Voluntary Disclosure, Management forecasts, Intraindustry effect, Information dissemination

[Pownall et al. (1993) document that nearly 80 percent of their sample of voluntary management earnings forecasts are not precise point forecasts. Imprecise forecast forms include closed-interval forecasts (i.e., ranges), open-interval forecasts (i.e., minimums and maximums), and general impressions about firms' earnings prospects. We perform cross-sectional logistic regressions to document determinants of forecast precision. Our sample consists of 1,212 annual and interim management forecasts. After controlling for firm-specific and horizon-specific earnings uncertainty, we find that managers produce more precise forecasts of annual earnings for firms with greater analyst following (our proxy for private information) and for smaller firms (our proxy for public information). The results are robust across subsamples. The majority of the results, however, do not hold for interim forecasts.]

[This study investigates the relation between financial analyst earnings forecast revisions and two independent variables: (1) a measure of management earnings forecast news issued prior to analyst revisions, and (2) measures derived from the security market price reaction to that news. Results indicate that security price reactions to management forecasts are useful in predicting subsequent analyst forecast revisions. Furthermore, the explanatory power of price reaction is a function of the timing of the management forecast release.]

[This study examines the effects of management forecast precision (i.e., lack of uncertainty) on equity pricing and the assessment of earnings uncertainty. Kim and Verrecchia (1991) modeled the price reaction to the public release of information as a positive function of both the unexpected component of the information and the information's precision. We test these predictions with a sample of 868 management forecasts for 1983-1986 annual and interim earnings. The use of management forecasts rather than actual earnings to test the precision hypothesis has the distinct advantage that the level of forecast precision is not directly regulated and thus may vary across forecasts. Further, managers explicitly disclose their level of uncertainty. Both this study and Pownall et al. (1993) document that most forecasts are open-interval (minimums and maximums), closed-interval (ranges), or general impressions rather than point estimates. The method used to test the precision hypothesis removes restrictions on the traditional regression of unexpected returns on unexpected earnings. Specifically, the slope and intercept coefficients that map unexpected earnings into unexpected returns can vary in the cross-section as a function of forecast precision. Our results support a direct relation between forecast precision and the importance of management forecasts for security pricing. Holthausen and Verrecchia (1990) and Morse et al. (1991) modeled a decrease in investors' consensus as a positive function of the magnitude of signal surprise and the dispersion of the perceived precision of the signal. We examine these predictions with a sample of 221 point and closed-interval (range) forecasts. We calculate whether the range of outcomes disclosed by a manager exceeds the range of Institutional Brokers Estimate System (IBES) analyst forecasts. We find this variable and the magnitude of unexpected security returns (a proxy for signal surprise) to be positively associated with increases in the standard deviation of IBES analyst forecasts. Morse et al. (1991) found the hypothesized relation between signal surprise and increase in analyst forecast variance, but were unable to separate the precision effect from the signal surprise effect. Managers' explicit labeling of forecasts as more uncertain through range disclosure permits the direct calculation of management forecast precision relative to analyst forecast precision. Our tests involve joint hypotheses of the effects of forecast precision on security prices and the credibility of managers' disclosures of forecast precision. Ajinkya and Gift (1984) developed and tested the "expectations adjustment hypothesis" which posits sufficient incentives for credible, symmetric forecast disclosure. King et al. (1990) argued that expectations adjustment also suggests credible labeling of the precision of forecasts.]

Pownall et al. (1993) document that nearly 80 percent of their sample of voluntary management earnings forecasts are not precise point forecasts. Imprecise forecast forms include closed-interval forecasts (i.e., ranges), open-interval forecasts (i.e., minimums and maximums), and general impressions about firms' earnings prospects. We perform cross-sectional logistic regressions to document determinants of forecast precision. Our sample consists of 1,212 annual and interim management forecasts. After controlling for firm-specific and horizon- specific earnings uncertainty, we find that managers produce more precise forecasts of annual earnings for firms with greater analyst following (our proxy for private information) and for smaller firms (our proxy for public information). The results are robust across subsamples. The majority of the results, however, do not hold for interim forecasts.

This study investigates the relation between financial analyst earnings forecast revisions and two independent variables: (1) a measure of management earnings forecast news issued prior to analyst revisions, and (2) measures derived from the security market price reaction to that news. Results indicate that security price reactions to management forecasts are useful in predicting subsequent analyst forecast revisions. Furthermore, the explanatory power of price reaction is a function of the timing of the management forecast release.

