Identifying Price Informativeness
提出并估计了价格信息含量的度量方法，通过回归资产价格变化对收益变化的响应来识别相对信息含量，并应用于美国股票面板数据，发现大市值、高换手率、高特质波动、高机构持股和分析师覆盖的股票信息含量更高，且信息含量分布的中位数、均值和标准差自1980年代中期以来持续上升。
Abstract We identify and estimate price informativeness, a necessary step in testing theories of information aggregation. Starting from a pricing equation and a stochastic process for payoffs, we show how to recover relative price informativeness from regressions of asset price changes on changes in payoffs. Applying our identification results, we estimate a panel of stock-specific measures of informativeness for U.S. stocks. In the cross-section, large stocks with high turnover, idiosyncratic volatility, institutional ownership, and analyst coverage have higher informativeness. In the time series, the median, mean, and standard deviation of the distribution of informativeness have steadily increased since the mid-1980s.