Quantitative Models and Construction Methods - Model Name: Excellent Fund Performance Enhancement Portfolio Construction Idea: Shift from benchmarking broad-based indices to benchmarking active equity funds, leveraging quantitative methods to enhance fund holdings for optimal selection [3][19][51] Construction Process: 1. Benchmark against active equity fund median returns, represented by the mixed equity fund index (885001.WI) [19][51] 2. Select funds based on performance layering, neutralizing return factors to mitigate style concentration risks [51] 3. Optimize portfolio to control deviations in individual stocks, industries, and styles relative to selected fund holdings [52] Evaluation: Demonstrates stability and consistent outperformance against active equity fund medians [51][52] - Model Name: Outperformance Selection Portfolio Construction Idea: Focus on stocks with significant pre- and post-event excess returns triggered by outperformance events [4][57] Construction Process: 1. Filter stocks based on research report titles indicating outperformance and analysts' upward revisions of net profit [4][57] 2. Conduct dual-layer selection using fundamental and technical analysis to identify stocks with both fundamental support and technical resonance [4][57] Evaluation: Consistently ranks in the top 30% of active equity funds annually [57] - Model Name: Brokerage Golden Stock Performance Enhancement Portfolio Construction Idea: Optimize the brokerage golden stock pool to achieve stable outperformance against the mixed equity fund index [5][62] Construction Process: 1. Use the brokerage golden stock pool as the stock selection space and benchmark [5][33] 2. Optimize portfolio to control deviations in individual stocks, industries, and styles relative to the golden stock pool [33][62] Evaluation: Reflects strong research capabilities and consistently ranks in the top 30% of active equity funds annually [62][63] - Model Name: Growth Stability Portfolio Construction Idea: Prioritize stocks with strong excess returns during the golden period of growth stock performance [6][67] Construction Process: 1. Segment growth stock pools based on the number of days until the scheduled financial report disclosure date, prioritizing stocks closer to the disclosure date [6][67] 2. Use multi-factor scoring to select high-quality stocks when sample size is large [6][67] 3. Introduce mechanisms such as weak balance, transition, buffering, and risk avoidance to reduce turnover and mitigate risks [67] Evaluation: Consistently ranks in the top 30% of active equity funds annually [67][68] --- Model Backtesting Results - Excellent Fund Performance Enhancement Portfolio - Annualized return: 20.31% (2012.1.4-2025.6.30) - Excess return vs. mixed equity fund index: 11.83% - Consistently ranks in the top 30% of active equity funds annually [53][56] - Outperformance Selection Portfolio - Annualized return: 30.55% (2010.1.4-2025.6.30) - Excess return vs. mixed equity fund index: 24.68% - Consistently ranks in the top 30% of active equity funds annually [58][60] - Brokerage Golden Stock Performance Enhancement Portfolio - Annualized return: 19.34% (2018.1.2-2025.6.30) - Excess return vs. mixed equity fund index: 14.38% - Consistently ranks in the top 30% of active equity funds annually [63][66] - Growth Stability Portfolio - Annualized return: 35.51% (2012.1.4-2025.6.30) - Excess return vs. mixed equity fund index: 26.88% - Consistently ranks in the top 30% of active equity funds annually [68][71]
主动量化策略周报:大盘股指数创历史新高,四大主动量化组合本周均战胜股基指数-20251025