- The dividend timing model was constructed in the report "Dividend Style Timing Scheme" on October 16, 2025[6] - The comprehensive factor value of the dividend timing model for the week of March 9 to March 13, 2026, was -0.39, remaining negative and almost unchanged compared to the previous week (-0.38)[1][6] - Momentum factor contributed positively to the dividend performance, while other variables such as the decline in US Treasury yields and the recovery of industry sentiment contributed negatively, resulting in an overall negative score[4][7] - Factor values for March 13, 2026, include: - China Non-Manufacturing PMI (Service Industry): 0.14[12] - China M2 YoY: 0.31[12] - US 10-Year Treasury Yield: -0.81[12] - Dividend relative net value: 1.59[12] - CSI Dividend Stock Dividend Yield - 10-Year Treasury Yield: -0.22[12] - Financing net purchase: 0.74[12] - Industry average sentiment: 0.91[12]

- The report highlights the performance of low-frequency stock selection factors, emphasizing the dominance of low volatility and low turnover rate factors during the week[1][5][8] - Quantitative stock portfolios such as the balanced portfolio achieved a weekly return of 0.91%, with a cumulative return of 16.49% in 2026[1][8][11] - The PB-earnings optimized portfolio delivered a weekly return of 1.43%, outperforming the CSI 300 index by 1.24%[5][8][30] - Small-cap growth portfolio recorded a weekly return of -0.93%, underperforming the micro-cap index by -0.59%[5][8][39] - Style factors showed that small-cap stocks outperformed large-cap stocks, and low valuation stocks outperformed high valuation stocks. For example, the PB factor achieved a multi-long-short return of 3.76% during the week[43][44][46] - Technical factors such as turnover rate and volatility contributed positive returns, with turnover rate factor achieving a multi-long-short return of 2.68% during the week[43][48][51] - Fundamental factors like adjusted expected net profit showed positive returns, with a multi-long-short return of 0.15% during the week[43][52][54]

- The dividend timing model was constructed in the report "Dividend Style Timing Scheme" on October 16, 2025[5] - The latest composite factor value of the dividend timing model for the week of 20260302 to 20260306 is -0.38, which remains negative and has declined compared to the previous week's value of -0.10[1][5] - The composite factor value reflects multiple influences, including the recent decline in US Treasury yields, which has strengthened its suppressive effect on dividends, and the recovery of market sentiment, which has negatively contributed to dividend excess returns[3][8] - The sub-factors of the model include variables such as China's non-manufacturing PMI (service sector), China's M2 year-on-year growth, US 10-year Treasury yield, relative net value of dividends, dividend yield spread over 10-year Chinese Treasury yield, net financing purchases, and industry average prosperity[11] - Factor values for 20260306 are as follows: China's non-manufacturing PMI (service sector) at 0.14, China's M2 year-on-year growth at 0.31, US 10-year Treasury yield at -0.70, relative net value of dividends at 0.76, dividend yield spread over 10-year Chinese Treasury yield at -0.11, net financing purchases at 0.26, and industry average prosperity at 0.97[11]

Quantitative Models and Construction Methods - **Model Name**: CSI 300 Enhanced Portfolio **Model Construction Idea**: The model aims to generate excess returns over the CSI 300 Index by leveraging quantitative strategies and factor-based enhancements [1][5][13] **Model Construction Process**: The portfolio is constructed by applying factor-based selection and weighting methodologies to the CSI 300 Index constituents. Specific factors and optimization techniques are not detailed in the report [13][15] **Model Evaluation**: The model demonstrates strong performance with consistent excess returns over the benchmark [13][15] - **Model Name**: PB-Earnings Optimized Portfolio **Model Construction Idea**: This model combines low valuation (PB) and high earnings factors to identify undervalued stocks with strong profitability [5][32] **Model Construction Process**: Stocks are selected based on a combination of low PB ratios and high earnings metrics. The portfolio is optimized to maximize exposure to these factors while maintaining diversification [32][34] **Model Evaluation**: The model effectively captures value opportunities and delivers significant excess returns over the CSI 300 Index [32][34] - **Model Name**: GARP Portfolio **Model Construction Idea**: The Growth at a Reasonable Price (GARP) strategy balances growth and valuation factors to identify stocks with sustainable growth potential at reasonable valuations [5][36] **Model Construction Process**: Stocks are screened and weighted based on a combination of growth metrics (e.g., earnings