The Implications of Using Stock-Split Adjusted I/B/E/S Data in Empirical Research

Payne, Jeff L.; Thomas, Wayne B.

doi:10.2308/accr.2003.78.4.1049

Cited by 279 publications

(151 citation statements)

References 12 publications

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“…The results in Skinner and Sloan (2002) suggest that the penalty for missing analysts' forecasts is significantly more prominent for high growth firms. