Group 1: Report Industry Investment Rating - Not provided in the content Group 2: Core Viewpoints of the Report - In the secondary market, during the sample period from August 18 - 22, 2025, the top - performing A - share and overseas major broad - based indices were科创50, ChiNext Index, and CSI 300, with weekly returns of 13.31%, 5.85%, and 4.18% respectively. Among Shenwan primary industries, communication, electronics, and comprehensive had the highest returns at 10.84%, 8.95%, and 8.25%, while real estate, coal, and pharmaceutical biology had lower returns at 0.50%, 0.92%, and 1.05% respectively [1][10][17]. - Regarding ETF product performance, during the sample period, broad - based ETFs had the best average performance with a weighted average return of 5.12%, while QDII ETFs had the worst with - 0.61%. In terms of the listing board, ETFs related to the Science and Technology Innovation Board and the Science and Technology Innovation and Entrepreneurship 50 had better performance, with weighted average returns of 13.01% and 10.85% respectively. US and Japanese stock ETFs had poor performance, with - 2.78% and - 2.65% respectively [21]. - For ETF fund flows, industry - themed ETFs had the largest net capital inflow of 254.09 billion yuan, and broad - based ETFs had the smallest at - 161.16 billion yuan. From the perspective of the listing board, Hong Kong stock ETFs had the largest net inflow of 214.47 billion yuan, and Science and Technology Innovation Board - related ETFs had the smallest at - 144.18 billion yuan [2][25]. Group 3: Summary by Relevant Catalogs 1. Secondary Market Overview - Index returns: During the sample period,科创50, ChiNext Index, and CSI 300 had the highest weekly returns at 13.31%, 5.85%, and 4.18% respectively. The PE valuation quantile of CSI 300 was the highest at 100.00%, and that of the Nikkei 225 was the lowest at 73.36% [10]. - Industry returns: Among Shenwan primary industries, communication, electronics, and comprehensive had the highest returns at 10.84%, 8.95%, and 8.25%, while real estate, coal, and pharmaceutical biology had lower returns at 0.50%, 0.92%, and 1.05% respectively. In terms of valuation, social services, light manufacturing, and building materials had the highest valuation quantiles at 100.00%, and agriculture, forestry, animal husbandry and fishery, household appliances, and comprehensive had lower quantiles at 35.12%, 55.37%, and 62.81% respectively [17]. 2. ETF Product Overview 2.1 ETF Market Performance - By product type: Broad - based ETFs had the best average performance with a weighted average return of 5.12%, and QDII ETFs had the worst with - 0.61%. - By listing board: ETFs related to the Science and Technology Innovation Board and the Science and Technology Innovation and Entrepreneurship 50 had better performance, with weighted average returns of 13.01% and 10.85% respectively. US and Japanese stock ETFs had poor performance, with - 2.78% and - 2.65% respectively. - By industry sector: Technology sector ETFs had the best average performance with a weighted average return of 12.53%, and biomedical sector ETFs had the worst with 1.55%. - By theme: Chip semiconductor and artificial intelligence ETFs had better performance, with weighted average returns of 15.09% and 14.57% respectively. Bank and dividend ETFs had relatively poor performance, with 0.91% and 1.10% respectively [21][23]. 2.2 ETF Fund Flows - By category: Industry - themed ETFs had the largest net capital inflow of 254.09 billion yuan, and broad - based ETFs had the smallest at - 161.16 billion yuan. - By listing board: Hong Kong stock ETFs had the largest net inflow of 214.47 billion yuan, and Science and Technology Innovation Board - related ETFs had the smallest at - 144.18 billion yuan. - By industry sector: Financial and real estate sector ETFs had the largest net inflow of 141.32 billion yuan, and technology sector ETFs had the smallest at - 53.84 billion yuan. - By theme: Non - bank and innovative drug ETFs had the largest net inflows of 142.21 billion yuan and 31.74 billion yuan respectively. Chip semiconductor and military - industry ETFs had the smallest at - 78.85 billion yuan and - 5.73 billion yuan respectively [2][25][28]. 2.3 ETF Trading Volume - By category: Broad - based ETFs had the largest increase in the average daily trading volume change rate at 27.34%, and commodity ETFs had the largest decrease at - 28.91%. - By listing board: CSI 500 ETFs had the largest increase in the average daily trading volume change rate at 76.67%, and Japanese stock ETFs had the largest decrease at - 15.32%. - By industry sector: The consumer sector had the largest increase in the average daily trading volume change rate at 48.26%, and the biomedical sector had the largest decrease at - 5.57%. - By theme: Non - bank and innovative drug ETFs had the highest average daily trading volumes in the past 5 days at 367.55 billion yuan and 104.62 billion yuan respectively. Consumer electronics and artificial intelligence ETFs had the largest increases in the average daily trading volume change rate at 52.58% and 38.65% respectively. Central state - owned enterprises and innovative drug ETFs had the largest decreases at - 8.12% and - 7.01% respectively [34][37][40][43]. 2.4 ETF Margin Trading - During the sample period, the net margin purchase of all equity ETFs was - 2.48 billion yuan, and the net short - selling was 2.32 billion yuan. Southern CSI 500 ETF had the largest net margin purchase, and Southern CSI 1000 ETF had the largest net short - selling [2][48]. 2.5 ETF New Issuance and Listing - During the sample period, 9 funds were established and 8 funds were listed [3][50].

