1. Report Industry Investment Rating There is no information about the report industry investment rating in the given content. 2. Core Viewpoints of the Report - The heavy use of factors with a reversal - like logic causes quantitative portfolios to under - allocate high - volatility stocks, leading to a deviation in the volatility distribution compared to the benchmark. When high - volatility stocks rise rapidly, the portfolio may underperform the index [4][6][9]. - Using volatility grouping to achieve "volatility neutrality" can control the volatility distribution risk but may result in a loss of excess returns. It is a risk - prevention measure [4][14][16]. - The recommended approach is to stratify individual stocks by volatility and apply different individual stock deviation constraints. Relaxing the constraints on high - volatility stocks can increase excess returns and reduce the maximum drawdown [4][19]. - The quantitative portfolio can obtain more excess returns in high - volatility stocks. Relaxing the constraints is beneficial for the portfolio to perform better [4][21]. - The volatility stratification constraint cannot achieve complete "volatility neutrality", but it can increase the allocation of high - volatility stocks. A more lenient definition of high - volatility stocks is conducive to improving the portfolio's excess returns [4][52][56]. - The volatility stratification constraint can be extended to other indices, generally increasing excess returns and reducing the maximum drawdown [4][58]. 3. Summary According to the Directory 3.1 How to Solve the Problem of the Biased Volatility Distribution in Quantitative Portfolios - **Quantitative portfolios often have a biased volatility distribution**: Four multi - factor portfolios are constructed with the CSI 500 index as the benchmark. Most portfolios under - allocate high - volatility stocks, and the heavy use of factors with a reversal - like logic is the main reason [7][8][9]. - **Using volatility grouping to achieve "volatility neutrality"**: This method can correct the portfolio's volatility distribution, mainly controlling the maximum drawdown. However, it may lead to a decline in excess returns and is more suitable for special periods [14][16][18]. - **Volatility stratification for individual stock deviation constraints is a more recommended solution**: By stratifying stocks into high - volatility and low - volatility groups and applying different deviation constraints, it can increase excess returns and reduce the maximum drawdown. Tightening constraints on high - volatility stocks has the opposite effect [19][20][21]. 3.2 Why Relax Constraints within High - Volatility Stocks? - **Some factors perform better in the high - volatility group**: Factors such as low - volatility, dividend, and growth factors have higher IC values in the high - volatility group. The growth factor shows better offensive performance in the high - volatility group, while the low - volatility factor has a stronger long - term excess return contribution [22][23][30]. - **The dispersion of some factors is higher in the high - volatility group**: The dispersion of factors such as reversal, low - liquidity, momentum, and growth is higher in the high - volatility group, which supports the better performance of the quantitative portfolio in this group [32][33]. - **The real contribution of stratification constraints in the high - volatility group**: After the volatility stratification constraint, the return contribution of over - allocated stocks in the high - volatility group increases significantly, while that of under - allocated stocks remains unchanged or decreases slightly, improving the overall performance of the portfolio [34][35][37]. 3.3 Portfolio Performance under Volatility Stratification Constraints - Overall, the volatility stratification constraint can improve the long - term performance of the portfolio, but the improvement varies by year. It may lead to a decline in excess returns in years when low - volatility factors perform well, and an increase in other years [38][47][48]. 3.4 Some Supplementary Conclusions - **Can volatility stratification constraints achieve "volatility neutrality?"**: Volatility stratification constraints cannot achieve complete "volatility neutrality", but they can increase the allocation of high - volatility stocks compared to the original portfolio [52]. - **Does the division of the high - volatility group have an impact?**: Narrowing the high - volatility group can reduce the maximum drawdown to some extent, but it also leads to a decline in monthly average excess returns. A more lenient definition of high - volatility stocks is beneficial for increasing excess returns [56][57]. - **Can it be applied to other indices?**: The volatility stratification constraint can be extended to other indices such as the SSE 300 and CSI 1000, generally increasing excess returns and reducing the maximum drawdown [58][59][60].