growth) and valuation metrics (e.g., PE ratio). The portfolio is constructed to achieve a balance between growth and value [36] **Model Evaluation**: The GARP portfolio demonstrates strong performance, particularly in capturing growth opportunities while mitigating valuation risks [36] - **Model Name**: Small-Cap Value Optimized Portfolio **Model Construction Idea**: This model focuses on small-cap stocks with low valuations to exploit the value premium in the small-cap segment [5][38][40] **Model Construction Process**: Stocks are selected from the small-cap universe based on valuation metrics such as PB and PE ratios. The portfolio is optimized to enhance exposure to value factors while maintaining diversification [38][40] **Model Evaluation**: The model captures the value premium effectively but exhibits higher volatility compared to broader market indices [38][40] - **Model Name**: Small-Cap Growth Portfolio **Model Construction Idea**: This model targets small-cap stocks with high growth potential, leveraging growth factors to identify outperforming stocks [5][42] **Model Construction Process**: Stocks are selected from the small-cap universe based on growth metrics such as earnings growth and revenue growth. The portfolio is constructed to maximize exposure to growth factors [42] **Model Evaluation**: The model captures growth opportunities but underperforms during periods of market stress or high volatility [42] Model Backtesting Results - **CSI 300 Enhanced Portfolio**: - Weekly return: 2.72% - Monthly return: 2.73% - YTD return: 9.77% - Excess return (YTD): 8.02% - Tracking error: 6.62% - Maximum drawdown: 2.09% [9][13][15] - **PB-Earnings Optimized Portfolio**: - Weekly return: 4.09% - Monthly return: 1.58% - YTD return: 7.85% - Excess return (YTD): 6.11% - Tracking error: 12.23% - Maximum drawdown: 2.38% [9][32][34] - **GARP Portfolio**: - Weekly return: 2.87% - Monthly return: 2.35% - YTD return: 14.05% - Excess return (YTD): 12.31% - Tracking error: 11.16% - Maximum drawdown: 1.18% [9][36] - **Small-Cap Value Optimized Portfolio 1**: - Weekly return: 4.03% - Monthly return: 4.16% - YTD return: 12.37% - Excess return (YTD): -5.65% - Tracking error: 10.46% - Maximum drawdown: 8.23% [9][38] - **Small-Cap Value Optimized Portfolio 2**: - Weekly return: 3.88% - Monthly return: 5.55% - YTD return: 18.61% - Excess return (YTD): 0.60% - Tracking error: 11.69% - Maximum drawdown: 5.62% [9][40] - **Small-Cap Growth Portfolio**: - Weekly return: 2.65% - Monthly return: 4.53% - YTD return: 14.07% - Excess return (YTD): -3.95% - Tracking error: 9.62% - Maximum drawdown: 6.37% [9][42] Quantitative Factors and Construction Methods - **Factor Name**: Market Capitalization (Size) **Factor Construction Idea**: Measures the relative size of companies, with larger companies expected to outperform smaller ones in certain market conditions [45][46] **Factor Construction Process**: Stocks are ranked by market capitalization, and the top 10% (large-cap) and bottom 10% (small-cap) are used to construct long and short portfolios, respectively. The difference in returns between the two portfolios represents the factor return [45][46] **Factor Evaluation**: The size factor shows mixed performance, with large-cap stocks outperforming small-cap stocks in the short term but underperforming in the long term [46][47] - **Factor Name**: Price-to-Book Ratio (PB) **Factor Construction Idea**: Identifies undervalued stocks by comparing market price to book value, with lower PB ratios indicating better value [45][46] **Factor Construction Process**: Stocks are ranked by PB ratio, and the top 10% (low PB) and bottom 10% (high PB) are used to construct long and short portfolios, respectively. The difference in returns between the two portfolios represents the factor return [45][46] **Factor Evaluation**: The PB factor demonstrates consistent performance in identifying value opportunities [46][47] - **Factor Name**: Return on Equity (ROE) **Factor Construction Idea**: Measures profitability relative to equity, with higher ROE indicating better financial performance [45][54] **Factor Construction Process**: Stocks are ranked by ROE, and the top 10% (high ROE) and bottom 10% (low ROE) are used to construct long and short portfolios, respectively. The difference in returns between the two portfolios represents the factor return [45][54] **Factor Evaluation**: The ROE factor consistently delivers positive returns, reflecting its effectiveness in capturing profitability [54][55] Factor Backtesting Results - **Market Capitalization (Size)**: - Weekly long-short return: -0.33% - Monthly long-short return: 2.93% - YTD long-short return: 6.67% [46][47] - **Price-to-Book Ratio (PB)**: - Weekly long-short return: 0.24% - Monthly long-short return: -0.73% - YTD long-short return: -2.22% [46][47] - **Return on Equity (ROE)**: - Weekly long-short return: 1.35% - Monthly long-short return: -0.59% - YTD long-short return: 2.32% [54][55]