证券研究报告|金融工程研究报告 [Table_Date] 2025 年 8 月 24 日 [Table_Title] 一周市场数据复盘 20250822 [Table_Summary] ► 宽基指数表现 上周市场普遍上涨，科创 50、创业板指和沪深 300 指数 涨幅较大，分别上涨 13.31%、5.85%和 4.18%。 今年以来小盘风格延续强势，中证 2000、科创 50 指数 涨跌幅居前，分别为 33.13%、26.18%。 ► 行业指数表现 上周涨幅最大的行业是通信、电子和计算机，分别上涨 10.84%、8.95%和 7.93%。 今年以来通信、有色金属行业表现最好，分别上涨 44.91%、38.6%。 PE 分位数达 100%的行业包括国防军工、计算机、机械 设备、电子、商贸零售、建筑材料；PE 分位数最低的三个行 业是食品饮料、农林牧渔、公用事业，分别为 15%、16%、 40%。 ► 行业拥挤度 我们使用行业指数最近一周价格和成交金额变动的马氏 距离衡量拥挤度。 上周家用电器和有色金属行业出现短期显著拥挤。 评级及分析师信息 [Table_Author] 分析师：丁睿雯 邮箱：dingrw@hx ...

每经记者｜叶峰 每经编辑｜赵云 本周股指集体上涨，沪深两市股票型ETF和跨境型ETF合计净流入约200亿元。 行业主题上看，证券、化工、金融科技等ETF被资金看好，而芯片相关ETF被资金抛售。 约200亿元资金借道ETF进场 本周沪深两市成交12.73万亿元，其中沪市成交5.3万亿元，深市成交7.43万亿元。截至最新收盘，沪指报收于3825.76点，全周上涨3.49%，深证成指报收于 12166.06点，全周上涨4.57%。 | 证券代码 | 证券简称 | 收盘价 | | 周涨跌幅 周份额变化 周资金净流入额 | | ETFJ | | --- | --- | --- | --- | --- | --- | --- | | | | (元) | (%) | (亿份) | (亿元) | (亿元 | | 510300.SH 沪深300ETF | | 4.48 | 4.28 | -2.96 | -12.11 | 408 | | 510310.SH 沪深300ETF易方达 | | 4.33 | 4.31 | -1.65 | -6.83 | 290 | | 510330.SH 沪深300ETF华夏 | | 4.54 | 4 ...

