ETF策略指数跟踪周报-20260112

Report Summary 1. Investment Ratings No investment ratings for the industry are provided in the report. 2. Core Viewpoints The report presents several ETF strategy indices constructed with the help of ETFs, which can convert quantitative models or subjective views into practical investment strategies. The performance and positions of these indices are tracked on a weekly basis [12]. 3. Summary by Directory 1. ETF Strategy Index Tracking - ETF Strategy Index Last Week's Performance: - Huabao Research Size Rotation ETF Strategy Index: Last week's index return was 7.47%, the benchmark was CSI 800 with a return of 4.18%, and the excess return was 3.30% [13]. - Huabao Research SmartBeta Enhanced ETF Strategy Index: Last week's index return was 1.97%, the benchmark was CSI 800 with a return of 4.18%, and the excess return was -2.21% [13]. - Huabao Research Quantitative Fire - Wheel ETF Strategy Index: Last week's index return was 3.81%, the benchmark was CSI 800 with a return of 4.18%, and the excess return was -0.36% [13]. - Huabao Research Quantitative Balance Art ETF Strategy Index: Last week's index return was 1.73%, the benchmark was SSE 300 with a return of 2.79%, and the excess return was -1.06% [13]. - Huabao Research Hot - Spot Tracking ETF Strategy Index: Last week's index return was 6.24%, the benchmark was CSI All - Share with a return of 5.04%, and the excess return was 1.20% [13]. - Huabao Research Bond ETF Duration Strategy Index: Last week's index return was -0.12%, the benchmark was ChinaBond Aggregate Index with a return of -0.23%, and the excess return was 0.11% [13]. 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 index in the next week and determines positions accordingly to obtain excess returns relative to the market [14]. - Performance: As of January 9, 2026, the excess return since 2024 was 25.26%, the excess return in the recent month was 2.56%, and the excess return in the recent week was 3.30% [14]. - Positions: As of January 9, 2026, it held 50% of CSI 500ETF (code: 159922.SZ) and 50% of CSI 1000ETF (code: 512100.SH) [18]. 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 obtain returns exceeding the market. The selected ETFs cover mainstream broad - based index ETFs and some style and strategy ETFs [18]. - Performance: As of January 9, 2026, the excess return since 2024 was 18.76%, the excess return in the recent month was -3.73%, and the excess return in the recent week was -2.21% [18]. - Positions: As of January 9, 2026, it held 25.21% of High - Dividend ETF (code: 159207.SZ), 25.13% of Shenzhen Dividend ETF (code: 159905.SZ), 24.98% of Free Cash Flow ETF800 (code: 563580.SH), and 24.68% of Dividend Low - Volatility 100ETF (code: 515100.SH) [21]. 1.3 Huabao Research Quantitative Fire - Wheel 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 prompt industry risks and multi - dimensionally digs out potential sectors to obtain excess returns relative to the market [21]. - Performance: As of January 9, 2026, the excess return since 2024 was 39.31%, the excess return in the recent month was 2.75%, and the excess return in the recent week was -0.36% [21]. 1.4 Huabao Research Quantitative Balance Art 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 judgment of the equity market. It establishes a prediction model for the market's large - and small - cap styles to adjust the position distribution of the equity market and comprehensively obtains excess returns relative to the market through timing and rotation [25]. - Performance: As of January 9, 2026, the excess return since 2024 was -12.27%, the excess return in the recent month was -1.07%, and the excess return in the recent week was -1.06% [25]. - Positions: As of January 9, 2026, it held 20.50% of Non - Ferrous Metals ETF (code: 512400.SH), 20.11% of Chemical ETF (code: 159870.SZ), 20.06% of Securities and Insurance ETF E Fund (code: 512070.SH), 19.88% of Steel ETF (code: 515210.SH), and 19.46% of Oil and Gas ETF (code: 159697.SZ) [26]. 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, industry major event tracking, 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, providing investors with references for short - term market trends and helping them make more informed investment decisions [28]. - Performance: As of January 9, 2026, the excess return in the recent month was 1.08%, and the excess return in the recent week was 1.20% [30]. - Positions: As of January 9, 2026, it held 40.04% of Non - Ferrous Metals 50ETF (code: 159652.SZ), 22.32% of Hong Kong Stock Dividend ETF Bosera (code: 513690.SH), 19.90% of Hong Kong Stock Connect Pharmaceutical E Fund ETF (code: 513200.SH), and 17.74% of Short - Term Financing ETF (code: 511360.SH) [31]. 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 lower than 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 [31]. - Performance: As of January 9, 2026, the excess return in the recent month was 0.15%, and the excess return in the recent week was 0.11% [32]. - Positions: As of January 9, 2026, it held 50.00% of 10 - Year Treasury Bond ETF (code: 511260.SH), 25.00% of Treasury Bond ETF 5 - 10 Years (code: 511020.SH), and 25.00% of Policy Financial Bond ETF (code: 511520.SH) [34].