Analysts’ annual earnings forecasts and changes to the I/B/E/S database

Review of Accounting Studies - I/B/E/S is a common source of analyst earnings forecast data, and the reliability of these data is important for practice and academic research. Examining a common...     

Disaggregating operating and financial activities: implications for forecasts of profitability

Researchers, practitioners, and standard setters emphasize the importance of disaggregating financial statements into operating and financial activities. However, there is a lack of research demonstrating that this disaggregation improves forecasts of profitability. In this study, we consider whether and when the operating/financial disaggregation improves forecasts of profitability. Contrary to the use of an aggregate forecasting approach by most related prior research, we first show that the operating/financial disaggregation only provides forecast improvement over a benchmark model incorporating aggregate information when the components forecasting approach is used. We also compare the operating/financial disaggregation to the unusual/infrequent disaggregation required by US GAAP. We find that the operating/financial disaggregation yields less accurate forecasts than the unusual/infrequent disaggregation. However, when using the components forecasting approach, we find that the combination of both disaggregations improves forecasts of profitability. Finally, we document that the incremental usefulness of the operating/financial disaggregation relative to a benchmark model incorporating aggregate information is a function of growth and accounting conservatism. Overall, our study provides timely evidence concerning how analysts and investors might best use the operating/financial disaggregation for forecasting profitability.     

The Effect of Measurement Subjectivity Classifications on Analysts' Use of Persistence Classifications When Forecasting Earnings Items

Earnings items are typically classified in financial reports based on their persistence and measurement subjectivity. Archival research examines investors' use of persistence and measurement subjectivity classifications for forecasting and valuation. However, this research typically examines only one of these classifications at a time and ignores the potential interactive implications of an earnings item's persistence and measurement subjectivity classifications. We recruited experienced financial analysts to participate in two experiments that examined the effect of measurement subjectivity classifications on analysts' use of persistence classifications when forecasting earnings items. We find that analysts rely less on an earnings item's persistence classification when measurement subjectivity is high relative to when measurement subjectivity is low. We also find that presentation format affects analysts' use of these two classifications. Specifically, we find that the matrix format (i.e., rows display persistence classifications and columns display measurement subjectivity classifications) facilitates analysts' combined use of persistence and measurement subjectivity classifications relative to the sequential format (i.e., the classifications are displayed separately). These findings suggest that archival research could improve its examination of market participants' use of earnings classifications for forecasting and valuation by recognizing that the implications of an earnings item's persistence classification can vary according to the item's measurement subjectivity classification. By also demonstrating how presentation format affects analysts' use of earnings classifications, our study provides further insights into this fundamental issue in accounting research and standard setting.     

Fair value accounting for liabilities: The role of disclosures in unraveling the counterintuitive income statement effect from credit risk changes

When liabilities are accounted for at fair value, a deterioration of a company’s credit risk results in the reporting of an income statement gain; an improvement in a company’s credit risk results in a loss. Many argue that these income statement effects are counterintuitive and that financial statement-users are likely to misinterpret fair value gains as positive signals and fair value losses as negative signals. Utilizing an experiment with CPAs as participants, we find that these arguments are indeed valid. Specifically, we find that over 70% of the participants incorrectly assess a company’s credit risk as improving (deteriorating) when a fair value gain (loss) is recognized. We also find that disclosures that explicitly specify the relation between the direction of the credit risk change and the income statement effect significantly reduce participants’ misinterpretations, and are more beneficial when fair value gains versus losses are recognized. These findings provide empirical evidence in the debate over the recognition of company-specific credit risk changes and offer direction for improving disclosures in the area of fair value accounting.     

Information Asymmetry Around Earnings Announcements

This study examines bid-ask spreads to determine how the anticipation and release of earnings announcements affect information asymmetry in the stock market. I use regression analysis and find that bid-ask spreads are negatively related to public information availability and positively related to earnings variability and the market reaction to prior unexpected earnings. The results suggest that firms for which earnings is expected to yield a relatively larger stock market reaction have greater information asymmetry than firms for which earnings are expected to yield a smaller market reaction.I also find that bid-ask spreads gradually increase in the four days prior to earnings announcements, and increase sharply the day prior to, the day of and the day after the earnings announcements. Bid-ask spreads seven to ten days after earnings announcements are not significantly different from bid-ask spreads seven to ten days prior to earnings announcements.     

An Incomplete Audit at the Earnings Announcement: Implications for Financial Reporting Quality and the Market's Response to Earnings

There has been a substantial increase, since 2004, in the number of firms that announce annual earnings before audit completion as opposed to after audit completion. In this study, we argue that earnings announced before audit completion are associated with lower financial reporting quality and investor perceptions that earnings are more likely to be overstated. Consistent with this expectation, we document that the market places more (less) weight on good (bad) earnings news for earnings announced after audit completion relative to earnings announced before audit completion. We continue to find this differential market response when we expand the returns window to include the 10‐K filing date, suggesting that the differential response is not driven by investors' temporary concerns about earnings revisions between the earnings announcement and the 10‐K filing date or by differential GAAP disclosures in the earnings announcement, as suggested in prior research. Finally, as a direct test of financial reporting quality, we show that earnings announced with a completed audit are less likely to be restated in the future, are less likely to meet or beat expectations, and are associated with fewer income‐increasing discretionary accruals than those announced with an incomplete audit.     

Using Asset Turnover and Profit Margin to Forecast Changes in Profitability

Financial statement analysis textbooks advocate disaggregating profitability into asset turnover and profit margin in performing financial analysis. In spite of the prominence of this technique, there is no evidence demonstrating its usefulness in a forecasting context. We provide evidence that disaggregating return on assets into asset turnover and profit margin does not provide incremental information for forecasting the change in return on assets one year ahead, but that disaggregating the change in return on assets into the change in asset turnover and the change in profit margin is useful in forecasting the change in return on assets one year ahead.     

Information friction and investor home bias: A perspective on the effect of global IFRS adoption on the extent of equity home bias

This paper provides a perspective on the effect of IFRS adoption on the tendency of investors to under-invest in foreign equities. We consider explanations for the equity home bias described in prior research and discuss research relevant to the informational consequences of global adoption of IFRS. Specifically, we evaluate whether IFRS adoption reduces information processing costs or decreases investor uncertainty about either the quality of financial reporting or the distribution of future cash flows. We predict that the effect of any reduction in information processing costs from the adoption of IFRS is likely to be small relative to the effects of other determinants of home bias such as the strength of investor protection mechanisms in foreign countries, behavioral biases toward familiar equities, and informational advantages related to geographical proximity. We argue that the quality of the information that investors have (or perceive they have) decreases with distance, conclude that global IFRS adoption is unlikely to affect home bias, and propose avenues for future research.     

Research on the use of financial statement information for forecasting profitability

Research on the use of financial statement information for forecasting profitability has two objectives: (i) to generate improved forecasts of profitability and accurate estimates of firm value; and (ii) to identify market inefficiencies with respect to financial statement information. For these areas of research, this article describes the evolution, provides examples and shares implications of the research. It also discusses opportunities for future research. The article highlights that financial statement analysis research has slowly evolved and has received limited attention from academics. The article argues that there are vast opportunities for impactful research on fundamental analysis and market inefficiencies.