1）异常换手率 $\Sigma_{\text{}}Turnover=\dfrac{Turnover_{i,d}}{\Sigma_{\text{}}Turnover_{i,d}}$ $$\Sigma\,T u r n o v e r_{i,d-t}/252$$ 其中分子是股票当个交易日的换手率，分母是股票过去252个交易日的平均换手率，最后将股票的日度异常换手率按月取平均，可以得到股票的月度异常换手率指标。 2）异常成交量 $$A B\_{V o l u m n}={\frac{V o l u m n_{i,d}}{\sum V o l u m n_{i,d-t}/252}}$$ 1.有限关注因子构建 传统对金融市场的研究通常基于以下核心假设：金融市场能够对所有新信息作出瞬时识别，并将其完全反映至资产价格中，从而形成对资产价值的最优估计，也就是所谓的强 有效市场。然而，这一理论框架隐含着一个关键前提：投资者需要持续且全面地关注各类信息，并将其精准纳入投资决策流程。Kahneman（1973）首次提出 "投资者关注度 是一种稀缺资源" 的理论，指出个人投资者在现实场景中，除了股票市场，还需将精力分配至家庭与工作等 ...

Core Insights - The report constructs a "limited attention" factor that represents the degree of retail investor attention on individual stocks, using indicators such as abnormal turnover, abnormal trading volume, extreme returns, and whether the stock has appeared on the "Dragon and Tiger List" [3][6][56] - The limited attention factor can indicate a "money-making effect," showing a high success rate for timing signals, with an overall monthly success rate exceeding 70% when applied to the CSI 300 index [3][25][56] - The factor performs better in smaller stock pools, indicating that retail investors' "herding behavior" can lead to significant price fluctuations in these stocks [3][56] Limited Attention Factor Construction - The construction of the limited attention factor is based on the premise that retail investors prioritize stocks that attract their attention, leading to a focus on high turnover, high trading volume, and extreme returns [6][8] - The factor is constructed using both linear combination and random forest methods, with the latter showing better predictive power for returns [13][14][19] Performance of the Limited Attention Factor - The performance of the limited attention factor is evaluated through its information coefficient (IC) and the average change in shareholder accounts, indicating a clear relationship between higher attention levels and increased retail investor interest [18][19] - The factor's IC and monthly long-short returns are notably higher in the CSI 1000 index, aligning with the logic that smaller stocks are more susceptible to retail investor behavior [22][24] Money-Making Effect Indication - The report highlights that the limited attention factor's IC can reflect the strength of the market's "money-making effect," particularly during the period from 2019 to mid-2021 when retail investors showed strong interest in high attention stocks [25][27][32] - The correlation between the limited attention factor's IC and industry trend consistency indicates that higher IC values suggest better market performance [29][30] Application of the Limited Attention Factor - The factor can be directly used in index enhancement strategies, either by adding it to existing models or by excluding stocks with high limited attention [35][37] - The report finds that directly adding the limited attention factor improves performance in the CSI 300 and CSI 500 indices, while both methods fail to enhance returns in the CSI 1000 index [40][57] Performance of Other Factors in Limited Attention Domains - The report identifies that price-volume factors, particularly low volatility, low liquidity, and long-term momentum, perform significantly better in the limited attention domain, while profitability, valuation, and dividend factors show decreased effectiveness [41][42][43] - The analysis of different stock pools reveals that the performance of factors varies significantly between limited attention and non-limited attention stocks, with growth and price-volume factors being more effective in the former [41][44]