This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Although analyst forecasts are generally more accurate than time-series model forecasts (e.g., O'Brien [1988]), analyst forecasts are not clearly superior to time-series model forecasts as a proxy for expected earnings (e.g., Brown et al. [1987b]). Recent research has concluded that earnings expectations reflected in stock prices at least partially reflect a seasonal random walk (SRW) model (Bernard and Thomas [1990] and Abarbanell and Bernard [1992]). In particular, Ball and Bartov [1996] find that market earnings expectations incorporate the sign of the serial correlation in seasonally differenced earnings but underestimate the correlation magnitude (see also Maines and Hand [1996]). These findings suggest that at least some market participants ignore public information in forming expected earnings; I examine whether information usage is correlated with investor sophistication and/or the degree to which investors are informed.
Lynn Rees, Pieter Elgers, The Market's Valuation of Nonreported Accounting Measures: Retrospective Reconciliations of Non-U.S. and U.S. GAAP, Journal of Accounting Research, Vol. 35, No. 1 (Spring, 1997), pp. 115-127
This study investigates whether the Auditing Standards Board's (ASB's) Statement on Auditing Standards No. 82 (AICPA [1997]) requiring auditors to separately assess the risk of fraud will lead auditors to spend more time reading fraud cues and design audit plans that are more sensitive to fraud risk. In this paper, fraud means intentionally misstating the financial statements. Auditors' ability to detect fraud has received significant attention from researchers, practitioners, legislators, and policymakers (see, e.g., Albrecht and Willingham [1993], National Commission