical sectors have seen substantial inflows, with net capital inflow reaching 147.38 billion [37] - The report highlights that the "anti-involution" strategy has catalyzed a rebound in several sectors, including new energy, steel, and construction materials, although high inventory levels in some industries remain a concern [27][35] - The report emphasizes that the current market structure supports the notion of "weight on the platform, technology growth in the spotlight," which is crucial for the index's upward movement [25][35] IPO Market Dynamics - The IPO market has experienced a surge, with 53 new projects accepted in June alone, surpassing the total from January to May [42][43] - The financing amount for IPOs in June reached 9.153 billion, marking a 164.82% increase month-on-month, indicating a favorable environment for innovative companies [42][43] Sector Performance - The report notes that the electronic sector received a boost following positive news regarding U.S.-Vietnam tariff negotiations [23] - The report also mentions that the healthcare sector has been a top performer, with significant capital inflows, while sectors like computing and non-bank financials faced the largest outflows [37][38]

Investment Rating - The report maintains an "Outperform" rating for the electric equipment and new energy industry [1]. Core Insights - The photovoltaic supply-side reform is ongoing, with a focus on improving product quality and eliminating low-price competition [1][2]. - In June, the wholesale sales of new energy passenger vehicles in China reached 1.26 million units, a year-on-year increase of 29% [1][2]. - The demand for batteries and materials is expected to grow as new models of electric vehicles are launched in the second half of the year, with projections indicating high growth in domestic sales of new energy vehicles by 2025 [1]. - The solid-state battery industrialization trend is clear, with attention on related materials and equipment companies [1]. - In May, China's photovoltaic installed capacity reached 92.92 GW, a year-on-year increase of 388%, which may suppress demand for photovoltaic installations in the near term [1]. - The hydrogen energy sector is being driven by policies promoting industrialization, with a focus on companies with cost and technological advantages in electrolyzer production and hydrogen infrastructure [1]. Summary by Sections Industry Performance - The electric equipment and new energy sector rose by 1.99% this week, outperforming the Shanghai Composite Index, which increased by 1.4% [10]. - The photovoltaic sector saw a significant increase of 6.80%, while the lithium battery index rose by 3.84% [2][13]. New Energy Vehicles - Major players in the new energy vehicle market reported varying delivery figures for June, with BYD delivering 383,600 units (up 11.98% year-on-year) and Li Auto experiencing a decline of 24% [2][27]. - The report highlights the expected growth in new energy vehicle sales, driven by the introduction of new models [1][2]. Photovoltaic Sector - The central economic work conference emphasized the need to regulate low-price competition and improve product quality in the photovoltaic industry [1][2]. - The report notes the significant increase in installed capacity and the potential impact on future demand [1]. Hydrogen Energy - The approval of a large-scale green hydrogen pipeline project indicates ongoing support for the hydrogen energy sector [1][27]. Company Developments - Companies like EVE Energy and Xinwanda are planning to issue H-shares for overseas listings, indicating growth strategies in the electric equipment sector [2][28].

