Quantitative Models and Construction Methods Model Name: Central Enterprise Innovation Index (000861.CSI) - **Model Construction Idea**: The index selects 100 representative listed companies under the State-owned Assets Supervision and Administration Commission (SASAC) based on their innovation and profitability to reflect the overall performance of innovative central enterprises[8] - **Model Construction Process**: - **Sample Space**: All listed companies under SASAC[9] - **Step 1**: Rank the securities in the sample space by average daily trading volume over the past year and exclude the bottom 20%[9] - **Step 2**: Select the remaining securities controlled by SASAC and its subsidiaries[9] - **Step 3**: Exclude securities with negative operating cash flow in the past year and negative net profit excluding non-recurring items in the past two years[9] - **Step 4**: Calculate the innovation score for non-financial companies based on R&D expenditure, R&D personnel ratio, patent quality score, and participation in national or industry standards. For financial companies, use revenue, net profit, patent quality score, and participation in standards[9] - **Step 5**: Rank the remaining securities by innovation score and select the top 50% as innovation-themed securities[9] - **Step 6**: Calculate the quality score for non-financial companies based on ROE, net profit growth, earnings quality, and financial leverage. For financial companies, use ROE and net profit growth. Combine the quality score with the scale score (based on market cap) to get a comprehensive score[9] - **Step 7**: Select the top 100 securities by comprehensive score as index samples[9] - **Adjustment**: The index samples are adjusted semi-annually[9] - **Model Evaluation**: The index is designed to reflect the performance of innovative central enterprises, with a focus on maintaining representativeness and accuracy through regular adjustments[8][9] Model Backtesting Results - **Central Enterprise Innovation Index**: - **Cumulative Return Since Inception**: 138.08%[5][10] - **Excess Return Over Major Indices**: - CSI 300: 79.25%[5] - SSE Composite Index: 83.67%[5] - CSI 500: 54.40%[5] - CSI 800: 74.09%[5] - **5-Year Cumulative Return**: 33.70%[10] - **Excess Return Over Major Indices in 5 Years**: - CSI 300: 49.24%[10] - SSE Composite Index: 29.47%[10] - CSI 800: 47.94%[10] Quantitative Factors and Construction Methods Factor Name: Innovation Score - **Factor Construction Idea**: Evaluate the innovation capability of non-financial and financial companies based on specific indicators[9] - **Factor Construction Process**: - **Non-Financial Companies**: - R&D expenditure to market cap ratio (40% weight) - R&D personnel ratio (10% weight) - Patent quality score (40% weight) - Participation in national or industry standards (10% weight)[9] - **Financial Companies**: - Revenue (40% weight) - Net profit (10% weight) - Patent quality score (40% weight) - Participation in national or industry standards (10% weight)[9] - **Calculation**: Sum the weighted scores to get the innovation score[9] Factor Name: Quality Score - **Factor Construction Idea**: Assess the financial quality of companies based on profitability and financial stability[9] - **Factor Construction Process**: - **Non-Financial Companies**: - ROE (30% weight) - Net profit growth (35% weight) - Earnings quality (25% weight) - Financial leverage (10% weight)[9] - **Financial Companies**: - ROE (50% weight) - Net profit growth (50% weight)[9] - **Calculation**: Sum the weighted scores to get the quality score[9] Factor Backtesting Results - **Innovation Score**: - **Top 50% Selection**: Used to identify innovation-themed securities[9] - **Quality Score**: - **Comprehensive Score Calculation**: Combined with scale score to select top 100 securities[9]

文/ 国家开发银行资金部总经理 谢志军 ，国家开发银行资金部市场发展处处长 周俊桃 深入研究美国贸易战历史，总结贸易战发动的深层次背景、措施过程、各 国应对方式以及对全球经济金融与国际治理体系的影响，对当前我国积极 应对此次中美贸易摩擦具有重要的意义。从全球治理与国际关系来看，贸 易战成为全球秩序重构的催化剂，大国博弈从均衡走向失衡，再去寻找新 的均衡。 美国历史上五次主要贸易战 镀金时代麦金莱系列关税（1890—1900） 第一阶段，1890年共和党推行《麦金莱关税法案》，所有进口商品平均税率提高至历史新高49.5%，提 高钢铁、纺织、锡板和羊毛等制成品的关税以保护国内产业。第二阶段，1894年民主党推出《威尔逊- 戈尔曼关税法案》，名义上降低部分关税，但贸易政策保护主义立场未显著改变。第三阶段，1897年共 和党总统麦金莱在美西战争前推出提高关税的《丁利关税法案》，关税功能从保护产业扩展到增加收入 资助战争，超高税率引发各国报复性关税，最终导致贸易战。 金融市场表现 麦金莱关税对金融市场产生强烈冲击。1888年至1890年5月，道琼斯平均指数处于牛市，而当市场预期 关税法案极有可能通过时，股市从1890年 ...

