Knowledge that Transforms

Accounting big baths are pervasive in practice. While big baths can improve the information environment and reduce information asymmetry, they can also degrade the information environment and obscure operating performance. In this study, we examine the role of management ethics. Specifically, we investigate whether managers’ truthfulness (or conversely, deceptiveness) affects how investors perceive big baths. Using linguistic analysis on earnings-conference calls to measure managerial deception and employing a difference-in-differences research design with propensity-score matching, we find that information asymmetry is significantly higher following big baths taken by deceptive CEOs, compared with big baths taken by less deceptive CEOs.

This paper investigates the usefulness of the real-time macroeconomic news-flow as a leading indicator of firm-level end-of-quarter realized earnings. Using recent advances in macroeconomics, I develop a nowcasting model for quarterly earnings and provide two main findings. First, I show that my model provides out-of-sample expectations that are as accurate as analysts’ forecasts. Second, macroeconomic news embedded in my nowcasts is not fully incorporated into investors’ earnings expectations and predicts future abnormal returns around earnings announcements. These findings have three main implications for capital markets research. First, real-time macroeconomic news can be used to update earnings expectations in real-time. Second, there are economic benefits of doing so, as evidenced by the magnitude of risk-adjusted returns around earnings announcements. Third, after three decades of almost nonexistent research on time-series models for quarterly earnings, the door is open again for fruitful research in this area.

We examine the value relevance of inflation-adjusted (IA) and historical cost (HC) amounts in a hyperinflationary economy. Using a unique dataset drawn from annual reports of firms listed on the Zimbabwe Stock Exchange from 2000 to 2005, we find that both sets of amounts are value relevant but HC amounts are superior to IA amounts. We also show that inflation gains and losses provide incremental information content beyond that provided by the HC amounts and that the power of this incremental content model is equivalent to that of the HC model but superior to that of the IA model. Further analyses indicate that, in periods of relatively low inflation, HC amounts are more value relevant, while in periods of relatively high inflation, the two sets of amounts are equally value relevant. Finally, we show that HC amounts have a greater ability to predict future cash flows than IA amounts, which suggests that the superiority of their value relevance stems from this.

This study investigates the efficacy of a fundamental analysis-based approach to screen U.S. bank stocks. We construct an index (BSCORE) based on fourteen bank–specific valuation signals. We document a positive association between BSCORE and future profitability changes, as well as current and one-year-ahead stock returns, implying that BSCORE captures forward looking information that the markets are yet to impound. A hedge strategy based on BSCORE yields positive hedge returns for all but two years during our 1994–2014 sample period. Results are robust to partitions of size, analyst following, and exchange listing, and persist after adjusting for risk factors. We further document a positive relation between BSCORE and future analyst forecast surprises as well as earnings announcement period returns, and a negative relation between BSCORE and future performance-based delistings. Overall, our results show that a fundamental analysis-based approach can provide useful insights for analyzing banks.