1. Report Industry Investment Rating No relevant content provided. 2. Core View of the Report The report presents several ETF - based strategy indices and tracks their performance and holdings on a weekly basis to help investors make investment decisions by converting quantitative models or subjective views into practical investment strategies [11]. 3. Summary by Related Catalogs 3.1 ETF Strategy Index Tracking - **Overall Performance Last Week**: - The table shows the performance of different ETF strategy indices last week, including their index returns, benchmark returns, and excess returns. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week index return of - 0.12%, a benchmark (CSI 800) return of - 0.41%, and an excess return of 0.30% [12]. 3.1.1 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, and decides positions based on the weekly output signal [3][13]. - **Performance**: As of May 23, 2025, the excess return since 2024 was 16.48%, the excess return in the past month was - 0.14%, and the excess return in the past week was 0.30%. The index's return in the past week was - 0.12%, compared to - 0.41% of the CSI 800 [3][13][16]. - **Position**: As of May 23, 2025, it held 100% of the CSI 300 ETF [16]. 3.1.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy Principle**: It uses price - volume indicators to time the self - built Barra factors and maps the timing signals to ETFs according to their exposures on 9 major Barra factors to obtain excess returns [3]. - **Performance**: As of May 23, 2025, the excess return since 2024 was 18.52%, the excess return in the past month was 0.39%, and the excess return in the past week was 1.29%. The index's return in the past week was 0.88%, compared to - 0.41% of the CSI 800 [3][17]. - **Position**: As of May 23, 2025, it held 100% of the Dividend Low - Volatility ETF [21]. 3.1.3 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 fundamentals, 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 digs out potential sectors [4]. - **Performance**: As of May 23, 2025, the excess return since 2024 was 2.95%, the excess return in the past month was 1.33%, and the excess return in the past week was 1.25%. The index's return in the past week was 0.84%, compared to - 0.41% of the CSI 800 [4][21]. - **Position**: Specific positions are provided in the report, but details are not fully summarized here [24]. 3.1.4 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 to build a quantitative timing system for equity market trend judgment and adjusts the equity market position distribution by predicting the market size - style [4]. - **Performance**: As of May 23, 2025, the excess return since 2024 was 0.31%, the excess return in the past month was - 1.63%, and the excess return in the past week was 0.10%. The index's return in the past week was - 0.07%, compared to - 0.18% of the SSE 300 [4][24]. - **Position**: As of May 23, 2025, it held various ETFs such as the CSI 1000ETF, Enhanced 500ETF, etc., with different weights [26]. 3.1.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy Principle**: It tracks and digs out hot - spot index target products through strategies such as market sentiment analysis, industry event tracking, and policy changes to build an ETF portfolio that can capture market hot - spots [5]. - **Performance**: As of May 23, 2025, the excess return in the past month was 1.07%, and the excess return in the past week was 1.60%. The index's return in the past week was 0.90%, compared to - 0.70% of the CSI All - Share Index [5][29]. - **Position**: As of May 23, 2025, it held real estate ETF, Hong Kong stock consumption ETF, etc., with different weights [30]. 3.1.6 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 lower than a certain threshold, it reduces the long - duration positions in the bond portfolio [5]. - **Performance**: As of May 23, 2025, the excess return in the past month was 0.14%, and the excess return in the past week was 0.11%. The index's return in the past week was 0.06%, compared to - 0.05% of the ChinaBond Aggregate Index [5][31]. - **Position**: As of May 23, 2025, it held short - term financing ETF, 10 - year Treasury bond ETF, etc., with different weights [33].