Quantitative Models and Construction Methods - **Model Name**: CSI 300 Enhanced Portfolio **Model Construction Idea**: The model aims to enhance the performance of the CSI 300 Index by leveraging quantitative strategies to generate excess returns over the benchmark index[5][9][15] **Model Construction Process**: The portfolio is constructed by applying quantitative stock selection and weighting methodologies to the CSI 300 Index constituents. The process involves identifying stocks with favorable factor exposures and optimizing the portfolio to maximize risk-adjusted returns while maintaining a low tracking error relative to the benchmark[9][15] **Model Evaluation**: The model demonstrated strong performance with positive excess returns over the benchmark index, indicating effective factor utilization and portfolio construction[15] - **Model Name**: CSI 500 Enhanced Portfolio **Model Construction Idea**: Similar to the CSI 300 Enhanced Portfolio, this model focuses on enhancing the performance of the CSI 500 Index by employing quantitative strategies[5][9][15] **Model Construction Process**: The portfolio is built by selecting stocks from the CSI 500 Index based on quantitative factors and optimizing the portfolio to achieve excess returns while controlling tracking error[9][15] **Model Evaluation**: The model underperformed the benchmark index during the observed period, suggesting potential challenges in factor effectiveness or market conditions[15] - **Model Name**: CSI 1000 Enhanced Portfolio **Model Construction Idea**: This model targets the CSI 1000 Index, aiming to generate excess returns through quantitative enhancements[5][9][15] **Model Construction Process**: The portfolio construction involves selecting stocks from the CSI 1000 Index using quantitative factors and optimizing the portfolio for risk-adjusted returns and low tracking error[9][15] **Model Evaluation**: The model showed a slight underperformance relative to the benchmark index, indicating room for improvement in factor application or portfolio optimization[15] - **Model Name**: GARP Portfolio **Model Construction Idea**: The GARP (Growth at a Reasonable Price) portfolio combines growth and valuation factors to identify stocks with strong growth potential at reasonable valuations[32] **Model Construction Process**: Stocks are selected based on a combination of growth metrics (e.g., earnings growth) and valuation metrics (e.g., price-to-earnings ratio). The portfolio is then optimized to balance growth and valuation exposures[32] **Model Evaluation**: The portfolio achieved positive excess returns over the CSI 300 Index, demonstrating the effectiveness of the GARP strategy in the observed period[32] - **Model Name**: Small-Cap Growth Portfolio **Model Construction Idea**: This portfolio focuses on small-cap stocks with strong growth characteristics, aiming to capture the growth premium in the small-cap segment[37] **Model Construction Process**: Stocks are selected from the small-cap universe based on growth factors such as earnings growth and revenue growth. The portfolio is optimized to maximize growth exposure while managing risk[37] **Model Evaluation**: The portfolio delivered positive excess returns over the micro-cap index, indicating the effectiveness of the growth factor in the small-cap segment[37] Model Backtesting Results - **CSI 300 Enhanced Portfolio**: Weekly return 4.69%, excess return 1.90%, tracking error 4.71%, maximum drawdown 1.68%[9][15][22] - **CSI 500 Enhanced Portfolio**: Weekly return 6.34%, excess return -1.58%, tracking error 4.07%, maximum drawdown 3.11%[9][15][16] - **CSI 1000 Enhanced Portfolio**: Weekly return 6.17%, excess return -0.86%, tracking error 5.31%, maximum drawdown 4.45%[9][15][18] - **GARP Portfolio**: Weekly return 3.62%, excess return 0.84%, tracking error 13.93%, maximum drawdown 4.04%[32][33] - **Small-Cap Growth Portfolio**: Weekly return 4.95%, excess return 0.49%, tracking error 11.60%, maximum drawdown 9.76%[37][40] Quantitative Factors and Construction Methods - **Factor Name**: Market Capitalization (Size) Factor **Factor Construction Idea**: This factor captures the size effect, where smaller companies tend to outperform larger companies over time[42] **Factor Construction Process**: Stocks are ranked by their market capitalization, and the top 10% (large-cap) and bottom 10% (small-cap) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the size factor's performance[41][42] **Factor Evaluation**: The factor showed mixed performance, with large-cap stocks outperforming small-cap stocks in the observed period[42] - **Factor Name**: Price-to-Book Ratio (PB) Factor **Factor Construction Idea**: This factor identifies undervalued stocks based on their price-to-book ratios[42] **Factor