格隆汇8月27日｜A股三大指数早盘集体上涨，截至午盘，沪指涨0.33%，深成指涨1.34%，指涨2.41%，北证50指数跌0.03%，沪深京三市半日成交额17463 亿元，较上日放量469亿元。全市场超2200只个股上涨。板块题材方面，半导体、CPO、AI眼镜、液冷服务器等AI产业链板块领涨；白酒、煤炭、教育、板 块跌幅居前。 ETF方面，人工智能产业链爆了！银华基金科创板人工智能ETF、AIETF富国、博时基金科创AIETF和科创人工智能ETF华夏分别涨7.66%、7.48%、7.42%和 7.36%。芯片板块全线回暖，国联安基金科创芯片设计ETF、嘉实基金科创芯片ETF分别涨6.74%和5.77%。 创新药板块继续回调，恒生创新药ETF、港股通创新药ETF和港股通创新药ETF工银分别跌2.03%、1.84%和1.83%。白酒板下挫，酒ETF跌1.59%。房地产板 块走低，房地产ETF基金跌1.21%。 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容的准确性、可靠性或完整性提供任何明 示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱：news ...

Market Overview - The three major A-share indices collectively rose, with the Shanghai Composite Index up 0.3% to 3739.26 points, the Shenzhen Component Index up 0.3%, and the ChiNext Index up 0.39% [1] - The North China 50 Index increased by 3.16%, reaching a new historical high during the session [1] - The total trading volume in the Shanghai and Shenzhen markets was 16,781 billion yuan, a decrease of 686 billion yuan from the previous day, with over 3,200 stocks rising [1] Sector Performance - The liquor sector saw a comprehensive increase, with stocks like JiuGuiJiu hitting the daily limit and SheDe JiuYe rising over 7% [1] - Various ETFs related to liquor and food and beverage sectors also experienced gains, with the liquor ETF tracking the CSI Liquor Index rising by 1.88% [3][4] Company Financials - Yanghe Brewery reported a 35.32% year-on-year decline in revenue for the first half of 2025, totaling 14.796 billion yuan, with a net profit drop of 45.34% to 4.344 billion yuan [4] - Kweichow Moutai's revenue for the first half of 2025 was 89.389 billion yuan, a 9% increase year-on-year, with a net profit of 45.403 billion yuan, also up 9% [4] Industry Trends - The liquor industry is currently undergoing a destocking cycle, facing multiple pressures from pricing, demand, and policy [5] - Despite challenges, Moutai's pricing has stabilized, and the company is expected to achieve its annual revenue targets through refined marketing strategies [5] Consumer Goods Insights - The consumer goods sector is entering a period of intensive mid-year report disclosures, with companies like Anqi Yeast and Weilong achieving revenue growth of 10% and 19% respectively in the first half of 2025 [5] - The industry is witnessing a shift towards new retail formats and consumer preferences for health and convenience, presenting growth opportunities in categories like snacks and low-alcohol beverages [6]

证券研究报告：金融工程报告 研究所 分析师:肖承志 SAC 登记编号:S1340524090001 Email:xiaochengzhi@cnpsec.com 研究助理:李子凯 SAC 登记编号:S1340124100014 Email:lizikai@cnpsec.com 近期研究报告 《OpenAI 发布 GPT-5，Claude Opus 4.1 上线——AI 动态汇总 20250811》 - 2025.08.12 《融资余额新高，创新药光通信调整， 指数预期仍将震荡上行挑战前高—— 行业轮动周报 20250810》 - 2025.8.11 《ETF 资金偏谨慎流入消费红利防守， 银行提前调整使指数回调空间可控— — 行 业 轮 动 周 报 20250803 》 - 2025.08.04 《ETF 资金持续净流出医药，雅下水电 站成短线情绪突破口——行业轮动周 报 20250727》 – 2025.07.28 《ETF 资金净流入红利流出高位医药， 指数与大金融回调有明显托底——行 业轮动周报 20250720》 – 2025.07.21 《大金融表现居前助指数突破，GRU 行 业轮动调入非银行金融—— ...