Group 1: Report Overview - The report is a weekly update on public - offering funds and ETF strategy indices, covering the week ending May 16, 2025 [1][11] Group 2: ETF Strategy Indices Introduction 2.1 General Introduction - The report presents several ETF strategy indices, aiming to convert quantitative models or subjective views into practical investment strategies and track their performance and holdings weekly [11] 2.2 Specific Indices 2.2.1 Huabao Research Large - Small Cap Rotation ETF Strategy Index - 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 to determine positions and gain excess returns. As of May 16, 2025, the excess return since 2024 is 16.17%, the excess return in the past month is - 0.28%, and the excess return in the past week is - 0.93% [3][13] 2.2.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - It uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on their exposure to 9 Barra factors. It selects mainstream broad - based index ETFs and some style and strategy ETFs. As of May 16, 2025, the excess return since 2024 is 16.94%, the excess return in the past month is - 0.30%, and the excess return in the past week is - 0.43% [3][17] 2.2.3 Huabao Research Quantitative Windmill ETF Strategy Index - It starts from a multi - factor perspective, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behavior. It uses valuation and crowding signals to indicate industry risks and digs out potential sectors. As of May 16, 2025, the excess return since 2024 is 1.55%, the excess return in the past month is 0.40%, and the excess return in the past week is - 0.02% [4][21] 2.2.4 Huabao Research Quantitative Balance Technique ETF Strategy Index - It uses a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior to build a quantitative timing system for equity market trend judgment. It also predicts the market's large - and small - cap styles to adjust equity market positions. As of May 16, 2025, the excess return since 2024 is 0.20%, the excess return in the past month is - 2.03%, and the excess return in the past week is - 0.89% [4][25] 2.2.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - It tracks and mines hot - spot index target products through market sentiment analysis, industry event tracking, investor sentiment, professional views, policy changes, and historical analysis. It constructs an ETF portfolio to capture market hot - spots and assist investors in making decisions. As of May 16, 2025, the excess return in the past month is - 1.57%, and the excess return in the past week is - 0.11% [5][29] 2.2.6 Huabao Research Bond ETF Duration Strategy Index - 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. As of May 16, 2025, the excess return in the past month is 0.15%, and the excess return in the past week is 0.05% [5][32] Group 3: Index Performance Comparison 3.1 Last Week's Performance | Index Name | Last Week's Index Return | Comparison Benchmark | Last Week's Benchmark Return | Excess Return | | --- | --- | --- | --- | --- | | Huabao Research Large - Small Cap Rotation ETF Strategy Index | - 0.13% | CSI 800 | 0.80% | - 0.93% | | Huabao Research Quantitative Windmill ETF Strategy Index | 0.78% | CSI 800 | 0.80% | - 0.02% | | Huabao Research Quantitative Balance Technique ETF Strategy Index | 0.22% | SSE 50 | 1.12% | - 0.89% | | Huabao Research SmartBeta Enhanced ETF Strategy Index | 0.38% | CSI 800 | 0.80% | - 0.43% | | Huabao Research Hot - Spot Tracking ETF Strategy Index | 0.56% | CSI All - Share | 0.67% | - 0.11% | | Huabao Research Bond ETF Duration Strategy Index | - 0.35% | ChinaBond Aggregate Index | - 0.40% | 0.05% | [12] 3.2 Other Periods' Performance - For each index, the report also provides performance data for the past month and since 2024, as well as the corresponding excess returns compared to the benchmarks [14][17][18][23][28][31][35] Group 4: Index Holdings - Each index has its specific holdings and corresponding weights as of May 16, 2025, which are detailed in the report [17][23][25][29][35][37]

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]

Report Industry Investment Rating - No information provided in the report. Core Viewpoints - The report presents several ETF strategy indices constructed using ETFs, and tracks the performance and holdings of these indices on a weekly basis. These indices aim to obtain excess returns relative to the market through different strategies [11]. Summary by Relevant Catalogs 1. ETF Strategy Index Tracking - **Overall Performance**: The table shows the performance of various ETF strategy indices last week, including index returns, benchmark returns, and excess returns. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week index return of 0.61%, a benchmark (CSI 800) return of 0.29%, and an excess return of 0.32% [12]. 1.1. Huabao Research Size 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. It outputs weekly signals to determine holdings and obtain excess returns [13]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.87%, the recent one - month excess return was 1.