Construction Process**: Stocks are ranked by their PB ratios, and the top 10% (high PB) and bottom 10% (low PB) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the PB factor's performance[41][42] **Factor Evaluation**: The factor underperformed during the observed period, with high PB stocks outperforming low PB stocks[42] - **Factor Name**: Expected Net Profit Adjustment Factor **Factor Construction Idea**: This factor captures the impact of expected net profit adjustments on stock performance[53] **Factor Construction Process**: Stocks are ranked by their expected net profit adjustments, and the top 10% (high adjustment) and bottom 10% (low adjustment) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance[41][53] **Factor Evaluation**: The factor delivered positive returns, indicating its effectiveness in identifying stocks with favorable profit adjustments[53] Factor Backtesting Results - **Market Capitalization (Size) Factor**: Multi-market excess returns: -0.79% (All Market), 4.83% (CSI 300), -5.59% (CSI 500), -2.47% (CSI 1000)[42][43][48] - **Price-to-Book Ratio (PB) Factor**: Multi-market excess returns: -4.01% (All Market), -5.52% (CSI 300), -6.06% (CSI 500), -5.68% (CSI 1000)[42][43][48] - **Expected Net Profit Adjustment Factor**: Multi-market excess returns: 0.57% (All Market), 0.86% (CSI 300), 1.89% (CSI 500), -0.58% (CSI 1000)[53][54][55]

Quantitative Models and Construction Methods - **Model Name**: CSI 300 Enhanced Portfolio **Model Construction Idea**: The model aims to enhance the performance of the CSI 300 Index by leveraging quantitative strategies to generate excess returns over the benchmark[5][9][15] **Model Construction Process**: The portfolio is constructed by applying factor-based selection and weighting methodologies to the CSI 300 Index constituents. Factors such as valuation, growth, and momentum are utilized to optimize the portfolio's performance relative to the benchmark[15] **Model Evaluation**: The model demonstrates consistent excess returns over the CSI 300 Index, indicating its effectiveness in capturing alpha through quantitative strategies[15] - **Model Name**: CSI 500 Enhanced Portfolio **Model Construction Idea**: Similar to the CSI 300 Enhanced Portfolio, this model focuses on outperforming the CSI 500 Index by employing quantitative factor-based strategies[5][9][15] **Model Construction Process**: The portfolio is optimized using factors such as valuation and growth, applied to the CSI 500 Index constituents. The model aims to achieve a balance between risk and return while maintaining a low tracking error relative to the benchmark[15] **Model Evaluation**: The model shows moderate excess returns, though its performance is less consistent compared to the CSI 300 Enhanced Portfolio[15] - **Model Name**: CSI 1000 Enhanced Portfolio **Model Construction Idea**: This model targets excess returns over the CSI 1000 Index by leveraging quantitative factor-based strategies tailored to small-cap stocks[5][9][15] **Model Construction Process**: Factors such as momentum and growth are applied to the CSI 1000 Index constituents. The portfolio construction process emphasizes capturing the unique characteristics of small-cap stocks while managing risk[15] **Model Evaluation**: The model effectively captures alpha in the small-cap segment, with consistent excess returns over the benchmark[15] - **Model Name**: GARP Portfolio **Model Construction Idea**: The Growth at a Reasonable Price (GARP) strategy combines growth and valuation factors to identify stocks with strong growth potential at reasonable valuations[32] **Model Construction Process**: Stocks are selected based on a combination of growth metrics (e.g., earnings growth) and valuation metrics (e.g., price-to-earnings ratio). The portfolio is then optimized to balance growth and valuation characteristics[32] **Model Evaluation**: The GARP portfolio demonstrates strong long-term performance, though short-term results may vary depending on market conditions[32] - **Model Name**: Small-Cap Growth Portfolio **Model Construction Idea**: This model focuses on small-cap stocks with high growth potential, leveraging factors such as earnings growth and momentum[39] **Model Construction Process**: Stocks are selected from the small-cap universe based on growth and momentum factors. The portfolio is constructed to maximize exposure to these factors while managing risk[39] **Model Evaluation**: The portfolio shows strong performance in capturing growth opportunities in the small-cap segment, though it may be sensitive to market volatility[39] Model Backtesting Results - **CSI 300 Enhanced Portfolio**: - Weekly excess return: 0.19%[15] - Monthly excess return: 2.63%[15] - Annual excess return: 8.82%[15] - **CSI 500 Enhanced Portfolio**: - Weekly excess return: -0.10%[15] - Monthly excess return: -0.07%[15] - Annual