Market Performance - The recent five trading days saw the Sci-Tech 50 Index decline by 0.36%, the ChiNext Index by 1.40%, and the large-cap value index by 0.16%, while the large-cap growth index fell by 2.71%. The Shanghai 50 Index decreased by 1.22%, whereas the small-cap index represented by the CSI 2000 rose by 0.94%. Sectors such as environmental protection and biomedicine performed well, while automotive and electrical equipment lagged behind [1]. Risk Premium Analysis - The risk premium, defined as the inverse of the static PE of the CSI All Index (EP) minus the yield of ten-year government bonds, indicates that the implied returns of equity and bond assets are at historically significant levels. For instance, on April 26, 2022, the risk premium reached 4.17%, and on October 28, 2022, it was 4.08%. As of January 19, 2024, the indicator stood at 4.11%, marking the fifth occurrence since 2016 of exceeding 4%. As of May 30, 2025, the indicator was at 3.90%, with the two-standard deviation boundary set at 4.75% [1]. Valuation Levels - As of May 30, 2025, the CSI All Index's PETTM was at the 50th percentile, with the Shanghai 50 and CSI 300 at 61% and 48%, respectively. The ChiNext Index was close to 11%, while the CSI 500 and CSI 1000 were at 30% and 32%. The ChiNext Index's valuation style is relatively low compared to historical averages [2]. Long-term Market Trends - The technical analysis of the Deep 100 Index indicates a cyclical pattern of bear markets every three years, followed by bull markets. Historical declines ranged from 40% to 45%, with the current adjustment starting in the first quarter of 2021 showing sufficient time and space for a potential upward cycle [2]. Fund Flow and Trading Activity - In the last five trading days, ETF inflows totaled 8.5 billion yuan, with margin trading increasing by approximately 720 million yuan. The average daily trading volume across both markets was 10.687 billion yuan [4]. AI and Machine Learning Applications - The use of convolutional neural networks (CNN) for modeling price and volume data has been explored, with features mapped to industry themes. The latest focus is on sectors such as banking [3][10].

Market Performance - The Sci-Tech 50 Index decreased by 1.47% over the last five trading days, while the ChiNext Index fell by 0.88%. In contrast, the large-cap value stocks rose by 0.48%, and the large-cap growth stocks declined by 0.40% [1] - The medical and biological sectors performed well, while the computer and machinery equipment sectors lagged behind [1] Risk Premium Analysis - The static PE of the CSI All Share Index minus the yield of 10-year government bonds indicates a risk premium. Historical extreme bottoms have shown this data to be at two standard deviations above the mean, with recent peaks at 4.17% on April 26, 2022, and 4.11% on January 19, 2024. As of May 23, 2025, the indicator stands at 3.84%, with the two standard deviation boundary at 4.76% [1] Valuation Levels - As of May 23, 2025, the CSI All Share Index's TTM PE is at the 51st percentile, with the SSE 50 and CSI 300 at 62% and 49%, respectively. The ChiNext Index is close to 11%, indicating a relatively low valuation level compared to historical averages [2] Long-term Market Trends - The Shenzhen 100 Index has experienced bear markets approximately every three years, followed by bull markets. The current adjustment, which began in Q1 2021, has shown sufficient time and space for a potential upward cycle [2] Fund Flow and Trading Activity - In the last five trading days, ETF funds saw an outflow of 24 billion yuan, while margin financing decreased by approximately 20 million yuan. The average daily trading volume across both markets was 1.1376 trillion yuan [3] AI and Machine Learning Applications - A convolutional neural network (CNN) has been utilized to model price and volume data, mapping learned features to industry themes. The latest focus is on sectors such as banking and dividends [2][10]