Report Summary 1. Report Industry Investment Rating - Not provided in the given content 2. Core Viewpoints of the Report - The strategy is based on the research reports "Strategy Portfolio Report under Industry Rotation: Quantitative Analysis from the Perspective of Industry Style Continuity and Switching" (20241007) and "Research on the Overview and Allocation Methods of the Stock - type ETF Market: Taking the ETF Portfolio Based on the Industry Rotation Strategy as an Example" (20241013) to construct a strategy portfolio of industry and theme ETFs [2] - In the week of 20250811, the model recommends allocating sectors such as joint - stock banks, games, and semiconductors. In the next week, the strategy will newly hold products like Game ETF, Science and Technology Innovation Chip Design ETF, and Satellite ETF, and continue to hold products like Bank ETF, Financial Real Estate ETF, and Gold Stock ETF [2] - As of last weekend, some ETFs and the trading timing signals of the underlying indexes gave daily or weekly risk warnings [2] 3. Summary by Relevant Catalogs Performance Tracking - During the period from 20250804 to 20250808, the cumulative net return of the strategy was about 2.62%, and the excess return relative to the CSI 300 ETF was about 1.41% [3] - From October 14, 2024, to the present, the cumulative out - of - sample return of the strategy was about 7.08%, and the cumulative excess relative to the CSI 300 ETF was about - 0.79% [3] Future 1 - Week Recommended ETFs (20250811 - 20250815) | Fund Code | ETF Name | Holding Status | ETF Market Value (billion yuan) | Heavy - Positioned Shenwan II Industry and Weight | Weekly Timing Signal | Daily Timing Signal | | --- | --- | --- | --- | --- | --- | --- | | 512800 | Bank ETF | Continue to hold | 151.38 | Joint - stock banks (44.73%) | 1 | - 1 | | 159869 | Game ETF | Transfer in | 73.17 | Games (81.29%) | 1 | 1 | | 588780 | Science and Technology Innovation Chip Design ETF | Transfer in | 2.77 | Semiconductors (95.73%) | 1 | 1 | | 159940 | Financial Real Estate ETF | Continue to hold | 7.99 | Securities (29.12%) | 1 | - 1 | | 517520 | Gold Stock ETF | Continue to hold | 46.34 | Precious metals (41.51%) | 1 | 1 | | 510000 | Central Enterprise ETF | Continue to hold | 1.21 | State - owned large - scale banks (18.11%) | 1 | 1 | | 512690 | Wine ETF | Continue to hold | 152.39 | Baijiu (85.37%) | - 1 | - 1 | | 159206 | ZETF | Transfer in | 1.33 | Military electronics II (34.22%) | 1 | 1 | | 159786 | VRETF | Transfer in | 1.32 | Optoelectronics (26.64%) | 1 | 1 | | 159652 | Non - ferrous 50 ETF | Transfer in | 5.21 | Industrial metals (49.34%) | 1 | 1 | [9] Near 1 - Week ETF Holdings and Performance (20250804 - 20250808) | Fund Code | Current Holding Status | ETF Name | ETF Market Value (billion yuan) | Near 1 - Week Increase/Decrease (%) | | --- | --- | --- | --- | --- | | 562550 | - | Green Power ETF | 1.21 | 1.50 | | 512800 | Continue to hold | Bank ETF | 151.38 | 1.99 | | 512690 | Continue to hold | Wine ETF | 152.39 | 1.06 | | 159768 | - | Real Estate ETF | 6.13 | 2.14 | | 159940 | Continue to hold | Financial Real Estate ETF | 7.99 | 1.41 | | 515220 | Transfer out | Coal ETF | 80.20 | 3.78 | | 159996 | Transfer out | Home Appliance ETF | 12.72 | 2.55 | | 510060 | Continue to hold | Central Enterprise ETF | 1.21 | 1.42 | | 516550 | Transfer out | Agricultural ETF | 1.87 | 1.76 | | 517520 | Continue to hold | Gold Stock ETF | 46.34 | 8.91 | | - | ETF Portfolio Average Return | - | - | 2.62 | | 510300 | - | CSI 300 ETF | 3819.72 | 1.21 | | - | ETF Portfolio Excess Return | - | - | 1.41 | [10]

