Quantitative Models and Construction Methods Model Name: PE-PEG Nine-Grid Classification System - **Model Construction Idea**: The PE-PEG framework optimizes the traditional PEG framework by incorporating both valuation safety margin and growth cost-effectiveness to better identify growth risks associated with high PE stocks and potential value traps associated with low PE stocks[8][20] - **Model Construction Process**: - Construct a nine-grid system based on PE and PEG, dividing stocks into nine distinct strategy zones[20] - The first group is the core position with high risk-return cost-effectiveness, the fourth group is the secondary position with reasonable valuation and outstanding growth, and the seventh group is the satellite position with strong growth but high valuation[8] - Formula: $ \text{PEG} = \frac{\text{PE}}{\text{Growth Rate}} $ - Parameters: PE represents the price-to-earnings ratio, and the growth rate represents the expected earnings growth rate[20] - **Model Evaluation**: The PE-PEG framework provides a more comprehensive evaluation by considering both valuation and growth, making it ideal for identifying high-risk and high-return stocks[20] - **Model Test Results**: - The first group has an annualized excess return of approximately 10.4% and a win rate of about 88.9% relative to the CSI All Share Index[26][31] - The seventh group has an annualized return of about 15.4% but also exhibits high volatility and maximum drawdown[26] Model Name: GARP Strategy 30 Portfolio - **Model Construction Idea**: The GARP strategy optimizes the traditional framework by incorporating growth constraints, quality assurance, and weight restructuring to construct a portfolio suitable for the A-share market[3][9] - **Model Construction Process**: - Growth Constraints: Use Dickinson's cash flow combination method to identify companies in the growth stage and verify the earnings of the candidate pool[9][36] - Quality Assurance: Select high-quality companies with stable and sustainable earnings through cross-examination of profitability stability and profitability authenticity[9][64] - Weight Restructuring: Assign weights based on revised profitability quality scores, with a maximum individual stock weight of 10%[9][69] - Formula: $ \text{Revised Profitability Quality Indicator} = \frac{\text{Net Cash Flow from Operating Activities TTM} - \text{Operating Profit TTM}}{\text{Total Assets}} $ - Parameters: TTM represents trailing twelve months[65] - **Model Evaluation**: The GARP strategy 30 portfolio demonstrates strong adaptability and stable returns in both bull and bear markets, making it a robust investment strategy[3][10] - **Model Test Results**: - Annualized return of approximately 12.08% and annualized excess return of over 12% relative to the CSI All Share Index, with a win rate of about 92%[77][81] Model Backtest Results PE-PEG Nine-Grid Classification System - **Annualized Return**: First group: 10.4%, Seventh group: 15.4%[26] - **Annualized Excess Return**: First group: 10.4%, Seventh group: 10.4%[26][31] - **Win Rate**: First group: 88.9%, Seventh group: 77.8%[31] GARP Strategy 30 Portfolio - **Annualized Return**: 12.08%[77][81] - **Annualized Excess Return**: 12.16%[81] - **Annualized Volatility**: 25.84%[81] - **Maximum Drawdown**: 48.60%[81] Quantitative Factors and Construction Methods Factor Name: PEG - **Factor Construction Idea**: PEG is used to evaluate the cost-effectiveness of growth by comparing the PE ratio to the expected earnings growth rate[20] - **Factor Construction Process**: - Formula: $ \text{PEG} = \frac{\text{PE}}{\text{Growth Rate}} $ - Parameters: PE represents the price-to-earnings ratio, and the growth rate represents the expected earnings growth rate[20] - **Factor Evaluation**: PEG is a core factor driving returns, with lower PEG values indicating higher cost-effectiveness and better performance[26] - **Factor Test Results**: Lower PEG values lead to higher annualized returns and lower volatility[26] Factor Name: Revised Profitability Quality Indicator - **Factor Construction Idea**: This factor assesses the authenticity and sustainability of earnings by comparing net cash flow from operating activities to operating profit[65] - **Factor Construction Process**: - Formula: $ \text{Revised Profitability Quality Indicator} = \frac{\text{Net Cash Flow from Operating Activities TTM} - \text{Operating Profit TTM}}{\text{Total Assets}} $ - Parameters: TTM represents trailing twelve months[65] - **Factor Evaluation**: This factor helps identify high-quality companies with sustainable earnings, reducing the risk of earnings manipulation[65] - **Factor Test Results**: Companies with higher revised profitability quality indicators exhibit more stable and sustainable earnings growth[65] Factor Backtest Results PEG - **Annualized Return**: Lower PEG values lead to higher annualized returns[26] - **Annualized Excess Return**: Lower PEG values lead to higher annualized excess returns[26] - **Volatility**: Lower PEG values lead to lower volatility[26] Revised Profitability Quality Indicator - **Annualized Return**: Higher revised profitability quality indicators lead to higher annualized returns[65] - **Annualized Excess Return**: Higher revised profitability quality indicators lead to higher annualized excess returns[65] - **Volatility**: Higher revised profitability quality indicators lead to lower volatility[65]

Core Insights - The rapid development of index investment and the diversification of index fund products are highlighted, with a focus on the opportunities and strategies in the ETF era [1][6] - The forum featured discussions on ETF innovations, investment opportunities in the Hong Kong stock market, and the rise of Smart Beta strategies [2][3][4] Group 1: ETF Development and Trends - The scale of passive equity funds in China is projected to reach 4.6 trillion yuan by 2024, surpassing active equity funds for the first time, indicating a new era of ETF innovation [2] - The core of ETF innovation in China lies in optimizing constituent stocks through quantitative strategies, which is expected to be a significant direction for the future [2] - The ETF investment decision system developed by the company utilizes a combination of market analysis, style rotation, and multi-model verification to enhance investment efficiency [2] Group 2: Investment Opportunities in Hong Kong Stocks - The company identifies five core sectors in the Hong Kong stock market: internet, innovative pharmaceuticals, smart vehicles, consumer goods, and dividend assets, which present significant structural opportunities [3] - The acceleration of AI commercialization is reshaping the valuations of leading internet companies, while innovative pharmaceuticals are expanding into new markets [3] - The Hang Seng Index ETF combines dividend and technology attributes, making it an ideal choice for long-term asset allocation [3] Group 3: Smart Beta Strategies - The A-share Smart Beta product scale reached 150.715 billion yuan by Q1 2025, reflecting rapid growth in this investment strategy [4] - Smart Beta strategies are breaking the boundaries between active and passive investments, offering low-cost and stable style advantages [4] - The global Smart Beta ETF market is projected to reach 2.24 trillion USD by 2024, with a year-on-year growth of 21.4%, driven by systematic applications of factor exposure [4] Group 4: Company Initiatives and Future Outlook - The company has developed a comprehensive product matrix covering multiple assets and strategies, catering to diverse investor needs [5] - The introduction of the "E起富" WeChat mini-program aims to provide users with enhanced investment decision-making support [5] - The ETF market is transitioning from simple scale expansion to refined strategy competition, with Smart Beta innovations and the exploration of scarce assets in Hong Kong being key focus areas [6]