Core Viewpoint - The article discusses the challenges and considerations of identifying "mainline sectors" during a bull market, suggesting that broad-based indices may be a more pragmatic choice for most investors [4][6][18]. Group 1: Mainline Investment Temptation and Identification Challenges - In bull markets, mainline sectors often yield significant excess returns, with data showing that in 2020, the top three industry indices had returns of 190.96%, 138.41%, and 135.19%, while the CSI 300 index only rose by about 27.21% [6][7]. - The difficulty of accurately identifying mainline sectors beforehand is highlighted, as many investors may only realize what the mainline was after the market has moved [8][10]. Group 2: Real Obstacles in Mainline Identification - Three main obstacles to identifying mainline sectors are discussed: 1. Extreme internal differentiation within industries complicates stock selection, as seen in the 2025 market where the ground equipment sector had a 103.73% annual increase, but individual stocks within the sector varied significantly in performance [10]. 2. The acceleration of valuation bubbles poses greater risks than broad indices, as high valuations can lead to significant corrections if industry progress does not meet expectations [10][11]. 3. Behavioral biases can interfere with investment discipline, leading to premature profit-taking or overconfidence, which can result in substantial losses [11]. Group 3: Unique Value of Broad-Based Indices - Broad-based indices offer unique advantages in risk diversification, stable returns, and operational convenience. They provide a better risk-return ratio through cross-industry and cross-market capitalization allocation [12][13]. - Historical data shows that broad-based indices like the CSI 300 had significantly lower maximum drawdowns compared to industry indices during bull and bear markets [13][15]. - The operational convenience of broad-based indices is enhanced by a well-established ecosystem of investment tools, such as ETFs, which lower the barriers for non-professional investors [16]. Group 4: Conclusion and Strategy - The article concludes that while broad-based indices may not outperform leading mainline sectors, they are often a better choice for ordinary investors due to their ability to mitigate emotional trading and provide stable returns [18][19]. - A suggested investment strategy for ordinary investors is the "core-satellite" approach, allocating 60%-80% of the portfolio to broad-based ETFs to capture market beta, while using 20%-40% for selective participation in mainline sectors to manage risk exposure [19].

Core Viewpoint - The article discusses the fluctuations of the Shanghai Composite Index around the 3700-point mark, highlighting its psychological significance and the differences in market conditions compared to previous years. It emphasizes that despite the index's stagnation, the total return index has shown significant growth, indicating underlying investment opportunities [3][4][5]. Group 1: Index Performance - The Shanghai Composite Index briefly surpassed 3700 points but closed at 3666.44 points, indicating a struggle to maintain this level [3][4]. - The index has shown a slight increase of 0.31% from 3655.09 points to 3666.44 points, but the total return index has increased by 13.73% from 3666.87 points to 4170.49 points, reflecting better investment performance [7][8]. - The largest ETFs tracking the Shanghai Composite Index have surpassed their values from February 2021, indicating strong performance despite the index's struggles [10]. Group 2: Changes in Index Composition - The composition of the Shanghai Composite Index has changed significantly over the past four and a half years, with 72 stocks exiting and 763 new stocks entering, resulting in a total of 2232 constituent stocks [12][15]. - The weight of the electronics sector has increased from 4.45% to 9.47%, while the food and beverage sector has seen a significant decrease from 12.41% to 5.49% [18][19]. Group 3: Sector Contributions - The banking sector has contributed significantly to the index's performance, with a weight increase from 16.04% to 18.52%, while the food and beverage sector has been a major drag on performance [18][19][31]. - The top-performing sectors include coal (178% increase), oil and petrochemicals (116% increase), and banking (78% increase), while the worst-performing sectors include social services (-73%), beauty and personal care (-50%), and food and beverage (-42%) [30][31]. Group 4: Key Stocks Impacting the Index - Key stocks such as Agricultural Bank, Industrial and Commercial Bank, and China Petroleum have significantly influenced the index's performance, contributing to a rise of 14.64% if excluded from the analysis [32][33]. - Conversely, stocks like Kweichow Moutai and China Duty Free have negatively impacted the index, suggesting a substantial influence of individual stocks on overall performance [32][33].