Quantitative Models and Construction Methods 1. Model Name: Genetic Programming Industry Rotation Model - **Model Construction Idea**: This model directly extracts factors from industry indices' price-volume and valuation data, updating the factor library at the end of each quarter. It selects the top five industries with the highest multi-factor composite scores for equal-weight allocation on a weekly basis[3][32] - **Model Construction Process**: - Factor extraction is performed on industry indices based on price-volume and valuation data - The factor library is updated quarterly - Weekly rebalancing is conducted, selecting the top five industries with the highest composite scores for equal-weight allocation[3][32] - **Model Evaluation**: The model achieved strong absolute and relative returns but exhibited rapid industry rotation, leading to slight underperformance against the benchmark in the previous week[3][32] 2. Model Name: Absolute Return ETF Simulated Portfolio - **Model Construction Idea**: Asset allocation weights are determined based on recent trends, with stronger-trending assets assigned higher weights. Equity allocation within the portfolio follows the monthly views of an industry rotation model[4][37] - **Model Construction Process**: - Asset classes are weighted based on recent trend strength - Equity allocation is determined by a monthly industry rotation model - The portfolio includes equity ETFs (e.g., dividend, healthcare, metals) and commodity ETFs (e.g., energy, soybean meal)[4][39] - **Model Evaluation**: The portfolio demonstrated stable performance with a focus on trend-following and diversification[4][37] --- Model Backtesting Results 1. Genetic Programming Industry Rotation Model - **Annualized Return**: 31.87% - **Annualized Volatility**: 18.18% - **Sharpe Ratio**: 1.75 - **Maximum Drawdown**: -19.63% - **Calmar Ratio**: 1.62 - **Year-to-Date (YTD) Return**: 28.68% - **Weekly Performance**: 3.03%[35] 2. Absolute Return ETF Simulated Portfolio - **Annualized Return**: 6.53% - **Annualized Volatility**: 3.82% - **Maximum Drawdown**: -4.65% - **Sharpe Ratio**: 1.71 - **Calmar Ratio**: 1.41 - **Year-to-Date (YTD) Return**: 5.58% - **Weekly Performance**: 0.33%[38] --- Quantitative Factors and Construction Methods 1. Factor Name: Market Intrinsic Momentum Indicators - **Factor Construction Idea**: These indicators measure the internal momentum of the market by analyzing the distribution of individual stock performance[18][19] - **Factor Construction Process**: - **Indicator 1**: Daily turnover difference between rising and falling stocks, normalized by total turnover $ \text{Indicator 1} = \frac{\text{Turnover of rising stocks - Turnover of falling stocks}}{\text{Total turnover}} $ - **Indicator 2**: Monthly high-low turnover difference, normalized by total turnover $ \text{Indicator 2} = \frac{\text{Turnover of stocks hitting monthly highs - Turnover of stocks hitting monthly lows}}{\text{Total turnover}} $ - **Indicator 3**: Six-month high-low turnover difference, normalized by total turnover $ \text{Indicator 3} = \frac{\text{Turnover of stocks hitting six-month highs - Turnover of stocks hitting six-month lows}}{\text{Total turnover}} $ - **Indicator 4**: Annual high-low turnover difference, normalized by total turnover $ \text{Indicator 4} = \frac{\text{Turnover of stocks hitting annual highs - Turnover of stocks hitting annual lows}}{\text{Total turnover}} $[18][19] - **Factor Evaluation**: These indicators effectively capture short-term and long-term market strength and provide strong signals for market trends[19] --- Factor Backtesting Results 1. Market Intrinsic Momentum Indicators - All four indicators showed upward trends in recent periods, aligning with the market's upward trajectory, indicating strong internal momentum supporting the index's rise[19]

Investment Rating - The industry investment rating is "Positive" [1] Core Viewpoints - The report highlights that factors such as anti-involution, stable growth, and the Yajiang Hydropower Station are collectively driving the steel equity market [1] Price Data Summary - The SW Steel Index is at 2,504, with a weekly increase of 7.7% and a year-to-date increase of 19.1% [3] - The price of rebar (HRB400 20mm) is 3,450 CNY/ton, reflecting a weekly increase of 5.5% and a year-to-date increase of 1.2% [3] - The iron ore price index is at 105 USD/ton, with a weekly increase of 4.3% and a year-to-date increase of 5% [3] Inventory Summary - Total social inventory of five major steel products is 926,000 tons, with a weekly change of 0.5% and a year-to-date change of 22% [5] - Total inventory at steel mills for five major products is 409,000 tons, with a weekly change of 1.1% and a year-to-date change of 16% [5] - Port inventory of iron ore is 13,794,000 tons, with a weekly change of 0.1% and a year-to-date change of 7% [5] Supply and Demand Summary - The weekly output of five major steel products is projected to be around 900,000 tons [9] - Daily average pig iron production is expected to reach approximately 240,000 tons [9] - The report indicates a steady demand for rebar, with apparent demand measured in ten thousand tons [14]

