ETF策略指数跟踪周报-20250818

Report Overview - The report is a weekly tracking report on public - offering fund ETF strategy indices, covering multiple ETF strategy indices and their performance as of August 15, 2025 [1] Report Industry Investment Rating - No industry investment rating is provided in the report Core Viewpoints - By constructing multiple ETF strategy indices, investors can conveniently transform quantitative models or subjective views into practical investment strategies, and the report tracks the performance and positions of these indices weekly [12] Summary by Directory 1. ETF Strategy Index Tracking - Performance of Last Week: The table shows the performance of different ETF strategy indices last week. For example, the Huabao Research Small - and - Large - Cap Rotation ETF Strategy Index had a return of 2.41%, with a benchmark return of 2.77% and an excess return of - 0.36%. The Huabao Research Quantitative Fire - Wheel ETF Strategy Index had a return of 4.16%, a benchmark return of 2.77%, and an excess return of 1.39% [13] 1.1. Huabao Research Small - and - Large - Cap 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 determine positions and obtain excess returns [4][14] - Performance: As of August 15, 2025, the excess return since 2024 was 17.66%, the excess return in the recent month was - 0.85%, and the excess return in the recent week was - 0.36%. The position was 100% in the CSI 300 ETF [14][17] 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 their exposure to 9 major Barra factors to obtain excess returns [16][17] - Performance: As of August 15, 2025, the excess return since 2024 was 14.35%, the excess return in the recent month was - 0.74%, and the excess return in the recent week was - 1.40%. The position was 100% in the Value 100ETF [16][20][21] 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - Strategy Principle: It starts from a multi - factor perspective, including long - and medium - term fundamental analysis, short - term market trend tracking, and behavior analysis of market participants. It uses valuation and congestion signals to prompt industry risks and digs out potential sectors to obtain excess returns [20] - Performance: As of August 15, 2025, the excess return since 2024 was 11.50%, the excess return in the recent month was 5.27%, and the excess return in the recent week was 1.39%. The positions included Communication ETF, Industrial Mother Machine ETF, etc. [20][23][24] 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 to construct a quantitative timing system for equity market trend judgment. It also builds a prediction model for market small - and large - cap styles to adjust equity market positions and obtain excess returns [24] - Performance: As of August 15, 2025, the excess return since 2024 was - 3.51%, the excess return in the recent month was - 1.66%, and the excess return in the recent week was - 1.35%. The positions included Ten - Year Treasury Bond ETF, CSI 1000ETF, etc. [24][27][29] 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - Strategy Principle: It tracks and mines hot - spot index target products through market sentiment analysis, industry event tracking, etc., to construct an ETF portfolio that can capture market hot - spots and help investors make investment decisions [28] - Performance: As of August 15, 2025, the excess return in the recent month was - 1.03%, and the excess return in the recent week was - 1.20%. The positions included Ten - Year Treasury Bond ETF, CSI 1000ETF, etc. [28][29] 1.6. Huabao Research Bond ETF Duration Strategy Index - Strategy Principle: It uses bond market liquidity and price - volume indicators to select effective timing factors and predicts bond yields through machine learning. When the expected yield is below a certain threshold, it reduces the long - duration positions in the bond portfolio to improve long - term returns and control drawdowns [6] - Performance: As of August 15, 2025, the excess return in the recent month was 0.00%, and the excess return in the recent week was 0.03%. The positions included Ten - Year Treasury Bond ETF, 5 - to 10 - Year Treasury Bond ETF, etc. [6][35][36]