- The report tracks various types of ETFs on a daily basis, categorizing them into "broad-based" and "thematic" ETFs based on the indices they track, such as CSI 300, CSI 500, and industry/style indices like non-bank financials and dividends[2] - The RSI (Relative Strength Index) is calculated using the formula: $ RSI = 100 - 100 / (1 + RS) $, where RS is the average gain divided by the average loss over a 12-day period. RSI values above 70 indicate an overbought market, while values below 30 indicate an oversold market[2] - The net subscription amount is calculated using the formula: $ NETBUY(T) = NAV(T) - NAV(T-1) * (1 + R(T)) $, where NETBUY(T) is the net subscription amount, NAV(T-1) is the ETF's net asset value from the previous trading day, and R(T) is the return on the current day[2] Quantitative Models and Construction Methods 1. **Model Name: RSI (Relative Strength Index)** - **Construction Idea**: Measures the speed and change of price movements to identify overbought or oversold conditions - **Construction Process**: - Calculate the average gain and average loss over a 12-day period - Compute the RS (Relative Strength) as the ratio of average gain to average loss - Apply the formula: $ RSI = 100 - 100 / (1 + RS) $ - **Evaluation**: Useful for identifying potential reversal points in the market[2] 2. **Model Name: Net Subscription Amount** - **Construction Idea**: Measures the net inflow or outflow of funds into an ETF - **Construction Process**: - Calculate the net asset value (NAV) of the ETF for the current and previous trading days - Compute the return (R) for the current day - Apply the formula: $ NETBUY(T) = NAV(T) - NAV(T-1) * (1 + R(T)) $ - **Evaluation**: Indicates investor sentiment and fund flow dynamics[2] Model Backtesting Results 1. **RSI Model** - **Indicator Values**: - CSI 300 ETFs: RSI values range from 69.68 to 75.23 - CSI 500 ETFs: RSI values range from 74.47 to 75.37 - CSI 800 ETFs: RSI values range from 73.39 to 77.74 - CSI 1000 ETFs: RSI values range from 77.70 to 78.26 - CSI A50 ETFs: RSI values range from 65.77 to 67.30 - CSI A500 ETFs: RSI values range from 74.12 to 75.83 - STAR 50 ETFs: RSI values range from 75.53 to 77.78 - GEM ETFs: RSI values range from 76.39 to 77.42 - Hang Seng ETFs: RSI values range from 56.98 to 61.45 - Nikkei 225 ETFs: RSI values range from 72.84 to 72.88 - Nasdaq 100 ETFs: RSI values range from 65.70 to 68.11 - Other overseas broad-based indices: RSI values range from 33.64 to 60.46[4][6] 2. **Net Subscription Amount Model** - **Indicator Values**: - CSI 300 ETFs: Net subscription amounts range from -3.97 billion to 7.87 billion - CSI 500 ETFs: Net subscription amounts range from -0.08 billion to 4.57 billion - CSI 800 ETFs: Net subscription amounts range from -0.06 billion to 5.86 billion - CSI 1000 ETFs: Net subscription amounts range from 0.44 billion to 2.21 billion - CSI A50 ETFs: Net subscription amounts range from -0.89 billion to -0.08 billion - CSI A500 ETFs: Net subscription amounts range from -0.13 billion to 0.38 billion - STAR 50 ETFs: Net subscription amounts range from -5.00 billion to 0.02 billion - GEM ETFs: Net subscription amounts range from -0.86 billion to 5.64 billion - Hang Seng ETFs: Net subscription amounts range from -0.82 billion to 0.02 billion - Nikkei 225 ETFs: Net subscription amounts range from -0.21 billion to -0.06 billion - Nasdaq 100 ETFs: Net subscription amounts range from -1.34 billion to -0.47 billion - Other overseas broad-based indices: Net subscription amounts range from -0.28 billion to 0.89 billion[4][6]

Group 1 - The core viewpoint is that the CSI 300 index, as a broad-based index, demonstrates stable performance in dividend strategies, with a high weight in the banking sector and significant representation from coal and transportation industries [1] - High dividend-paying companies exhibit a return on equity (ROE) significantly above the industry average, showcasing strong cash flow protection and creating a positive cycle of stable earnings, continuous dividends, and improved ROE [1] - The CSI 300 Enhanced ETF (561300) tracks the CSI 300 index (000300), which consists of 300 large-cap, liquid securities from the Shanghai and Shenzhen markets, covering approximately 48% of the total market capitalization of A-shares [1] Group 2 - The industry distribution of the CSI 300 index is broad, encompassing cyclical sectors such as finance, materials, and industrials, while also increasing the weight of emerging sectors like information technology and healthcare as the economic structure transforms [1] - Investors without stock accounts can consider the Guotai CSI 300 Enhanced Strategy ETF Initiated Link A (021847) and Guotai CSI 300 Enhanced Strategy ETF Initiated Link C (021848) [1]