excess return: 4.72%[15] - **CSI 1000 Enhanced Portfolio**: - Weekly excess return: 0.47%[15] - Monthly excess return: 0.96%[15] - Annual excess return: 4.67%[15] - **GARP Portfolio**: - Weekly excess return: -0.13%[32] - Monthly excess return: 1.53%[32] - Annual excess return: 23.51%[32] - **Small-Cap Growth Portfolio**: - Weekly excess return: 0.55%[39] - Monthly excess return: 5.00%[39] - Annual excess return: -6.37%[39] Quantitative Factors and Construction Methods - **Factor Name**: Market Capitalization (Size) **Factor Construction Idea**: This factor captures the performance difference between small-cap and large-cap stocks[42] **Factor Construction Process**: Stocks are ranked by market capitalization, and the top 10% (small-cap) and bottom 10% (large-cap) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance[41][42] **Factor Evaluation**: The factor shows strong performance in favor of small-cap stocks, particularly in the short term[42] - **Factor Name**: Price-to-Book Ratio (PB) **Factor Construction Idea**: This valuation factor identifies undervalued stocks based on their book value relative to market price[42] **Factor Construction Process**: Stocks are ranked by PB ratio, and the top 10% (low PB) and bottom 10% (high PB) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance[41][42] **Factor Evaluation**: The factor's performance is mixed, with periods of underperformance in certain market conditions[42] - **Factor Name**: Return on Equity (ROE) **Factor Construction Idea**: This profitability factor identifies companies with high returns on equity, indicating efficient use of capital[53] **Factor Construction Process**: Stocks are ranked by ROE, and the top 10% (high ROE) and bottom 10% (low ROE) are selected to form long and short portfolios, respectively. The difference in returns between these portfolios represents the factor's performance[41][53] **Factor Evaluation**: The factor demonstrates consistent positive returns, particularly in the long term[53] Factor Backtesting Results - **Market Capitalization (Size)**: - Weekly long-short return: 0.20%[42] - Monthly long-short return: -6.40%[42] - Annual long-short return: 45.24%[43] - **Price-to-Book Ratio (PB)**: - Weekly long-short return: -0.45%[42] - Monthly long-short return: -1.51%[42] - Annual long-short return: -12.78%[43] - **Return on Equity (ROE)**: - Weekly long-short return: 0.65%[53] - Monthly long-short return: 4.49%[53] - Annual long-short return: 2.82%[54]

Core Insights - The report indicates that small-cap and value factors experienced a pullback, while high profitability and high growth factors performed relatively well [1] - The quant stock portfolio of top-performing funds achieved a weekly return of 4.43%, with a cumulative return of 52.54% for 2025 [1] Group 1: Multi-Factor Portfolio Performance - The aggressive and balanced portfolios had weekly returns of -4.10% and -3.85% respectively, underperforming the major indices [10] - For the year-to-date (YTD) 2025, the aggressive and balanced portfolios recorded cumulative returns of 69.47% and 55.27%, significantly outperforming the major indices [11] Group 2: Fund Holdings Performance - The exclusive holdings of top-performing funds yielded a weekly return of 4.43%, outperforming the total index of stock funds by 4.09% [26] - Since December 2025, these holdings have achieved a cumulative return of 7.58%, with an excess return of 6.65% [26] Group 3: Profitability, Growth, and Cash Flow Combination - The combination of profitability, growth, and cash flow achieved a weekly return of 1.12%, outperforming the CSI 300 index by 1.20% [28] - For 2025, this combination has a cumulative return of 88.82%, significantly higher than the CSI 300 index's return of 16.42% [28] Group 4: Low Valuation with Fundamental Support - The PB-profitability preferred portfolio had a weekly return of -2.64%, underperforming the CSI 300 index by 2.57% [30] - For the year-to-date 2025, this portfolio recorded a cumulative return of 19.82%, slightly outperforming the CSI 300 index [31] Group 5: Small-Cap Value and Growth Performance - The small-cap value preferred portfolio 1 had a weekly return of -2.84%, outperforming the micro-cap index by 1.85% [35] - The small-cap growth portfolio recorded a weekly return of -1.94%, outperforming the micro-cap index by 2.75% [39] Group 6: Single Factor Performance - In style factors, large-cap stocks outperformed small-cap stocks, and high-valuation stocks outperformed low-valuation stocks [42] - Technical factors showed negative excess returns across the board, with reversal and turnover factors contributing negatively [46] Group 7: Fundamental Factors - The ROE factor contributed positively, with a multi-factor return of 1.63% for the week [53] - The SUE factor also showed positive returns, indicating strong performance in fundamental analysis [53]