Core Viewpoint - The article analyzes the lack of price momentum in the Chinese A-share market, attributing it to a tug-of-war between retail and institutional investors, particularly on news and non-news days [2][3]. Group 1: Price Momentum Analysis - The absence of price momentum in the Chinese A-share market is due to the "tug-of-war" between retail and institutional investors, where price overshooting on news days is corrected on non-news days, leading to an overall insignificant momentum effect [5][6]. - On news days, retail investors tend to overreact, causing price spikes, while institutional investors sell on non-news days to correct these price adjustments, especially for stocks that performed well on news days [5][6]. Group 2: Retail and Institutional Investor Behavior - Retail investors show a significant increase in trading activity on news days, as indicated by a rise in Baidu search index and posts on stock forums, leading to an imbalance in buying and selling [11][12]. - Institutional investors increase selling activity on non-news days, particularly for stocks that had positive news, which contributes to the correction of price overshooting [5][6]. Group 3: Positive News Ratio and Returns - A strategy based on the positive news ratio yields a monthly return of 0.67%, with a risk-adjusted return of 0.93%, indicating that stocks with a higher ratio of positive news tend to perform better [5][6]. - The analysis shows that the positive news ratio is a significant predictor of subsequent stock returns, with higher returns associated with stocks that have a greater proportion of positive news [15][18]. Group 4: Order Imbalance and Trading Patterns - The average daily order imbalance on news days shows a significant buy-sell imbalance, particularly for small trades, while non-news days exhibit a sell imbalance [13][14]. - Retail attention, measured through search indices and forum posts, is notably higher on news days compared to non-news days, reflecting increased investor engagement during these periods [11][12]. Group 5: Methodology and Data Sources - The study employs a behavioral finance framework to analyze the differences in returns on news and non-news days, utilizing data from various sources including news sentiment analysis and trading volume metrics [26][30]. - The sample period for the analysis spans from July 2012 to December 2021, focusing on stocks with market capitalizations above the bottom 30% of all A-share stocks [9][10].

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