ETF策略指数跟踪周报-20250512

1. Report Industry Investment Rating - No relevant information provided 2. Core Viewpoints of the Report - The report presents several ETF strategy indices constructed with the help of ETFs and tracks their performance and positions on a weekly basis, aiming to obtain excess returns relative to the market [11] 3. Summary by Relevant Catalogs 3.1 ETF Strategy Index Tracking - Overall Performance: The table shows the performance of various ETF strategy indices last week, including their returns, benchmark returns, and excess returns. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week return of 1.92%, a benchmark (CSI 800) return of 1.90%, and an excess return of 0.02% [12] 3.2 Huabao Research Size Rotation ETF Strategy Index - Strategy: 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. It outputs weekly signals, predicts the strength of the index for the next week, and decides positions accordingly to obtain excess returns [3][13] - Performance: As of 2025/5/9, the excess return since 2024 was 17.22%, the excess return in the past month was 0.12%, and the excess return in the past week was 0.02%. The positions as of the same date included 50% in the CSI 500ETF (fund code: 159922.SZ) and 50% in the CSI 1000ETF (fund code: 512100.SH) [3][13][16] 3.3 Huabao Research SmartBeta Enhanced ETF Strategy Index - Strategy: It uses price - volume indicators to time self - built barra factors, maps timing signals to ETFs based on the exposure of ETFs to 9 barra factors, aiming to obtain returns exceeding the market. The selected ETFs cover mainstream broad - based index ETFs and some style and strategy ETFs [3][16] - Performance: As of 2025/5/9, the excess return since 2024 was 17.34%, the excess return in the past month was - 0.23%, and the excess return in the past week was 0.43%. The position as of that date was 100% in the Dividend Low - Volatility ETF (fund code: 512890.SH) [16][17][23] 3.4 Huabao Research Quantitative Fire - Wheel ETF Strategy Index - Strategy: It starts from a multi - factor perspective, including the grasp of the medium - and long - term fundamental dimension, the tracking of short - term market trends, and the analysis of the behavior of various market participants. It uses valuation and crowding signals to prompt industry risks and multi - dimensionally dig out potential sectors to obtain excess returns [4][20] - Performance: As of 2025/5/9, the excess return since 2024 was 1.56%, the excess return in the past month was 0.27%, and the excess return in the past week was 0.94%. The positions included 20.57% in the Military Industry ETF (fund code: 512660.SH), 20.44% in the Bank ETF (fund code: 512800.SH), 20.39% in the Agriculture ETF (fund code: 159825.SZ), 19.33% in the Non - ferrous 60ETF (fund code: 159881.SZ), and 19.27% in the Home Appliance ETF (fund code: 159996.SZ) [20][23][24] 3.5 Huabao Research Quantitative Balancing Act ETF Strategy Index - Strategy: It uses a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior to construct a quantitative timing system for trend judgment of the equity market. It also builds 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 [4][24] - Performance: As of 2025/5/9, the excess return since 2024 was 1.19%, the excess return in the past month was - 2.76%, and the excess return in the past week was - 1.17%. The positions included 5.26% in the CSI 1000ETF (fund code: 512100.SH), 5.07% in the Enhanced 500ETF (fund code: 159610.SZ), 29.39% in the 300 Enhanced ETF (fund code: 561300.SH), 25.29% in the Policy Financial Bond，ETF (fund code: 511520.SH), 24.86% in the Short - term Financing ETF (fund code: 511360.SH), and 10.12% in the 10 - year Treasury Bond ETF (fund code: 511260.SH) [24][25][27] 3.6 Huabao Research Hot - Spot Tracking ETF Strategy Index - Strategy: It tracks and digs out hot - spot index target products in a timely manner based on strategies such as market sentiment analysis, industry major event tracking, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction, and constructs an ETF portfolio that can capture market hot - spots in time to provide investors with references for short - term market trends [5][27] - Performance: As of 2025/5/9, the excess return in the past month was - 3.20%, and the excess return in the past week was - 0.92%. The positions included 27.94% in the Hong Kong Stock Consumption ETF (fund code: 513230.SH), 24.82% in the Bosera Hong Kong Stock Dividend ETF (fund code: 513690.SH), 23.49% in the Soybean Meal ETF (fund code: 159985.SZ), 19.57% in the 5 - to 10 - year Treasury Bond ETF (fund code: 511020.SH), and 4.18% in the Real Estate ETF (fund code: 515060.SH) [27][30][31] 3.7 Huabao Research Bond ETF Duration Strategy Index - Strategy: 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 long - duration positions in the bond investment portfolio to improve the long - term return and drawdown control ability of the portfolio [5][31] - Performance: As of 2025/5/9, the excess return in the past month was 0.23%, and the excess return in the past week was - 0.02%. The positions included 50.00% in the 10 - year Treasury Bond ETF (fund code: 511260.SH), 25.02% in the Policy Financial Bond ETF (fund code: 511520.SH), and 24.99% in the 5 - to 10 - year Treasury Bond ETF (fund code: 511020.SH) [31][32][35]