Using a sample of 856 management earnings forecasts, we provide evidence that managers release larger shock‐earnings forecasts in nontrading periods. Our results do not depend on whether the magnitude of the shock is measured exogenously (unexpected accounting earnings) or endogenously (security market reaction). The timing effects are more pronounced for less‐precise (i.e., open‐interval and closed‐interval) forecasts. Also, we provide evidence of an overnight reaction to closed‐period management forecast releases. Our results are consistent with explanations for voluntary disclosure that rely on a precommitted policy of information asymmetry reduction (see Diamond 1985; King, Pownall, and Waymire 1990). These explanations lead to predictions of strategic timing of greater shocks in the nontrading period in order to provide the less‐informed with a period for information evaluation. Résumé. À partir d'un échantillon de 856 prévisions de bénéfices publiées par la direction de diverses entreprises, les auteurs démontrent que les prévisions publiées par les gestionnaires en période où les titres ne sont pas négociés ont davantage d'impact. Les résultats qu'ils obtiennent ne dépendent pas du caractère exogène (bénéfices comptables inattendus) ou endogène (réaction du marché des valeurs mobilières) de la mesure de l'impact. L'effet du choix du moment est plus prononcé pour les prévisions moins précises (c'est‐à‐dire à intervalle ouvert et à intervalle fermé). Les auteurs démontrent aussi qu'il se produit une réaction à la publication de prévisions par la direction en période de fermeture, dans les vingt‐quatre heures qui suivent la publication. Les résultats de l'étude sont conformes au principe de la présentation facultative d'information dont l'explication repose sur une politique, préalablement adoptée, de réduction de l'asymétrie de l'information (voir Diamond, 1985; King, Pownall et Waymire, 1990). Cette explication mène à des prédictions voulant que l'on choisisse, à des fins stratégiques, les périodes de non‐négociation des titres pour publier les prévisions de bénéfices dont l'impact est plus grand, de manière à laisser aux investisseurs moins bien informés un certain laps de temps pour évaluer l'information.

This study examines the effects of management forecast precision (i.e., lack of uncertainty) on equity pricing and the assessment of earnings uncertainty. Kim and Verrecchia (1991) modeled the price reaction to the public release of information as a positive function of both the unexpected component of the information and the information's precision. We test these predictions with a sample of 868 management forecasts for 1983-1986 annual and interim earnings. The use of management forecasts rather than actual earnings to test the precision hypothesis has the distinct advantage that the level of forecast precision is not directly regulated and thus may vary across forecasts. Further, managers explicitly disclose their level of uncertainty. Both this study and Pownall et al. (1993) document that most forecasts are open-interval (minimums and maximums), closed-interval (ranges), or general impressions rather than point estimates. The method used to test the precision hypothesis removes restrictions on the traditional regression of unexpected returns on unexpected earnings. Specifically, the slope and intercept coefficients that map unexpected earnings into unexpected returns can vary in the cross-section as a function of forecast precision. Our results support a direct relation between forecast precision and the importance of management forecasts for security pricing. Holthausen and Verrecchia (1990) and Morse et al. (1991) modeled a decrease in investors' consensus as a positive function of the magnitude of signal surprise and the dispersion of the perceived precision of the signal. We examine these predictions with a sample of 221 point and closed-interval (range) forecasts. We calculate whether the range of outcomes disclosed by a manager exceeds the range of Institutional Brokers Estimate System (IBES) analyst forecasts. We find this variable and the magnitude of unexpected security returns (a proxy for signal surprise) to be positively associated with increases in the standard deviation of IBES analyst forecasts. Morse et al. (1991) found the hypothesized relation between signal surprise and increase in analyst forecast variance, but were unable to separate the precision effect from the signal surprise effect. Managers' explicit labeling of forecasts as more uncertain through range disclosure permits the direct calculation of management forecast precision relative to analyst forecast precision. Our tests involve joint hypotheses of the effects of forecast precision on security prices and the credibility of managers' disclosures of forecast precision. Ajinkya and Gift (1984) developed and tested the "expectations adjustment hypothesis" which posits sufficient incentives for credible, symmetric forecast disclosure. King et al. (1990) argued that expectations adjustment also suggests credible labeling of the precision of forecasts.