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.61%, recent one - month return was - 2.35%, and since 2024 was 25.11%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [13][14]. - **Holdings**: As of April 30, 2025, it held 50% of CSI 500ETF (159922.SZ) and 50% of CSI 1000ETF (512100.SH) [16]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: 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 achieve market - outperforming returns. It selects mainstream broad - based index ETFs and some style and strategy ETFs [15]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.49%, the recent one - month excess return was 1.48%, and the recent one - week excess return was - 1.51%. The index's recent one - week return was - 1.22%, recent one - month return was - 1.91%, and since 2024 was 24.73%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [16][17]. - **Holdings**: As of April 30, 2025, it held 100% of Dividend Low - Volatility ETF (512890.SH) [23]. 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: Adopts a multi - factor approach, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behaviors. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally digs out potential sectors to obtain excess returns [20]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 0.53%, the recent one - month excess return was 0.93%, and the recent one - week excess return was - 0.03%. The index's recent one - week return was 0.26%, recent one - month return was - 2.45%, and since 2024 was 8.78%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [20][23]. - **Holdings**: As of April 30, 2025, it held 20.93% of Bank ETF (512800.SH), 20.88% of Agriculture ETF (159825.SZ), 19.59% of Military Industry ETF (512660.SH), etc. [24]. 1.4. Huabao Research Quantitative Balancing Act ETF Strategy Index - **Strategy**: Employs a multi - factor system covering economic fundamentals, liquidity, technical aspects, and investor behavior. It constructs a quantitative timing system to judge the equity market trend, builds a prediction model for market large - and small - cap styles to adjust equity market position distribution, and comprehensively obtains excess returns through timing and rotation [24]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 2.46%, the recent one - month excess return was 2.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.27%, recent one - month return was - 0.97%, and since 2024 was 12.35%, compared to the SSE 300's - 0.05%, - 3.01%, and 9.89% respectively [24][26]. - **Holdings**: As of April 30, 2025, it held 5.09% of CSI 1000ETF (512100.SH), 4.98% of 500ETF Enhanced (159610.SZ), 29.13% of 300 Enhanced ETF (561300.SH), etc. [28]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: Based on strategies such as market sentiment analysis, industry event tracking, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction, it tracks and mines hot - spot index target products in a timely manner to construct an ETF portfolio that can capture market hot - spots, providing short - term market trend references for investors [28]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 2.06%, and the recent one - week excess return was 0.11%. The index's recent one - week return was 1.19%, compared to the CSI All - Share's 1.08% [28][31]. - **Holdings**: As of April 30, 2025, it held 4.15% of Real Estate ETF (515060.SH), 27.03% of Hong Kong Stock Consumption ETF (513230.SH), etc. [32]. 1.6. Huabao Research Bond ETF Duration Strategy Index - **Strategy**: Uses bond market liquidity 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 position in the bond investment portfolio to improve long - term returns and drawdown control ability [32]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 0.20%, and the recent one - week excess return was 0.02%. The index's recent one - week return was 0.19%, recent one - month return was 1.20%, since 2024 was 9.32%, and since inception was 14.47%, compared to the ChinaBond Aggregate Index's 0.17%, 1.00%, 4.97%, and 6.91% respectively [32][33]. - **Holdings**: As of April 30, 2025, it held 50.01% of 10 - Year Treasury Bond ETF (511260.SH), 25.00% of Policy Financial Bond ETF (511520.SH), etc. [36].

1. Report Industry Investment Rating No relevant content provided. 2. Core View of the Report The report provides several ETF strategy indices constructed with the help of ETFs and tracks the performance and positions of these indices on a weekly basis. These indices aim to obtain excess returns relative to the market through different strategies and models [11]. 3. Summary by Relevant Catalogs 3.1 ETF Strategy Index Tracking - **ETF Strategy Index Last Week's Performance**: - **HuaBao Research Large - Small Cap Rotation ETF Strategy Index**: Last week's index return was 0.46%, the benchmark was CSI 800 with a return of 0.59%, and the excess return was -0.14% [12]. - **HuaBao Research Quantitative Fire - Wheel ETF Strategy Index**: The index return was 0.75%, the benchmark was CSI 800 with a return of 0.59%, and the excess return was 0.15% [12]. - **HuaBao Research Quantitative Balance Art ETF Strategy Index**: The index return was 0.28%, the benchmark was SSE 300 with a return of 0.38%, and the excess return was -0.11% [12]. - **HuaBao Research SmartBeta Enhanced ETF Strategy Index**: The index return was 0.28%, the benchmark was CSI 800 with a return of 0.59%, and the excess return was -0.32% [12]. - **HuaBao Research Hot - Spot Tracking ETF Strategy Index**: The index return was 1.55%, the benchmark was CSI All - Share Index with a return of 1.10%, and the excess return was 0.45% [12]. - **HuaBao Research Bond ETF Duration Strategy Index**: The index return was -0.10%, the benchmark was ChinaBond Aggregate Index with a return of -0.08%, and the excess return was -0.02% [12]. 