Summary of Key Points from the Conference Call Company and Industry - The focus is on the **广发中证智选高股息策略 ETF** and its underlying **智选高股息指数** which is designed to select high dividend stocks based on cash dividend proposals rather than historical dividend rates [1][2][3] Core Insights and Arguments - **Selection Methodology**: The index uses cash dividend proposals as a selection criterion, which enhances predictive accuracy and stability of returns compared to traditional indices that rely on historical data [1][3][5] - **Performance Metrics**: As of April 2025, the index has achieved an annualized return close to **20%**, outperforming the 中证红利全收益 and 红利低波全收益 indices by approximately **5.4%** and **1.4%** respectively, with a Sharpe ratio of **0.8** [3][8] - **Risk Management**: The index is designed to mitigate risks associated with sudden interruptions in dividend payments by adjusting its components based on cash dividend proposals, ensuring that selected stocks will implement real cash dividends within four months [6][4] - **Unique Positioning**: The ETF is unique in the market, with no similar products launched in the past three years, providing intellectual property protection and differentiation [2][7] - **Long-term Viability**: The index has shown a long-term annual dividend yield of approximately **7%**, consistently exceeding other dividend indices by nearly **2%** [9][10] Additional Important Content - **Industry Distribution**: The index maintains a balanced industry distribution, with coal and transportation sectors having the highest weights, while the banking sector's weight has decreased from nearly **30%** to **7.8%**, enhancing its rebalancing capability [11] - **Financial Metrics**: The index's components exhibit superior financial metrics such as ROE and ROA, which are not the primary goals of the index but indicate strong profitability and a sound capital structure [12] - **Investment Probability**: Holding the index for **3 years** yields a high probability of positive returns, with average returns of **18%**, **43%**, and **68%** over **1**, **3**, and **5 years** respectively [13] - **Long-term Asset Value**: Dividend assets are viewed as having high long-term win rates, with current dividend asset yields showing strong potential for upward movement in a low-interest-rate environment [14] - **Dividend Distribution**: The ETF plans to implement periodic dividends, with an estimated dividend yield of **6%** for 2025, subject to adjustments based on mid-term distributions [16][17]

Market Performance - The recent 5 trading days saw the Sci-Tech 50 Index increase by 0.24%, the ChiNext Index rise by 4.13%, large-cap value stocks up by 1.55%, large-cap growth stocks up by 2.05%, the SSE 50 Index up by 1.46%, and the small-cap represented by the CSI 2000 up by 3.77% [1] - The defense and military industry, as well as the communication sector, performed well, while steel and retail sectors lagged behind [1] Risk Premium Analysis - The static PE of the CSI All Index minus the yield of 10-year government bonds indicates a risk premium, which has historically reached extreme levels at two standard deviations above the mean during significant market bottoms, such as in 2012, 2018, and 2020 [1] - As of April 26, 2022, the risk premium reached 4.17%, and on October 28, 2022, it was 4.08%, with a recent reading of 4.11% on January 19, 2024, marking the fifth occurrence since 2016 of exceeding 4% [1] Valuation Levels - As of May 9, 2025, the CSI All Index's PETTM is at the 50th percentile, with the SSE 50 and CSI 300 at 61% and 47% respectively, while the ChiNext Index is close to 11% [2] - The ChiNext Index's valuation is relatively low compared to historical averages [2] Long-term Market Trends - The technical analysis of the Deep 100 Index indicates a pattern of bear markets every three years followed by bull markets, with previous declines ranging from 40% to 45% [2] - The current adjustment cycle began in Q1 2021, suggesting a potential for upward movement from the bottom [2] Fund Flow and Trading Activity - In the last 5 trading days, ETF funds saw an outflow of 17.9 billion yuan, while margin trading increased by approximately 4.4 billion yuan [2] - The average daily trading volume across both markets was 1.2918 trillion yuan [2] AI and Machine Learning Insights - A convolutional neural network (CNN) was utilized to model price and volume data, mapping learned features to industry themes, with a current focus on banking [2][7] Market Sentiment - The proportion of stocks above the 200-day moving average is being tracked to gauge market sentiment [9] Equity and Bond Risk Preference - Ongoing monitoring of risk preferences between equity and bond assets is being conducted [11]