Core Viewpoint - The ETF market is experiencing a shift from broad-based products to sector-specific investments, with significant outflows from broad-based ETFs and inflows into thematic ETFs, indicating changing investor preferences [2][5][8]. Group 1: ETF Market Trends - As of August 5, stock ETFs have seen a net outflow of 628 billion yuan over the past month, marking a decline below 1 trillion units for the first time since October of the previous year [2][5]. - Broad-based ETFs, particularly those tracking the CSI A500 index, have faced severe redemption pressures, with only one out of 38 products seeing net inflows [5][6]. - In contrast, thematic ETFs have attracted 176 billion yuan in net inflows, with sectors like dividends, banking, and coal being popular among investors [2][6]. Group 2: Market Dynamics - The ETF market, valued at 4.64 trillion yuan, is characterized by a significant concentration of assets, with the top ten firms controlling nearly 80% of the market share [2][8]. - Major players like Huaxia and E Fund have seen their ETF scales increase by over 100 billion yuan this year, while many smaller firms struggle to reach 10 billion yuan [2][8]. - The competitive landscape is intensifying, with many mid-sized firms facing high resource and cost barriers, leading to a "war of attrition" in the market [3][9]. Group 3: Investor Behavior - Investors are shifting their focus from broad-based ETFs to sector-specific products, reflecting a desire for more targeted investment strategies during market fluctuations [7][10]. - The trend indicates that investors are looking for higher returns through short-term trading in strong sectors, rather than relying on the broader market [7][10]. Group 4: Challenges for Fund Companies - The ETF business, while seen as a growth avenue, presents significant resource and cost challenges, particularly for smaller firms [9][10]. - The high costs associated with system maintenance, marketing, and operations make it difficult for smaller companies to compete effectively in the ETF space [9][10]. - Despite these challenges, some mid-sized firms are beginning to re-evaluate their strategies and invest in ETF capabilities to capture market opportunities [10].

Group 1 - The core viewpoint of the article highlights the trading activity of the liquor ETF (512690) on August 4, with a financing buy amount of 0.53 billion yuan, ranking 320th in the market [1] - Over the recent three trading days from July 31 to August 4, the liquor ETF experienced financing buys of 1.47 billion yuan, 0.74 billion yuan, and 0.53 billion yuan respectively [1] Group 2 - On the same day, the short selling activity recorded a sell of 515,600 shares, resulting in a net sell of 188,200 shares [2]

Strategy Overview - The report focuses on constructing a strategy portfolio based on industry and thematic ETFs, utilizing quantitative analysis from previous strategy reports [2]. Strategy Update - For the week of August 4, 2025, the model recommends increasing allocations to sectors such as electricity, joint-stock banks, and liquor, while continuing to hold real estate and agriculture ETFs [2]. - New additions include Green Power ETF, Bank ETF, and Liquor ETF, with ongoing holdings in Real Estate ETF and Agriculture ETF [2]. - As of the last weekend, some ETFs and index trading timing signals provided daily or weekly risk alerts [2]. Performance Tracking - From July 28 to August 1, 2025, the strategy recorded a cumulative net return of approximately -2.19%, with an excess return of about -0.53% compared to the CSI 300 ETF [2]. - Since October 14, 2024, the cumulative return of the strategy outside the sample period is approximately 4.34%, with an excess return of about -2.17% relative to the CSI 300 ETF [2].

