Core Viewpoint - The article discusses the construction and performance of a "limited attention" factor in stock selection, highlighting how investor attention is a scarce resource that influences market behavior and stock performance [1][2]. Limited Attention Factor Construction - The traditional efficient market hypothesis assumes that investors can instantaneously process all new information, but in reality, investors have limited attention, leading to non-rational decision-making [2]. - The "limited attention" factor is constructed using four indicators: abnormal turnover rate, abnormal trading volume, extreme returns, and whether a stock appears on the "Dragon and Tiger List" [3][4]. - The construction methods include linear combination and random forest, with the latter showing better predictive power for returns [4][5]. Factor Performance - The performance of the limited attention factor indicates that stocks with higher attention levels attract more retail investor interest, leading to short-term price increases but often resulting in poor long-term performance [7][8]. - The factor's effectiveness is more pronounced in smaller stock pools, where retail investors' behavior can significantly impact stock prices [13][12]. Implications of Limited Attention Factor - The limited attention factor can signal "money-making effects" in the market, particularly during certain periods when retail investors chase high-attention stocks [14][17]. - The factor's IC (Information Coefficient) shows a correlation with market conditions, suggesting that it can be used for market timing and sector rotation strategies [19][22]. Application of Limited Attention Factor - The factor can be directly used in index enhancement strategies by either adding it to existing predictive models or excluding high-limited attention stocks from selection [25][30]. - Different methods of applying the factor yield varying results, with the addition of the factor generally enhancing performance in larger stock pools [30][41]. - The analysis of other factors within the limited attention domain reveals that growth and low volatility factors perform better, while profitability and value factors show decreased effectiveness [32][41].