Academic journal article Accounting Horizons

The Impact of Split Adjusting and Rounding on Analysts' Forecast Error Calculations

Academic journal article Accounting Horizons

The Impact of Split Adjusting and Rounding on Analysts' Forecast Error Calculations

Article excerpt

SYNOPSIS: This study finds that analysts' forecast data files, commonly used by accountants and financial analysts to estimate market expectations about earnings announcements, contain inaccurate historical data for companies that split their common stock. These inaccuracies result because stock split adjustments are made retrospectively and split-adjusted data are rounded. Moreover, because well-performing firms are more likely to execute stock splits, the consequences of the stock split problem are systematic, potentially distorting both time-series and cross-sectional characteristics of forecast errors. The analysis also demonstrates that the problem can influence interpretations of security price reactions to earnings announcements. To illustrate this point, we report evidence suggesting that errors induced by rounding split-adjusted data alter conclusions about how investors interpret earnings that meet, but do not exceed, the consensus forecast.

INTRODUCTION

The use of analysts' forecasts of earnings per share (BPS) is pervasive among practitioners and academics. A typical use presumes that the consensus forecast indicates EPS anticipated by market participants, and that a difference between reported EPS and the consensus forecast reflects the surprise in accounting earnings disclosures. The importance of determining the surprise component in earnings is well known, and thus, the properties of analysts' forecast data are investigated frequently in both the academic and the practice-oriented literature (e.g., Kahn and Rudd 1999; Abarbanell and Lehavy 2000).

This paper describes a potential inaccuracy from using historical analysts' forecast data for firms that split their common stock. More specifically, in commonly used analysts' forecast data files, both forecasted and actual earnings per share are rounded to the nearest cent after making retroactive and cumulative stock split adjustments. (1) The consequence of this practice is that comparisons of actual and forecast earnings for firms that execute stock splits are less precise than comparisons for firms that do not split their stock. (2)

For example, assume that the consensus analysts' forecast EPS is $0.10 and the actual EPS is $0.09, and that the firm subsequently executes a 2-for-1 stock split. Both the forecast and the actual EPS are reported as $0.05 after rounding to the nearest cent. Thus, data from the forecast files erroneously indicate that earnings "meet" the consensus forecast, even though actual earnings reported at the disclosure date differed from the consensus expectation.

Using the quarterly EPS database compiled by First Call during 1993-1999, we find that approximately 22 percent of the observations have retroactive split adjustments that potentially compromise the accuracy of the forecast errors. Consistent with evidence reported in prior studies (Asquith et al. 1989; Lakonishok and Lev 1987), we find that observations affected by the split adjustment differ systematically from observations not affected by splits. Split-adjusted observations show greater accounting performance, pre- and post-announcement period stock price performance, sales growth, and systematic risk, but lower book-to-market and debt-to-asset ratios. Thus, errors induced by rounding split-adjustment data do not occur randomly. While the systematic loss of accuracy in forecast errors can be tolerated in many situations, it can have a material impact in others, especially when the analysis focuses on small forecast errors.

Investigating Stock Splits and Stock Returns

To illustrate how stock splits can affect empirical relations, we examine stock returns associated with "on-target" earnings announcements, defined as earnings announcements where EPS exactly meets the consensus earnings forecast. Meeting the consensus forecast is often presumed to be "good news" (Levitt 1998; Dechow et al. …

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