Core Viewpoint - The article introduces a comprehensive index map that includes various commonly used stock indices, their codes, selection rules, industry distribution, average and median market capitalization of constituent stocks, and the number of constituent stocks, which will be regularly updated for easy reference [1][2]. Group 1: Types of Indices - The index map includes several categories of stock indices: broad-based indices, strategy indices, industry indices, thematic indices, and overseas indices [4][2]. Group 2: Broad-based Indices - Examples of broad-based indices include: - CSI 300 (000300.SH): Comprises 300 large-cap stocks with an average market cap of 1,929.37 billion and a median of 955.29 billion [5]. - CSI 500 (000905.SH): Comprises 500 mid-cap stocks with an average market cap of 295.98 billion and a median of 271.81 billion [5]. - CSI 800 (000906.SH): Comprises 800 stocks with an average market cap of 908.50 billion and a median of 358.74 billion [5]. Group 3: Strategy Indices - Strategy indices focus on specific investment strategies, such as: - CSI Dividend (000922.CSI): Selects 100 stocks with high dividend yields and stable dividends, with an average market cap of 1,963.17 billion [6]. - Shanghai Stock Exchange Dividend (000015.SH): Comprises 50 stocks with high dividend yields from the Shanghai Stock Exchange, with an average market cap of 2,809.85 billion [6]. Group 4: Industry Indices - Industry indices reflect the performance of specific sectors, such as: - Financial Sector Index: Represents the performance of up to 50 banking stocks with an average market cap of 3,507.12 billion [7]. - Real Estate Sector Index: Comprises 50 stocks from the real estate industry with an average market cap of 195.47 billion [7]. Group 5: Thematic Indices - Thematic indices focus on specific investment themes or trends, providing insights into particular market segments [8].

Group 1: Core Views - Recent leveraged funds continue to flow in, with the total margin trading balance exceeding 2 trillion this week. The market sentiment remains optimistic, but the increase in the ratio of margin trading to market capitalization is limited. The 2 trillion mark has stronger signaling meaning than practical meaning and may trigger reverse trading, weakening risk appetite [2]. - Seven departments including the central bank jointly issued the "Guiding Opinions on Financial Support for New - type Industrialization", creating credit demand for banks through monetary structured tools, supporting the manufacturing industry, and stimulating a rapid rebound in the banking sector [2]. - US employment data released last week plunged, increasing market bets on interest rate cuts. The US dollar index has continued to decline to around 98, and foreign capital has replenished A - share positions, supporting the sentiment in the mainland market after the A - share index correction [2]. - This week's total A - share trading volume slightly decreased compared to last week, with daily trading around 1.6 trillion. Most broad - based indices recovered last week's losses, with small - and medium - cap stocks remaining strong. The CSI 1000 rose more than 2%, and together with the CSI 2000 and micro - cap stock indices, reached new highs for the year. Large - cap broad - based indices rose slightly more than 1% this week [2]. - The downward support for basis has weakened, and the intraday structured divergence in trends among varieties has increased. The risk appetite shown in the futures market has declined, and there is a need to guard against the risk of a slowdown in the index's upward rate or even a continuous adjustment [2]. - As of Friday, the annualized basis of each variety was basically the same as last week, with the annualized discounts of IC and IM still around 10% and 11% respectively [2]. Group 2: Weekly Forecast - The model's judgment on the movement direction of the basis of IH, IF, IC, and IM next week is: strengthening, weakening, strengthening, and weakening respectively [4].

Group 1 - The article discusses the importance of diversifying investments across different asset classes, including both RMB and foreign currency assets, as well as stocks and bonds [2] - It highlights the significance of USD bond funds as a crucial component of investment diversification [2] - A free course is offered to provide systematic knowledge on investing in USD bond funds, along with supplementary materials like course notes and mind maps for efficient learning [2] Group 2 - The article explains the concept of the CSI A500 index, which belongs to the A series of indices, and its classification into several major types [5] - It points out the drawbacks of market capitalization-weighted indices, such as increased index risk due to short-term speculative companies and high concentration in certain industries [5] - The A series indices incorporate two strategies: broad-based indices and strategy indices, along with industry and thematic indices to enhance long-term returns [6]