Core Viewpoint - The report tracks the performance of various active quantitative strategies by GuoXin JinGong, focusing on their ability to outperform the median returns of actively managed equity funds, with specific strategies including "Excellent Fund Performance Enhancement Portfolio," "Expected Surprises Selection Portfolio," "Brokerage Golden Stock Performance Enhancement Portfolio," and "Growth Stability Portfolio" [2][3][18]. Group 1: Performance Overview - The "Excellent Fund Performance Enhancement Portfolio" achieved an absolute return of 2.17% this week and 4.27% year-to-date, ranking in the 64.54th percentile among active equity funds [1][7]. - The "Expected Surprises Selection Portfolio" recorded an absolute return of 3.70% this week and 10.71% year-to-date, ranking in the 27.99th percentile among active equity funds [1][6]. - The "Brokerage Golden Stock Performance Enhancement Portfolio" had an absolute return of 3.11% this week and 7.36% year-to-date, ranking in the 45.26th percentile among active equity funds [1][12]. - The "Growth Stability Portfolio" achieved an absolute return of 4.44% this week and 11.86% year-to-date, ranking in the 22.63rd percentile among active equity funds [1][13]. Group 2: Strategy Summaries - The "Excellent Fund Performance Enhancement Portfolio" is constructed by benchmarking against actively managed equity funds, utilizing quantitative methods to enhance performance based on the holdings of top-performing funds [4][19]. - The "Expected Surprises Selection Portfolio" selects stocks based on expected earnings surprises and analyst upgrades, focusing on both fundamental and technical criteria to build a portfolio of stocks with strong support [6][22]. - The "Brokerage Golden Stock Performance Enhancement Portfolio" is based on a selection of stocks from brokerage recommendations, optimizing the portfolio to minimize deviation from the brokerage stock pool while aiming to outperform the ordinary equity fund index [9][25]. - The "Growth Stability Portfolio" employs a two-dimensional evaluation system for growth stocks, prioritizing stocks closer to their earnings report dates and using multi-factor scoring to select high-quality stocks [11][28]. Group 3: Historical Performance - The "Excellent Fund Performance Enhancement Portfolio" has achieved an annualized return of 20.50% from January 2012 to December 2024, outperforming the benchmark by 12.36% [20][21]. - The "Expected Surprises Selection Portfolio" has an annualized return of 28.53% since January 2010, exceeding the benchmark by 23.02% [23][24]. - The "Brokerage Golden Stock Performance Enhancement Portfolio" has an annualized return of 19.01% from January 2018 to December 2024, outperforming the benchmark by 14.87% [26][27]. - The "Growth Stability Portfolio" has achieved an annualized return of 34.74% since January 2012, exceeding the benchmark by 26.43% [29].

Core Viewpoint - The article emphasizes the importance of a multi-strategy dynamic allocation approach to capture style rotation opportunities in the market, utilizing quantitative indicators to assess the allocation value of different styles or strategies [1][6]. Summary by Sections Style Timing Framework to Strategy Rotation Model - The style timing model can effectively avoid high-risk phases but may miss some upward opportunities in styles. Historical data is used to identify similar past indicators to predict future performance [3][26]. - A voting method is employed to integrate multiple indicators, resulting in a comprehensive style timing model that has shown to reduce risk while maintaining a lower annualized return compared to holding styles directly [3][31]. Performance Metrics - The style timing model achieved an annualized return of 16.5% during the backtest period from January 1, 2015, to January 31, 2025, with an excess return of 12.7% over the benchmark [3][39]. - The active quantitative strategy rotation model yielded an annualized return of 36.2% during the backtest period from January 1, 2015, to February 28, 2025, outperforming the benchmark by 28.5% [4][39]. Key Indicators for Style Allocation - The article identifies key indicators for measuring style allocation value, including valuation difference, active inflow rate difference, and combination temporal correlation [2][17]. - Historical data shows that a larger valuation difference correlates with better future excess returns, while a significant active inflow rate difference indicates potential overreaction risks [2][10]. Latest Insights and Recommendations - As of March 2025, the recommendation is to favor small-cap and growth styles while maintaining a neutral stance on value and dividend styles [4][35]. - The report suggests holding indices like the CSI 2000 for small-cap and the National Growth Index for growth styles, along with specific active quantitative strategies [4][35]. Multi-Dimensional Timing Indicators - The article discusses the construction of a multi-dimensional timing indicator system that includes valuation difference, market participation, and combination consistency to assess future style performance [18][22]. - The effectiveness of these indicators is tested, showing that they can provide valuable insights into future excess returns across different styles [22][23]. Strategy Rotation and Dynamic Allocation - The article outlines a strategy for dynamic allocation and rotation among styles based on multi-dimensional timing indicators, aiming to optimize returns while managing risks [37][39]. - The dynamic allocation strategy is designed to adjust holdings based on the prevailing market conditions and style performance indicators [37][39].

Core Viewpoint - The report tracks the performance of various active quantitative strategies by GuoXin JinGong, focusing on their ability to outperform the median returns of actively managed equity funds, with specific strategies including "Excellent Fund Performance Enhancement Portfolio," "Expected Surprises Selection Portfolio," "Brokerage Golden Stock Performance Enhancement Portfolio," and "Growth Stability Portfolio" [2][3][19]. Group 1: Performance Overview - The "Excellent Fund Performance Enhancement Portfolio" had an absolute return of -3.35% this week and 2.06% year-to-date, ranking in the 60.77 percentile among active equity funds [1][7]. - The "Expected Surprises Selection Portfolio" achieved an absolute return of -1.97% this week and 6.75% year-to-date, ranking in the 27.36 percentile among active equity funds [6][8]. - The "Brokerage Golden Stock Performance Enhancement Portfolio" reported an absolute return of -2.03% this week and 4.12% year-to-date, ranking in the 43.96 percentile among active equity funds [12][10]. - The "Growth Stability Portfolio" had an absolute return of -2.32% this week and 7.11% year-to-date, ranking in the 25.48 percentile among active equity funds [13][14]. Group 2: Strategy Descriptions - The "Excellent Fund Performance Enhancement Portfolio" aims to outperform the median returns of actively managed equity funds by utilizing a quantitative approach based on the holdings of top-performing funds [19][21]. - The "Expected Surprises Selection Portfolio" selects stocks based on expected earnings surprises and analyst upgrades, focusing on both fundamental and technical criteria to build a portfolio [23][24]. - The "Brokerage Golden Stock Performance Enhancement Portfolio" leverages the stock pool identified by brokerage analysts, optimizing the selection to enhance performance relative to the ordinary equity fund index [26][27]. - The "Growth Stability Portfolio" employs a two-dimensional evaluation system for growth stocks, prioritizing those with upcoming earnings announcements to capture potential excess returns [29][30].