Quantitative Models and Construction Methods Model 1: High Prosperity Industry Rotation Strategy (S1) - **Model Construction Idea**: The model aims to select industries with upward profit expectations by tracking industry profitability using a multi-factor model based on analysts' consensus expectations[16] - **Model Construction Process**: - Construct three major types of factors based on the original value, slope, and curvature of profit expectations - Screen candidate factors with annualized excess return >3% - Use hierarchical clustering to classify candidate factors into 8 categories and select the highest excess return factor from each category for rank equal-weighted composite - Exclude overvalued industries and select the top 3 industries with the highest factor values weekly[16] - **Model Evaluation**: The model effectively captures industries with high profitability expectations[16] Model 2: Implicit Sentiment Momentum Tracking Strategy (S2) - **Model Construction Idea**: The strategy constructs a sentiment momentum model that runs ahead of earnings expectation data by capturing "unproven sentiment" in the market[19] - **Model Construction Process**: - Perform cross-sectional regression of industry daily returns on daily turnover rate changes to strip out "expected sentiment" - Calculate the residual as "unproven sentiment" - Construct half-month and 12-month momentum factors based on cumulative unproven sentiment factor net value - Rank and equal-weight composite the two momentum factors - Exclude overvalued industries and select the top 3 industries with the highest factor values weekly[20] - **Model Evaluation**: The model captures market sentiment ahead of earnings expectation data[19] Model 3: Macro Style Rotation Strategy (S3) - **Model Construction Idea**: The strategy predicts the long-short situation of four industry styles (high beta, high valuation, 12-month momentum, high volatility) based on current macro indicators and their correlation with the returns of these styles[22] - **Model Construction Process**: - Construct a fundamental indicator system from "economic growth," "inflation," "currency," "credit," and "market sentiment" - Calculate the exposure of each industry to the four styles and estimate the expected long-short returns of the style factors - Use a weak voting classifier to predict the long-short of the styles - Map the style predictions to industries and select the top 6 industries with the highest total scores monthly[23] - **Model Evaluation**: The model effectively integrates macro indicators with industry style predictions[22] Model 4: Long-term Reversal Strategy (S4) - **Model Construction Idea**: The strategy leverages the momentum effect within 2 years and the reversal effect beyond 3 years in industries[27] - **Model Construction Process**: - Construct a "1-year momentum" factor excluding the most recent month's returns - Construct a "3-year reversal" factor using the period from 3 years ago to 2 years ago - Construct a turnover factor using the turnover rate of free float market value - Rank and equal-weight composite the three factors - Select the top 5 industries with the highest factor values monthly[27] - **Model Evaluation**: The model captures long-term reversal and medium-term momentum effects in industries[27] Model 5: Fund Flow Industry Rotation Strategy (S5) - **Model Construction Idea**: The strategy constructs an industry rotation model based on "market main fund flow and strength" and "late trading fund flow and strength"[29] - **Model Construction Process**: - Construct an "institutional order trend strength factor" using the net buy amount of institutional orders - Construct a "late trading fund flow and strength factor" using the average daily inflow of late trading funds - Rank and equal-weight composite the two factors - Select the top 5 industries with the highest fund inflow strength monthly[30] - **Model Evaluation**: The model effectively captures the flow and strength of market funds[29] Model 6: Financial Report Factor Failure Reversal Strategy (S6) - **Model Construction Idea**: The strategy leverages the phenomenon of financial report factors performing poorly in recent years to construct an industry rotation model based on the mean reversion theory of factor effectiveness[34] - **Model Construction Process**: - Classify financial report factors into categories and screen for "long-term effective factors" with annualized excess return >5.5% - Identify "short-term failure factors" that underperform the industry equal-weight benchmark for 4 consecutive months - Composite the highest annualized excess return factors from each category - Select the top 5 industries with the highest factor values monthly[35] - **Model Evaluation**: The model captures the mean reversion of financial report factors[34] Model 7: Multi-factor Scoring Composite Strategy (S7) - **Model Construction Idea**: The strategy is a quarterly rebalancing strategy that composites factors from "momentum," "liquidity," "valuation," and "quality" dimensions[39] - **Model Construction Process**: - Exclude industries with a weight below 2% in the CSI 800 - Select 2 factors from each dimension and rank equal-weight composite - Select the top 5 industries with the highest factor values quarterly[40] - **Model Evaluation**: The model effectively integrates multiple factor dimensions[39] Model Backtest Results - **S1**: Annualized excess return -1.8% YTD[66] - **S2**: Annualized excess return 5.6% YTD[66] - **S3**: Annualized excess return 2.7% YTD[66] - **S4**: Annualized excess return 4.8% YTD[66] - **S5**: Annualized excess return -0.2% YTD[66] - **S6**: Annualized excess return 0.6% YTD[66] - **S7**: Annualized excess return 3.9% YTD[66] - **Composite Strategy**: Annualized excess return 2.0% YTD[66]

