ETF策略指数跟踪周报-2025-03-31

Report Summary 1. Report Industry Investment Rating No information provided in the report. 2. Core Viewpoints The report presents several ETF strategy indices constructed with the help of ETFs, which can transform quantitative models or subjective views into practical investment strategies. The performance and positions of these indices are tracked on a weekly basis [11]. 3. Summary by Relevant Catalogs 1. ETF Strategy Index Tracking - Overall Performance: The table shows the performance of various ETF strategy indices last week. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week index return of 0.01%, a benchmark return of - 0.24%, and an excess return of 0.25%. The data is as of 2025/3/28, and the last - week return calculation period is from 2025/3/21 to 2025/3/28 [12]. 1.1. Huabao Research Size Rotation ETF Strategy Index - Strategy Principle: It uses multi - dimensional technical indicator factors and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. The model outputs signals weekly to predict the strength of the indices in the next week and determines positions accordingly to obtain excess returns relative to the market [13]. - Performance: As of 2025/3/28, the excess return since 2024 was 16.29%, the excess return in the past month was - 0.07%, and the excess return in the past week was 0.25%. The position was 100% in the CSI 300 ETF [13][16]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - Strategy Principle: It uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on the exposure of ETFs to 9 major Barra factors to achieve returns exceeding the market. The selected ETFs cover mainstream broad - based index ETFs and some style and strategy ETFs [16]. - Performance: As of 2025/3/28, the excess return since 2024 was 14.75%, the excess return in the past month was 0.59%, and the excess return in the past week was 0.93%. The positions were 73.37% in the Dividend Low - Volatility ETF and 26.63% in the Value 100 ETF [16][21]. 1.3. Huabao Research Quantitative Windmill ETF Strategy Index - Strategy Principle: It starts from a multi - factor perspective, including the grasp of medium - and long - term fundamental dimensions, the tracking of short - term market trends, and the analysis of the behaviors of various market participants. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally explores potential sectors to obtain excess returns relative to the market [20]. - Performance: As of 2025/3/28, the excess return since 2024 was - 0.11%, the excess return in the past month was - 1.33%, and the excess return in the past week was - 0.68%. The positions included the Bank ETF, Auto ETF, Media ETF, etc. [20][23]. 1.4. Huabao Research Quantitative Balance ETF Strategy Index - Strategy Principle: It uses a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior factors to build a quantitative timing system for trend analysis of the equity market. It also establishes a prediction model for the market's large - and small - cap styles to adjust the position distribution in the equity market and obtains excess returns through comprehensive timing and rotation [23]. - Performance: As of 2025/3/28, the excess return since 2024 was - 0.50%, the excess return in the past month was - 0.30%, and the excess return in the past week was 0.03%. The positions included the 10 - Year Treasury Bond ETF, CSI 1000 ETF, etc. [23][27]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - Strategy Principle: It tracks and mines hot - spot index target products in a timely manner based on strategies such as market sentiment analysis, tracking of major industry events, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction. It constructs an ETF portfolio that can capture market hot - spots in a timely manner to provide investors with references for short - term market trends and help them make more informed investment decisions [27]. - Performance: As of 2025/3/28, the excess return in the past month was 0.25%, and the excess return in the past week was 0.45%. The positions included the Real Estate ETF, Hong Kong Consumption ETF, etc. [27][30]. 1.6. Huabao Research Bond ETF Duration Strategy Index - Strategy Principle: It uses bond market liquidity indicators and price - volume indicators to screen effective timing factors and predicts bond yields through machine - learning methods. When the expected yield is below a certain threshold, it reduces the position of long - duration bonds in the bond investment portfolio to improve the long - term return and drawdown control ability of the portfolio [31]. - Performance: As of 2025/3/28, the excess return in the past month was 0.43%, and the excess return in the past week was 0.00%. The positions included the Short - Term Financing ETF, 10 - Year Treasury Bond ETF, etc. [31][32].