Knowledge that Transforms

Abstract In this paper, we analyze how financial analysts generate information, make decisions about firm coverage, and try to maintain their forecasting accuracy after the passage of Regulation Fair Disclosure (“Reg FD”). Using the model developed by Barron, Kim, Lim, and Stevens 1998, we find that analysts are investing more effort in idiosyncratic information discovery. In order to do this, individual analysts appear to be reducing coverage for well‐followed firms while increasing coverage of firms that were less followed prior to Reg FD. Analysts who had preferential links with firms that they covered, such as analysts from large brokerage houses, tend to have greater forecast accuracy in the pre‐FD period. However, these analysts are unable to sustain their forecasting superiority in the post‐FD period, which suggests that there has been a leveling of the information playing field among analysts. Overall, our results reflect a trend toward greater reliance on idiosyncratic information discovery on part of the financial analysts.

Abstract We model a firm's investment decision, an auditor's effort‐rendering behavior, audit fees, and prices of the firms under two auditor liability rules: strict liability and negligence liability. We show that an auditor's effort level is socially optimal under strict liability, while it is not generally so under negligence liability. Furthermore, both the firm owner's expected benefit and the audit fee are higher under strict liability than under negligence liability. We define the legal error under negligence liability as the difference between the assessed audit effort (that is, the estimate of audit effort made by the court) and the actual audit effort and prove that the greater the variance of the legal error, the more incentive an auditor has to exert effort under negligence liability compared with strict liability. Finally, the number of investments being undertaken could be higher under strict liability because more firm owners are willing to hire auditors to go public.

Abstract In this study, we investigate whether investor perceptions of the financial reporting credibility of Big 5 audits are related to the auditor's economic dependence on the client as measured by nonaudit as well as total (audit and nonaudit) fees paid to the incumbent auditor. We use the client‐specific ex ante cost of equity capital as a proxy for investor perceptions of financial reporting credibility and examine auditor fees both as a proportion of the revenues of the audit firm and as a proportion of the revenues of the audit firm's practice office through which the audit was conducted. Our findings suggest that both nonaudit and total fees are perceived negatively by investors' that is, the higher the fees paid to the auditor, the greater the implied threat to auditor independence, and the lower the financial reporting credibility of a Big 5 audit. Furthermore, our findings appear to be largely unrelated to corporate governance: investors do not perceive the auditor as compensating for weak governance. Separately, recent anecdotal evidence suggests that declining revenues from nonaudit services' as a result of recent regulatory restrictions” are being offset by substantial increases in audit fees. Other things being equal, rising audit fees imply higher profit margins for audit services, indicating that the audit function may no longer be a loss leader. Thus, to the extent that investors perceive total fees negatively, recent regulatory initiatives to limit nonaudit fees may not have adequately addressed the perceived, if not the actual, threat to auditor independence posed by fees.

Abstract Prior literature observes that information uncertainty exacerbates investor underreaction behavior. In this paper, I investigate whether, as professional investment intermediaries, sell‐side analysts suffer more behavioral biases in cases of greater information uncertainty. I show that greater information uncertainty predicts more positive (negative) forecast errors and subsequent forecast revisions following good (bad) news, which corroborates previous findings on the post‐analyst‐revision drift. The opposite effects of information uncertainty on forecast errors and subsequent forecast revisions following good versus bad news support the analyst underreaction hypothesis and are inconsistent with analyst forecast rationality or optimism suggested in prior literature.