Group 1: Metal Sector - China Hongqiao's net profit forecast for 2024 is CNY 223.72 billion, with a PE ratio of 8.14[12] - Hualing Steel's net profit is projected to increase from CNY 20.32 billion in 2024 to CNY 28.54 billion in 2025, with a PE ratio of 19.72[12] - Xiamen Tungsten's net profit is expected to rise from CNY 17.28 billion in 2024 to CNY 21.01 billion in 2025, with a PE ratio of 22.97[12] Group 2: Construction and Transportation - Sichuan Road and Bridge's net profit is forecasted to grow from CNY 72.10 billion in 2024 to CNY 82.86 billion in 2025, with a PE ratio of 10.35[12] - YTO Express's net profit is expected to decrease from CNY 40.12 billion in 2024 to CNY 35.39 billion in 2025, with a PE ratio of 13.03[12] - China Merchants Highway's net profit is projected to be CNY 55 billion in 2025, with a PE ratio of 14.56[12] Group 3: Chemical and Energy Sector - Yara International's net profit is expected to rise from CNY 9.50 billion in 2024 to CNY 17.94 billion in 2025, with a PE ratio of 30.56[12] - Funiu Power's net profit forecast for 2025 is CNY 28.95 billion, with a PE ratio of 9.18[12] - Huajin's net profit is projected to recover to CNY 0.92 billion in 2025 after a loss of CNY 27.95 billion in 2024[12] Group 4: Strategic Metals and New Materials - Xiamen Tungsten's strategic metal segments are expected to contribute 79% to profits in 2024, with a focus on tungsten and rare earths[21] - Zhongcai Technology's special glass fiber is projected to see significant demand growth due to AI hardware requirements, with expected profits of CNY 0.2 billion in 2024[30] - The company anticipates a profit contribution from special glass fiber of CNY 7.2 billion by 2026[30]

南华期货焦煤焦炭周报 ——当头一棒 2025/07/27 南华研究院 黑色研究团队 张泫：Z0022723 投资咨询业务资格：证监许可【2011】1290号 周度观点 【盘面回顾】本周焦煤现货继续上涨，蒙5#原煤报价1050-1100元/吨，安泽低硫主焦报价1400-1450元/吨， 周内焦炭现货三轮提涨落地，周日焦化厂开启四轮提涨，预计下周一正式落地。周内双焦盘面经历暴涨爆 跌，价格波动极大，煤焦月差价差波动较大，JM9-1月差-59.5(-10)，J9-1月差-48(-3)。 【产业表现】 焦煤：国内方面，前期因环保、顶库等原因减停产的煤矿陆续复产，但复产速度偏慢。进口方面，本周口岸 蒙煤通关量900-1100车/天，通关已恢复正常。海煤进口利润持续改善，预计将体现在1-2月后的到港量上。 需求方面，盘面反弹带动期现投机需求，焦煤现货快速涨价，刺激下游焦化厂补充原料库存。期现锁货+刚需 采购提振煤焦短期需求，部分显性库存转移至表外，焦煤现货流动性收紧，库存结构明显改善。 焦炭：因现货焦煤疯狂涨价，焦化厂亏损幅度扩大，焦炭生产积极性一般。目前三轮提涨已经落地，焦企正 在争取第四轮提涨，现阶段钢材现货利润相当 ...

钢铁行业碳排放总量占全国15%左右，是占比最高的制造业，是实现工业节能降碳的重中之重。 "当前钢铁行业处于减量发展与深度转型时期，产业结构性矛盾问题依然突出，产品低端过剩、高端不足，行业节能降碳水平还有较大提升空间。"国家发展 改革委环资司二级巡视员金明红26日在2025（第十六届）钢铁行业节能减排大会上表示，全行业要持续优化产品结构，大力开展节能降碳减煤改造，推动产 业提质升级和绿色低碳转型。 作为支撑我国国民经济发展的基础性行业之一，钢铁行业碳排放总量占全国15%左右，是占比最高的制造业，是实现工业节能降碳的重中之重。 金明红说，"十四五"以来我国节能降碳工作取得了积极进展，构建了较为完备的政策制度体系，深入推进重点领域节能降碳，加快推动能源结构绿色低碳转 型，不断强化工作基础和能力建设。但也要清醒认识到，节能降碳形势依然严峻。 金明红表示，国家发展改革委将加强重点用能和碳排放单位管理，实施节能审查和碳排放评价全流程管理，持续完善政策体系和市场化机制，强化能力建 设，推动经济社会绿色低碳转型。 中国钢铁工业协会副会长兼秘书长姜维表示，面向机遇与挑战并存的"十五五"新征程，进一步推动钢铁行业形成"协同"的理 ...

