ETF策略指数跟踪周报-20260119
HWABAO SECURITIES·2026-01-19 06:03

Report Industry Investment Rating No information provided in the content. Core Viewpoints of the Report The report presents several ETF strategy indices constructed with the help of ETFs, and tracks the performance and positions of these indices on a weekly basis. Each index has its own unique strategy and has achieved different levels of excess returns over different time periods [12]. Summary by Relevant Catalogs 1. ETF Strategy Index Tracking - Overall Performance Last Week: The table shows the performance of various ETF strategy indices last week, including their returns, comparison benchmarks, benchmark returns, and excess returns. For example, the Huabao Research Large - Small Cap Rotation ETF Strategy Index had a last - week return of 1.73%, with a benchmark (CSI 800) return of 0.20% and an excess return of 1.52% [13]. 1.1. Huabao Research Large - Small Cap Rotation ETF Strategy Index - Strategy: Utilizes 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. - Performance: As of 2026/1/16, the excess return since 2024 was 27.85%, the excess return in the recent month was 4.13%, and the excess return in the recent week was 1.52%. The index's recent - week return was 1.73%, recent - month return was 10.63%, and return since 2024 was 69.44%, compared with the CSI 800's 0.20%, 6.50%, and 41.59% respectively. - Positions: As of 2026/1/16, it held 50% in the CSI 500ETF (fund code: 159922.SZ) and 50% in the CSI 1000ETF (fund code: 512100.SH) [14][15][18]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - Strategy: Uses price - volume indicators to time self - built Barra factors, and then maps the timing signals to ETFs based on the ETFs' exposure 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. - Performance: As of 2026/1/16, the excess return since 2024 was 16.89%, the excess return in the recent month was - 4.53%, and the excess return in the recent week was - 1.19%. - Positions: As of 2026/1/16, it held 25.23% in the Free Cash Flow ETF800 (fund code: 563580.SH), 25.11% in the Shenzhen Dividend ETF (fund code: 159905.SZ), 24.87% in the Dividend Low - Volatility 100ETF (fund code: 515100.SH), and 24.79% in the High - Dividend ETF (fund code: 563180.SH) [18][19][21]. 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - Strategy: Starts from a multi - factor perspective, including the grasp of medium - to - long - term fundamental dimensions, 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 digs out potential sectors to obtain excess returns relative to the market. - Performance: As of 2026/1/16, the excess return since 2024 was 39.33%, the excess return in the recent month was 1.80%, and the excess return in the recent week was - 0.03%. - Positions: As of 2026/1/16, it held 21.64% in the Non - Ferrous Metals ETF (fund code: 512400.SH), 19.99% in the Chemical ETF (fund code: 159870.SZ), 19.79% in the Penghua Petroleum ETF (fund code: 159697.SZ), 19.43% in the Steel ETF (fund code: 515210.SH), and 19.16% in the E Fund Securities and Insurance ETF (fund code: 512070.SH) [21][23][26]. 1.4. Huabao Research Quantitative Balance Art ETF Strategy Index - Strategy: Adopts 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 equity market position distribution and comprehensively obtains excess returns relative to the market through timing and rotation. - Performance: As of 2026/1/16, the excess return since 2024 was - 11.23%, the excess return in the recent month was - 0.53%, and the excess return in the recent week was 0.77%. - Positions: As of 2026/1/16, it held 9.05% in the 10 - Year Treasury Bond ETF (fund code: 511260.SH), 6.50% in the Enhanced 500ETF (fund code: 159610.SZ), 6.38% in the CSI 1000ETF (fund code: 512100.SH), 33.10% in the Enhanced 300 ETF (fund code: 561300.SH), 22.48% in the Short - Term Financing ETF (fund code: 511360.SH), and 22.48% in the Policy Financial Bond ETF (fund code: 511520.SH) [25][26][28]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - Strategy: 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 timely tracks and digs out hot - spot index target products to construct an ETF portfolio that can timely capture market hot - spots, providing investors with references for short - term market trends and helping them make more informed investment decisions. - Performance: As of 2026/1/16, the excess return in the recent month was 2.67% and the excess return in the recent week was 1.48%. - Positions: As of 2026/1/16, it held 41.45% in the Non - Ferrous 50ETF (fund code: 159652.SZ), 21.71% in the Bosera Hong Kong Stock Dividend ETF (fund code: 513690.SH), 19.81% in the E Fund Hong Kong Stock Connect Pharmaceutical ETF (fund code: 513200.SH), and 17.03% in the Short - Term Financing ETF (fund code: 511360.SH) [28][30][31]. 1.6. Huabao Research Bond ETF Duration Strategy Index - Strategy: 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 portfolio's long - term returns and drawdown control ability. - Performance: As of 2026/1/16, the excess return in the recent month was 0.30% and the excess return in the recent week was 0.20%. - Positions: As of 2026/1/16, it held 50.02% in the 10 - Year Treasury Bond ETF (fund code: 511260.SH), 24.99% 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][34].