May 21st, 2001 | Artyom Durnev, Randall Morck, Bernard Yeung, and Paul Zarowin
The paper examines the relationship between firm-specific stock price variation and the informativeness of stock prices. The authors use data from 1975 to 1995 to measure firm-specific stock return variability and stock price informativeness, defined as how much current stock prices predict future earnings. They find that firms and industries with lower market model $R^2$ statistics exhibit higher association between current returns and future earnings, indicating more information about future earnings in current stock returns. This supports the interpretation that higher firm-specific returns variation reflects more informed trading by arbitrageurs, leading to more efficient stock markets. The findings are consistent with recent research showing that greater firm-specific returns variation is associated with better functioning stock markets and more efficient capital allocation. The paper uses both simple correlations and regression analyses to robustly confirm these results, controlling for various factors that might affect the informativeness of stock prices.The paper examines the relationship between firm-specific stock price variation and the informativeness of stock prices. The authors use data from 1975 to 1995 to measure firm-specific stock return variability and stock price informativeness, defined as how much current stock prices predict future earnings. They find that firms and industries with lower market model $R^2$ statistics exhibit higher association between current returns and future earnings, indicating more information about future earnings in current stock returns. This supports the interpretation that higher firm-specific returns variation reflects more informed trading by arbitrageurs, leading to more efficient stock markets. The findings are consistent with recent research showing that greater firm-specific returns variation is associated with better functioning stock markets and more efficient capital allocation. The paper uses both simple correlations and regression analyses to robustly confirm these results, controlling for various factors that might affect the informativeness of stock prices.