Disclosures, Line-of-business reporting, Segment reporting, Portfolio returns

This paper documents the empirical distributions of daily trading volume prediction errors for several commonly used volume measures and expectation models for individual firms and for portfolios. The prediction errors for raw volume measures are significantly positively skewed, with thin left tails and fat right tails. However, natural log transformations of the volume measures are approximately normally distributed. For longer than one-day prediction intervals, recognition of autocorrelation in daily trading volume is advantageous for detecting abnormal trading. Results of analysis for clustering of events and for different size firms are also presented.

Disclosures, Management forecasts, Market expectations, Bad news disclosures

Abstract Reviews the book "Cost Accounting," by Michael Chatfield and Denis Neilson.

ABSTRACT This study examines whether the information implied by simultaneous levels of option and stock prices (specifically, the implied standard deviation of returns) reflects other contemporaneously available information. The independent contemporaneous measure considered is the observed dispersion (across several financial analysts), at a point in time, in the forecasts of earnings per share for a given firm. The results indicate that implied standard deviations clearly reflect the contemporaneous dispersion in analysts' forecasts incrementally , i.e., beyond the information contained in the historical time series of returns.

Abstract ABSTRACT: This paper evaluates whether the primary and secondary dissemination of earnings forecast revisions by security analysts is reflected in security prices. Security prices were used to determine the profitability (before the cost of search) of trading strategies based on the nonpublic knowledge of forecast revisions. For a sample of 288 weekly earnings forecast revisions, the results were consistent with the hypothesis that early knowledge of forecast revisions could be used to form profitable trading strategies. Furthermore, the secondary dissemination of forecasts continued to have information content at the point of disclosure. These results are inconsistent with the strong form, but consistent with the semi-strong form, of market efficiency. Furthermore, the information contemporaneously available from public sources did not generate equivalently profitable trading rules, indicating that forecast revisions were not deducible from other publicly available information. Finally, some general public policy implications concerning mandatory disclosure of forecasts were drawn.

We investigate the relation of the board of directors and institutional ownership with the properties of management earnings forecasts. We find that firms with more outside directors and greater institutional ownership are more likely to issue a forecast and are inclined to forecast more frequently. In addition, these forecasts tend to be more specific, accurate and less optimistically biased. These results are robust to changes specification, Granger causality tests, and simultaneous equation analyses. The results are similar in the pre– and post–Regulation Fair Disclosure (Reg FD) eras. Additional analysis suggests that concentrated institutional ownership is negatively associated with forecast properties. This association is less negative in the post–Reg FD environment, which is consistent with Reg FD reducing the ability of firms to privately communicate information to select audiences.

[Varian (1985) and Karpoff (1986) showed analytically that trading volume is positively related to the degree of differing beliefs. This study provides empirical evidence on the postulated relationship. The extent of disagreement or dispersion in financial analysts' forecasts of annual EPS for a firm is employed as the proxy for agents' differing beliefs about the firm's prospects. The revision in analysts' mean EPS forecasts, from one month to the next, is used to control for the volume effects of the net information signals emanating during the period. While some researchers have addressed the relation between the level of trading and earnings announcements (Beaver 1968; Morse 1981), and between trading volume and the magnitude of earnings forecast errors (Bamber 1986, 1987), the impact of discordant expectations on trading volume has been the subject of more recent empirical examination (Comiskey et al. 1987; Ziebart 1990; Lang and Litzenberger 1989). The hypothesis tested in this study posits that the fraction of outstanding common shares traded is a positive function of both forecast dispersion and mean forecast revision. While most previous studies of volume have concentrated on specific accounting disclosures, this study examines the trading associated with an almost continuous flow of information about the sampled firms that analysts implicitly use in their periodic revisions of earnings forecasts. Hence, tests of the model become possible at several times during the year, independent of formal accounting events/disclosures. Monthly observations in each of the four years 1978 to 1981 are used for the sample of 420 calendar-year firms; total number of observations is 16,747 over 48 months. Generalized least squares (GLS) estimation is applied to observations pooled over time and cross-sections and for each of the four years separately. Ordinary least squares (OLS) estimations are also performed and reported for comparative purposes and also to assess the stability of the models in monthly cross-sections. The results indicate a significant positive association between the dispersion in analysts' forecasts of annual EPS and the volume of trading. A relatively stable and positive association is found even after controlling for the volume effects of the magnitude of monthly revisions in the mean analysts' (annual) EPS forecast. The evidence corroborates the theoretical result that the degree of heterogeneity in beliefs is a determinant of the intensity of trading.]