Report's Investment Rating for the Industry The provided content does not mention the industry investment rating. Core Views of the Report - The report constructs multiple ETF portfolios, including macro industry, macro + momentum industry, core - satellite, and trinity style rotation portfolios, to capture investment opportunities and manage risks in the ETF market [1][5]. - It combines macro - based and momentum - based methods to form complementary strategies, aiming to improve the performance of the portfolios [12]. - The trinity style rotation model uses macro liquidity as the core to build a long - term style rotation model and selects ETFs based on the model's results [6]. Summary by Relevant Catalog 1. ETF Portfolio Construction Methods 1.1 Based on Macro Method - Calculate the macro - sensitivity scores of economic, liquidity, and credit for industry - themed ETFs, and adjust the scores according to the latest indicators. Select the top 6 industry - themed indices and corresponding largest - scale ETFs for equal - weight allocation [1][7]. - Traditional cyclical industries are sensitive to the economy, TMT is sensitive to liquidity, and consumption is sensitive to credit. State - owned enterprises and ESG - related themes have low sensitivity to liquidity and credit [5]. 1.2 Trinity Style Rotation - Build a long - term style rotation model centered on macro liquidity, including growth/value, market capitalization, and quality models. Combine the results of the three models to get the final style preference [6]. - Screen ETFs with high exposure to the target style, control industry exposure, and set allocation limits to obtain the ETF allocation model [6]. 2. Macro Industry Portfolio - Select industry - themed ETFs that have been established for over 1 year and have a current scale of over 200 million. Calculate and adjust sensitivity scores, and remove liquidity scores if there is a significant divergence between liquidity and credit. Then select the top 6 industry - themed indices and corresponding largest - scale ETFs for equal - weight allocation [7][8]. - Currently, with economic forward - looking indicators rising and liquidity and credit indicators tightening, the portfolio is value - oriented with high proportions of banks and cyclical sectors. The December 2025 holdings include Huabao CSI Bank ETF, Cathay CSI Coal ETF, etc. [9]. - The portfolio has large fluctuations and outperformed the benchmark significantly in November 2025 [11]. 3. Macro + Momentum Industry Portfolio - Combine macro - based and momentum - based methods. Use clustering to group industry - themed indices and select the product with the highest 6 - month return from each group for equal - weight allocation [12]. - The December 2025 holdings include Huabao CSI Bank ETF, Cathay CSI Coal ETF, and others. The battery and metal industries selected by momentum have increased [15]. - The portfolio has performed well this year and outperformed the CSI 300 significantly in November 2025 [16]. 4. Core - Satellite Portfolio - Design a "core - satellite" portfolio with the CSI 300 as the core to address the high volatility and rapid industry rotation of industry - themed ETFs [18]. - Calculate macro - sensitivity scores for domestic broad - based, industry - themed, and Smart Beta ETFs, construct three stock portfolios, and weight them at 50%, 30%, and 20% respectively [18]. - The December 2025 holdings include Huatai - Peregrine CSI 300 ETF, Huaxia SSE 50 ETF, etc. The portfolio has been stable this year and outperformed the index almost every month, including in November 2025 [21][23]. 5. Trinity Style Rotation ETF Portfolio - The model currently favors small - cap growth + high - quality segments. The factor exposures and historical performance are presented in the report [24]. - The December 2025 holdings include Southern CSI 500ETF, Southern CSI 1000ETF, etc. [30].

Report Summary 1. Report Industry Investment Rating No relevant content provided. 2. Core View of the Report On August 22, 2025, the A - share market generally rose, with the Shanghai Composite Index up 1.45%, the Shenzhen Component Index up 2.07%, and the ChiNext Index up 3.36%. The trading volume of the two markets reached 25793 billion yuan. Different sectors and ETFs showed diverse performance [2][6]. 3. Summary by Directory Market Overview - The Shanghai Composite Index closed at 3825.76, up 1.45%; the Shenzhen Component Index closed at 12166.06, up 2.07%; the ChiNext Index closed at 2682.55, up 3.36%. The trading volume of the two A - share markets was 25793 billion yuan [2][6]. - Industries with the highest gains were electronics (4.82%), communication (3.77%), and computer (3.50%); industries with the highest losses were banking (-0.30%), textile and apparel (-0.20%), and coal (-0.15%) [2][6]. Stock ETF - The top - traded stock ETFs were Huaxia SSE STAR Market 50 ETF (up 9.52%, premium rate 9.47%), Huatai - Berry CSI 300 ETF (up 2.31%, premium rate 2.38%), and Southern CSI 500 ETF (up 1.90%, premium rate 1.88%) [3][7]. - The table shows detailed information of the top ten stock ETFs in terms of trading volume, including code, fund name, price, change rate, tracking index, premium rate, trading volume, etc. [8]. Bond ETF - The top - traded bond ETFs were Haifutong CSI Short - term Financing ETF (down 0.00%, premium rate - 0.00%), Penghyang CCDC - 30 - year Treasury Bond ETF (down 0.24%, premium rate - 0.38%), and Boshi CSI Convertible and Exchangeable Bond ETF (up 1.20%, premium rate 1.32%) [4][9]. - The table presents detailed information of the top five bond ETFs in terms of trading volume [10]. Gold ETF - Gold AU9999 was down 0.02%, and Shanghai Gold was down 0.17%. The top - traded gold ETFs were Huaan Gold ETF (down 0.22%, premium rate - 0.22%), Boshi Gold ETF (down 0.19%, premium rate - 0.21%), and E Fund Gold ETF (down 0.19%, premium rate - 0.21%) [12]. - The table shows detailed information of the top five gold ETFs in terms of trading volume [13]. Commodity Futures ETF - Huaxia Feed Soybean Meal Futures ETF was down 0.85%, premium rate - 1.38%; Jianxin Yisheng Zhengzhou Commodity Exchange Energy and Chemical Futures ETF was down 0.23%, premium rate - 0.04%; Dacheng Non - ferrous Metals Futures ETF was up 0.18%, premium rate - 0.01% [15]. - The table provides detailed information of commodity futures ETFs, including tracking index and its change rate [16]. Cross - border ETF - The previous trading day, the Dow Jones Industrial Average was down 0.34%, the Nasdaq was down 0.34%, the S&P 500 was down 0.40%, and the German DAX was up 0.07%. On this day, the Hang Seng Index was up 0.93%, and the Hang Seng China Enterprises Index was up 1.08%. - The top - traded cross - border ETFs were E Fund CSI Hong Kong Securities Investment Theme ETF (up 1.33%, premium rate 1.28%), GF CSI Hong Kong Innovative Drug ETF (up 1.61%, premium rate 1.46%), and Huaxia Hang Seng Technology ETF (up 2.01%, premium rate 2.59%) [17]. - The table shows detailed information of the top five cross - border ETFs in terms of trading volume [18]. Money ETF - The top - traded money ETFs were Yin Hua Rili ETF, Hua Bao Tian Yi ETF, and Money ETF Jianxin Tian Yi [19]. - The table presents the trading volume of the top three money ETFs [21].