Examines the empirical association between trading volume and belief revisions that differ among individual analysts. Hypothesis based on relative positions of individual analysts' current and prior forecasts of earnings to measure differential belief revisions.

[This study examines the association between trading volume and belief revisions. Most trading volume theories suggest that investors' differential belief revisions cause trading volume. A belief revision is differential if it changes the position of an individual's expectation relative to the distribution of expectations held by others. Thus, I use the correlation between the relative positions of individual analysts' current and prior forecasts of earnings to measure differential belief revisions. In a multiple regression analysis, this correlation measure explains trading volume beyond that explained by prior dispersion in forecasts, which is consistent with Karpoff's (1986) prediction that trading is caused by both differential prior beliefs and differential belief revisions.]

This study reports the results of an experiment showing that auditor assessments of litigation risk and planned audit investments are higher when potential errors overstate financial performance than when those errors understate performance. This result is much stronger in the presence of high levels of litigation risk in the client’s industry. These results suggest that in industries where litigation risk is high audited financial statements may contain more unintentional material understatement errors than overstatement errors. Thus, litigation risk—through its effect on auditors—may encourage financial statements that understate firm performance

This study provides evidence that differential interpretations are an important stimulus for speculative trading. We measure differential interpretations using data on analysts' revisions of forecasts of annual earnings after the announcement of quarterly earnings that are components of those annual earnings numbers. We find two conditions under which differential interpretations play a significant role in explaining trading. First, we present empirical evidence supporting Kandel and Pearson's (1995) argument that trading coincident with small price changes reflects investors' differential interpretations of information. This evidence is important because it is inconsistent with conventional models of trade that assume homogeneous interpretations. Second, we also find that differential interpre? tations explain a significant amount of the trading occurring in a sample where trading volume is higher than the (firm-specific) non-announcement period average. This result is consistent with informed traders acting on their differential interpretations when there is enough liquidity trading to help camouflage their own information-based trades. In sum, the study's results confirm Bachelier's (1900) intuition that differential interpretations are an important stimulus for trading.

This study examines the predictive value of Management Discussion and Analysis (MD&A) information. More specifically, this study tests the association between properties of analysts' earnings forecasts and MD&A quality, where MD&A quality is measured by the Securities Exchange Commission (SEC). We find that high MD&A ratings are associated with less error and less dispersion in analysts' earnings forecasts after controlling for many other expected influences on analysts' forecasts. We also find that estimated regression coefficients are consistent with MD&A information having a substantial effect on earnings forecasts. Finally, we find our results are driven by forward‐looking disclosures about capital expenditures and operations, and also by historical disclosures about capital expenditures. These findings are consistent with the suggestion by many constituencies (including the SEC) that the type of information found in high quality MD&A is particularly relevant for predicting earnings.

Most theoretical models of trade (Pfleiderer, 1984; Grundy and McNichols, 1989; Holthausen and Verrecchia, 1990; Kim and Verrecchia, 1991; Blume et al., 1994) imply that the trading volume prompted by a public announcement is positively related to the announcement's precision. Relying upon this notion, empirical researchers interpret high trading volume as an indication that an announcement is highly informative. We argue that such interpretations are not, in general, correct. In a world with transaction costs, the relation between information precision and trading volume is ambiguous and can be negative. This explains why, in empirical tests using data from actual markets, the relation between announcement precision and trading volume is not monotonically positive, even though in laboratory experiments it is. Our results imply that trading volume reactions to public announcements are most sensitive to announcement precision among low-transaction cost securities and in low-cost trading regimes.

ABSTRACT: This paper examines the ex ante effects of public information quality on market prices and how such effects vary with information asymmetry among traders in a two-period experimental market. We vary public information quality by changing its precision and information asymmetry among traders by varying the distribution of private signals. We find high-quality public disclosure leads to increased price efficiency and decreased cost of capital in the pre-announcement period when information asymmetry is high. The impending high-quality public information increases the competition among informed traders, which leads prices to impound more private information and alleviates the adverse selection problems facing uninformed traders. Our study suggests building a high-quality public information environment (e.g., by adopting high-quality accounting standards or committing to transparent disclosure policies) would likely provide ex ante benefits for firms with significant adverse selection among traders.

[This paper investigates the association between aspects of investors' disagreement around earnings announcements and investors' trading decisions. Theory suggests that trading volume arises because of investor disagreement, but disagreement is a multi-faceted construct. We find that three distinctly different aspects of disagreement each play an incremental role in explaining trading volume around earnings announcements, even after controlling for the magnitude of the contemporaneous price change. These aspects of disagreement are: dispersion in prior beliefs, change in dispersion, and belief jumbling. Dispersion in prior beliefs is the level of variation in expectations before the earnings announcement, change in dispersion is the difference in the level of dispersion in beliefs after vs. before the earnings announcement, and belief jumbling occurs when investors' beliefs change positions relative to each other around the earnings announcement. Our results indicate that each of these three aspects of disagreement is associated with investors' real economic (i.e., trading) decisions around earnings announcements.]

In this study we examine changes in the precision and the commonality of information contained in individual analysts' earnings forecasts, focusing on changes around earnings announcements. Using the empirical proxies suggested by the Barron et al. (1998) model that are based on the across-analyst correlation in forecast errors, we conclude that the commonality of information among active analysts decreases around earnings announcements. We also conclude that the idiosyncratic information contained in these individual analysts' forecasts increases immediately after earnings announcements, and that this increase is more significant as more analysts revise their forecasts. These results are consistent with theories positing that an important role of accounting disclosures is to trigger the generation of idiosyncratic information by elite information processors such as financial analysts (Kim and Verrecchia 1994, 1997).