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[26][39] - **Model Construction Process**: The diffusion index is calculated for each industry, reflecting the proportion of stocks within the industry that exhibit positive momentum. The index ranges from 0 to 1, where higher values indicate stronger momentum. The model selects industries with the highest diffusion indices for allocation. For example, as of August 1, 2025, the top-ranked industries included Steel (1.0), Comprehensive Finance (1.0), and Non-Banking Finance (0.999)[27][28] - **Model Evaluation**: The model has shown mixed performance over the years. While it achieved significant excess returns in 2021 (up to 25% before September), it experienced notable drawdowns in 2023 (-4.58%) and 2024 (-5.82%) due to its inability to adjust to market reversals[26] 2. Model Name: GRU Factor Model - **Model Construction Idea**: This model leverages GRU (Gated Recurrent Unit) deep learning networks to process high-frequency volume and price data, aiming to identify industry rotation opportunities[40] - **Model Construction Process**: The GRU network is trained on historical minute-level data to predict industry factor rankings. The model then allocates to industries with the highest predicted rankings. As of August 1, 2025, the top-ranked industries included Non-Banking Finance (-1.15), Steel (0.7), and Base Metals (0.5)[34][38] - **Model Evaluation**: The model has demonstrated strong adaptability in short-term scenarios but struggles in long-term or extreme market conditions. Its performance in 2025 has been hindered by concentrated market themes, resulting in difficulty capturing inter-industry excess returns[33][40] --- Backtesting Results of Models 1. Diffusion Index Model - **Weekly Average Return**: -1.67%[30] - **Excess Return (August)**: -0.44%[30] - **Excess Return (2025 YTD)**: -0.40%[25][30] 2. GRU Factor Model - **Weekly Average Return**: 0.00%[38] - **Excess Return (August)**: 0.16%[38] - **Excess Return (2025 YTD)**: -2.35%[33][38] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: Measures the breadth of positive momentum within an industry[27] - **Factor Construction Process**: The diffusion index is calculated as the proportion of stocks in an industry with positive momentum. For example, as of August 1, 2025, the diffusion index for Steel was 1.0, while for Coal it was 0.23[27][28] - **Factor Evaluation**: The factor effectively identifies industries with strong upward trends but may underperform during market reversals[26] 2. Factor Name: GRU Industry Factor - **Factor Construction Idea**: Utilizes GRU deep learning to rank industries based on high-frequency trading data[40] - **Factor Construction Process**: The GRU network processes minute-level volume and price data to generate factor rankings. For instance, as of August 1, 2025, the GRU factor for Non-Banking Finance was -1.15, while for Steel it was 0.7[34][38] - **Factor Evaluation**: The factor is effective in capturing short-term trends but struggles in long-term or highly volatile markets[33][40] --- Backtesting Results of Factors 1. Diffusion Index Factor - **Top Industries (August 1, 2025)**: Steel (1.0), Comprehensive Finance (1.0), Non-Banking Finance (0.999)[27][28] - **Weekly Average Return**: -1.67%[30] - **Excess Return (August)**: -0.44%[30] - **Excess Return (2025 YTD)**: -0.40%[25][30] 2. GRU Industry Factor - **Top Industries (August 1, 2025)**: Non-Banking Finance (-1.15), Steel (0.7), Base Metals (0.5)[34][38] - **Weekly Average Return**: 0.00%[38] - **Excess Return (August)**: 0.16%[38] - **Excess Return (2025 YTD)**: -2.35%[33][38]

Core Insights - As of July 30, the total inflow of funds into ETFs reached 190.857 billion, while outflows amounted to 176.103 billion, resulting in a net inflow of 14.755 billion [1] Fund Inflows - The non-money market ETFs with the highest net inflows were: - Southern CSI A500 ETF (159352) with a net inflow of 0.527 billion - A500 Fund (563360) with a net inflow of 0.350 billion - Liquor ETF (512690) with a net inflow of 0.328 billion [1] Fund Outflows - The non-money market ETFs with the highest net outflows were: - Huaxia SSE STAR 50 ETF (588000) with a net outflow of 0.818 billion - E Fund CSI Hong Kong Securities Investment Theme ETF (513090) with a net outflow of 0.571 billion - Huaxia Hang Seng Technology ETF (QDII) (513180) with a net outflow of 0.540 billion [1]

Core Insights - As of July 28, the net decrease in ETF shares across the two markets was 2.809 billion shares [1] - Notable increases in shares were observed in specific ETFs: Huabao Zhongzheng Bank ETF (512800) increased by 11.422 billion shares, Huaxia Shanghai Stock Exchange Sci-Tech Innovation Board 50 Component ETF (588000) increased by 9.392 billion shares, and Wine ETF (512690) increased by 6.969 billion shares [1] ETF Market Overview - The overall trend indicates a significant net reduction in ETF shares, suggesting a potential shift in investor sentiment or market conditions [1] - The increase in shares for specific ETFs may indicate a targeted investment strategy focusing on market leaders and sectors poised for rebound [1]