Core Viewpoint - The domestic ETF market is experiencing explosive growth, approaching a scale of 4 trillion yuan, but faces increasing homogenization and competition, prompting some public funds to focus on "first-mover" differentiated products to capture market opportunities [1][2][9]. Group 1: Market Dynamics - The ETF market has seen a surge in new issuances, with over ten public funds competing, leading to intense competition where smaller funds struggle to keep up with larger ones [2]. - Major public funds dominate key broad-based and thematic ETF tracks, while some are exploring niche markets and innovative strategies to differentiate themselves [2][6]. Group 2: Innovative Product Launches - Several "first" ETFs have been launched this year, including the first General Aviation ETF and the first Satellite ETF, both by Yongying Fund, indicating a trend towards innovative product offerings [3]. - Other notable launches include the first ETF linked to a high-dividend strategy and the first ETF focused on the new energy sector in the ChiNext market, showcasing the trend of differentiation among leading public funds [3][4]. Group 3: Growth of Existing Products - The first convertible bond ETF launched by Bosera Fund has seen its scale grow from 6.284 billion yuan to 38.622 billion yuan in just one year, highlighting the potential for significant growth in innovative ETFs [4]. - The unique policy financial bond ETF from Fuguo Fund has also experienced substantial growth, increasing from approximately 7.224 billion yuan to over 43.9 billion yuan within a year [5]. Group 4: Competitive Advantages of "First-Mover" ETFs - "First-mover" ETFs can quickly capture market share and build scale, as seen with the first gold industry ETFs that have gained significant traction since their launch [6]. - These products can create brand loyalty and recognition due to their unique strategies, allowing public funds to compete effectively in a crowded market [7]. Group 5: Challenges Ahead - Despite the advantages, public funds face challenges in nurturing these "first-mover" ETFs, including high initial marketing costs and the risk of low liquidity and strategy obsolescence [8]. - The competitive landscape is shifting towards a focus on existing products, with later entrants potentially leveraging cost advantages to challenge smaller funds [9].

- The "CSI Smart High Dividend Strategy Index" was launched by the China Securities Index Company in 2024 to optimize traditional dividend stock selection logic through dynamic screening mechanisms and volatility control rules[2][32] - The index selects 50 stocks with continuous dividends and high expected dividend yields, using a "expected dividend yield" selection method combined with a dividend yield and volatility weighting mechanism to avoid the "high dividend trap" and ensure selected stocks have stable dividend capabilities and low volatility[2][32][39] - The index's construction process includes selecting stocks with continuous dividends over the past three years, calculating the expected dividend yield based on disclosed cash dividend plans, and weighting by the ratio of dividend yield to volatility[39][41] - The index has shown superior performance with higher annualized returns, lower volatility, and smaller maximum drawdowns compared to other dividend indices, demonstrating its value in long-term asset allocation[2][33][37] Model Performance Metrics - CSI Smart High Dividend Strategy Index, annualized return: 19.66%, annualized volatility: 24.60%, Sharpe ratio: 0.88, maximum drawdown: 64.82%[37] - Dividend Low Volatility 100 Total Return Index, annualized return: 17.87%, annualized volatility: 24.47%, Sharpe ratio: 0.81, maximum drawdown: 64.02%[15][37] - CSI Dividend Total Return Index, annualized return: 14.14%, annualized volatility: 25.86%, Sharpe ratio: 0.75, maximum drawdown: 72.13%[15][37] - CSI All Share Total Return Index, annualized return: 11.00%, annualized volatility: 26.29%, Sharpe ratio: 0.50, maximum drawdown: 71.48%[15] Factor Construction and Evaluation - The "expected dividend yield" factor is constructed by calculating the dividend yield based on disclosed cash dividend plans and adjusting for stock price at the end of April[39][41] - The factor is evaluated positively for its ability to avoid the "high dividend trap" and ensure selected stocks have stable dividend capabilities and low volatility[2][39] - The index's weighting method, which uses the ratio of dividend yield to volatility, effectively controls annualized volatility and enhances risk-adjusted returns[39][41] Factor Performance Metrics - CSI Smart High Dividend Strategy Index, dividend yield: consistently higher than other dividend indices during the period from September 30, 2024, to March 31, 2025[38] - The index's constituent stocks have a net asset return rate of approximately 10.5% and the lowest asset-liability ratio among compared dividend indices, indicating high profitability and low debt risk[54][56]