Group 1 - South Korea has unexpectedly shifted its stance in handling China-US relations, imposing anti-dumping duties on China while showing intentions to engage in Taiwan Strait issues [1][3] - The cancellation of the scheduled US-Korea "2+2" economic talks did not deter the South Korean economic delegation from pursuing tariff negotiations, indicating a strong commitment to international trade cooperation [1][3] - South Korea's Ministry of Trade decided to impose temporary anti-dumping duties on hot-rolled steel plates and single-mode optical fibers from China, aiming to protect domestic industries during formal investigations [3][4] Group 2 - The economic relationship between China and South Korea is closely intertwined, and the imposition of anti-dumping duties by South Korea could disrupt normal trade and cooperation between the two countries [4][6] - Analysts suggest that while South Korea may increase military spending, the likelihood of direct involvement in Taiwan Strait affairs remains low, although vigilance is necessary due to potential trade-offs with the US [6] - China has expressed strong opposition to any actions that sacrifice its interests for US concessions, indicating readiness to take decisive measures to protect its rights in the international trade environment [6]

Core Viewpoint - The U.S. Department of Commerce has preliminarily determined that Oman is circumventing anti-dumping and countervailing duties on similar products from China by using hot-rolled steel produced in China to manufacture circular welded carbon steel pipes (CWP) [1][3]. Group 1: Investigation and Findings - The investigation began on November 19, 2024, focusing on circumvention activities across Oman, with Al Jazeera Steel Products Company SAOG identified as the mandatory respondent [3]. - The average anti-dumping duty rate for Chinese CWP is 85.55%, while the countervailing duty rate is as high as 198.49% [3]. - The U.S. has intensified scrutiny on imported steel products, particularly those processed through third countries to evade tariffs [3][4]. Group 2: Market Impact - In 2024, the U.S. imported approximately 50,000 tons of CWP from Oman, accounting for 2.5% of total imports, with Chinese hot-rolled steel remaining competitive in the global market due to price advantages [4]. - The preliminary ruling may lead to the imposition of tariffs on Omani CWP similar to those on Chinese products, potentially exceeding 200%, which would significantly raise export costs for Oman and affect its competitiveness in the U.S. market [5]. - U.S. domestic steel producers like Nucor and Steel Dynamics may benefit from this situation as their market share could increase [5]. Group 3: Broader Context - The global steel market is currently facing an oversupply situation, with low-priced steel from China entering the U.S. market through third countries, leading to ongoing trade disputes [5]. - Similar circumvention issues have been observed in global trade, with countries like Vietnam and Thailand also facing investigations by the U.S. [4].

Group 1 - The Yarlung Tsangpo River downstream hydropower project has officially commenced with a total investment of 1.2 trillion yuan, planning to build five hydropower stations, with an annual power generation capacity equivalent to three times that of the Three Gorges Dam, which is expected to stimulate related theme ETFs [1] Group 2 - Various ETFs including construction materials ETF, infrastructure 50 ETF, and chemical ETF have seen increases this week, with over 1 billion yuan net inflow into 43 funds, including steel ETF and construction materials ETF, which have net inflows of 14.24 billion yuan and 11.05 billion yuan respectively [2] - The construction materials ETF tracks the CSI All Share Construction Materials Index, covering sectors such as cement (44.8%), decoration materials (35.3%), and glass fiber (10%), with key stocks benefiting from the Yarlung Tsangpo River project [2] - The infrastructure ETF tracks the CSI Infrastructure Index, encompassing the infrastructure and engineering machinery industry chain [3] - The steel ETF tracks the CSI Steel Index, covering iron ore mining, steel smelting, and processing, aiming to reflect the overall performance of steel-related companies in the A-share market [4] - The chemical ETF tracks the CSI Subdivided Chemical Industry Theme Index, covering various chemical sectors, with leading stocks including Wanhua Chemical and Salt Lake Shares [4] Group 3 - The "anti-involution" policy is expected to optimize the industry landscape, with leading companies likely to see a turning point in profitability, particularly in sectors like steel, glass fiber, and new energy chains, which are currently at historical lows in profitability and capital expenditure [5] - The market is experiencing significant activity with daily trading volume reaching nearly 1.9 trillion yuan, driven by liquidity and policy deployment, with optimistic expectations being rapidly priced in [6] - The main market themes currently revolve around "anti-involution" and large infrastructure projects, with opportunities identified in power equipment, resource products, and construction materials sectors [6] - The "anti-involution" policy is anticipated to bring positive changes to the industry chain, potentially reshaping competitive dynamics and leading to price recovery in some high-end manufacturing sectors [7]