Group 1: Policy Signals and Market Reactions - The recent signals regarding the orderly exit of backward production capacity emerged before the July 1 meeting of the Central Financial Committee, with some product prices stabilizing in June[3] - The Central Financial Committee emphasized the need to promote the orderly exit of backward production capacity, marking a shift from industry self-discipline to top-level policy[3] - Despite the policy signals, related industry stock performances remained subdued until the July 1 meeting, indicating a delayed market reaction[21] Group 2: Market Characteristics and Trends - The current market is expected to exhibit "pulse-like" trends due to unclear demand-side signals, contrasting with the 2016 supply-side reform that saw simultaneous demand boosts[22] - The segmentation of industries will likely show significant differentiation between "old industries" (e.g., steel, coal, cement) and "new industries" (e.g., new energy vehicles, lithium batteries)[22] - Focus should be on new industries with external demand, which may offer higher profit elasticity under similar supply-side adjustments[22] Group 3: Economic Implications and Risks - The stabilization of related industries will significantly aid macroeconomic structural adjustments and improve price factors, contributing to the overall elevation of the A-share market[23] - Risks include the potential underperformance of the orderly exit of backward production capacity, unexpected macroeconomic fluctuations, and unforeseen tariff disputes[28]

Market Update - The production and demand expectations for June show a marginal recovery, indicating a potential repair in profit factors [1][2] - In May, industrial enterprise profits weakened significantly due to a decline in both volume and price, leading to a faster decline in revenue growth [2] - The forward-looking indicator, June PMI, has slightly rebounded, suggesting a continuation of a strong production pattern [2] Inventory and Price Trends - In May, finished product inventory showed a marginal decline, primarily due to weak prices affecting nominal inventory [2] - The June PMI inventory sub-indices have shown varying degrees of recovery, aligning with the economic indicators that suggest a weak May but a recovery in June [2] - Short-term price pressures may have peaked, and the negative impact of base effects is expected to diminish in the second half of the year [2] Profitability Outlook - Entering July, profitability contributions are expected to improve, with the A-share market showing a rebound supported by positive valuation contributions [2] - The market currently undervalues profit factors, and the mid-year performance window in July-August may lead to a phase of recovery for profitability factors [2] - The market is anticipated to exhibit an upward oscillation trend in the second half of the year, supported by a favorable liquidity environment and improved macroeconomic expectations [2]

Group 1 - The core view of the report indicates that risk assets are expected to maintain relative advantages, with the profitability factor likely to recover [2][4][10] - The asset allocation model is an improved version of the Black-Litterman (BL) model, which combines market consensus with active views to optimize asset allocation and enhance the Sharpe ratio [3][5] - The model predicts that in the third quarter of 2025, the allocation ratio for domestic stocks will continue to increase while the bond allocation ratio will remain relatively high [10][11] Group 2 - In the A-share market, the profitability factor is expected to recover, and the advantage of small-cap stocks is likely to continue [2][17] - As of June 30, 2025, the market style performance for the second quarter showed strong results for small-cap and low-valuation factors, with weak profitability and weak reversal [13][16] - The report recommends focusing on indices such as the ChiNext Index, CSI A500, and CSI 2000, which exhibit high profitability and small-cap attributes [20][21]

Core Insights - The report highlights the sustained high demand for domestic computing power driven by ongoing U.S. restrictions on advanced chip imports, accelerating the domestic substitution process [3][7] - Domestic cloud service providers are increasing capital expenditures, gradually releasing industrial demand, while the iteration of domestic AI large models and applications is further boosting computing power needs [3][7] Industry Performance - The report provides a snapshot of market indices, with the Shanghai Composite Index closing at 3454.79, down 0.09%, and the Shenzhen Component Index at 10412.63, down 0.61% [4] - The performance of various sectors is noted, with steel up 3.37% and electronics down 2.01% [5] Key Focus Areas - The domestic computing power market is experiencing a boom, with Huawei's Ascend 910C servers being deployed in significant quantities, indicating a new phase in domestic computing commercialization [7] - The Ascend 910C chip boasts a single-chip computing power of 320 TFLOPS (FP16), designed for efficiency and low power consumption, suitable for AI tasks [7] - Major domestic internet companies are ramping up investments in AI infrastructure, with Alibaba planning to invest 380 billion RMB over three years, and Tencent's capital expenditure reaching 275 billion RMB in Q1 2025, up 91% year-on-year [8] Demand Drivers - The report notes that application-side inference is expected to drive demand growth, with significant increases in token usage reported by major companies like Alphabet and ByteDance [9] - The domestic supply side, including chips and supernode deployments, has achieved technological breakthroughs, which will lead to increased demand for computing power as industry applications evolve [9]