3.2 HuaBao Research Large - Small 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 predict the strength of the indices in the next week and determines positions accordingly to obtain excess returns [13]. - **Performance**: As of April 25, 2025, the excess return since 2024 was 16.35%, the excess return in the recent month was 0.58%, and the excess return in the recent week was -0.14%. The position was 100% in the SSE 300 ETF [13][16]. 3.3 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 [16]. - **Performance**: As of April 25, 2025, the excess return since 2024 was 18.06%, the excess return in the recent month was 3.02%, and the excess return in the recent week was -0.32%. The position was 100% in the Dividend Low - Volatility ETF [16][21]. 3.4 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 congestion signals to prompt industry risks and multi - dimensionally digs out potential sectors to obtain excess returns [20]. - **Performance**: As of April 25, 2025, the excess return since 2024 was 0.74%, the excess return in the recent month was 0.92%, and the excess return in the recent week was 0.15%. The positions included 21.03% in the Agriculture ETF and 18.93% in the Home Appliance ETF [20][23]. 3.5 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 construct a quantitative timing system for trend judgment of the equity market. It also builds a prediction model for the large - small cap style of the market to adjust the position distribution in the equity market and comprehensively obtains excess returns through timing and rotation [23]. - **Performance**: As of April 25, 2025, the excess return since 2024 was 1.99%, the excess return in the recent month was 2.40%, and the excess return in the recent week was -0.11%. The positions included various ETFs such as the CSI 1000 ETF, Enhanced 500 ETF, etc. [23][26]. 3.6 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 views, 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 [26]. - **Performance**: As of April 25, 2025, the excess return in the recent month was 2.74%, and the excess return in the recent week was 0.45%. The positions included the Real Estate ETF, Hong Kong Stock Consumption ETF, etc. [26][30]. 3.7 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 position of long - duration bonds in the bond investment portfolio to improve the long - term return and drawdown control ability of the portfolio [30]. - **Performance**: As of April 25, 2025, the excess return in the recent month was 0.17%, and the excess return in the recent week was -0.02%. The positions included the 10 - Year Treasury Bond ETF, Policy Financial Bond ETF, etc. [30][34].

1. Investment Analysis of ETF Strategy Indexes 1. ETF Strategy Index Tracking - The Huabao Research Large - Small Cap Rotation ETF Strategy Index uses a machine - learning model based on multi - dimensional technical indicator factors to predict the return difference between the Shenwan Large - Cap Index and Shenwan Small - Cap Index. It 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. As of April 18, 2025, the excess return since 2024 was 16.43%, the excess return in the recent month was 0.85%, and the excess return in the recent week was 0.28% [13][14][17]. - The Huabao Research SmartBeta Enhanced ETF Strategy Index 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, aiming to outperform the market. As of April 18, 2025, the excess return since 2024 was 18.35%, the excess return in the recent month was 4.41%, and the excess return in the recent week was 2.88% [16][17][20]. - The Huabao Research Quantitative Fire - Wheel ETF Strategy Index takes a multi - factor approach, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behaviors. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally explores potential sectors to gain excess returns relative to the market. As of April 18, 2025, the excess return since 2024 was 0.57%, the excess return in the recent month was - 0.94%, and the excess return in the recent week was - 0.37% [20][21][24]. - The Huabao Research Quantitative Balance ETF Strategy Index adopts a multi - factor system, including economic fundamentals, liquidity, technical aspects, and investor behavior. It constructs a quantitative timing system to judge the equity market trend, establishes a prediction model for market large - and small - cap styles to adjust the equity market position distribution, and comprehensively gains excess returns relative to the market through timing and rotation. As of April 18, 2025, the excess return since 2024 was 2.10%, the excess return in the recent month was 3.15%, and the excess return in the recent week was - 0.33% [23][24][26]. - The Huabao Research Hot - Spot Tracking ETF Strategy Index tracks and mines hot - spot index target products in a timely manner through strategies such as market sentiment analysis, industry 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, providing investors with short - term market trend references and assisting them in making more informed investment decisions. As of April 18, 2025, the excess return in the recent month was 2.37%, and the excess return in the recent week was - 0.08% [26][29][30]. - The Huabao Research Bond ETF Duration Strategy Index uses bond market liquidity indicators and price - volume indicators to screen 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 investment portfolio to enhance the portfolio's long - term returns and drawdown control ability. As of April 18, 2025, the excess return in the recent month was 0.16%, and the excess return in the recent week was 0.23% [30][31][34].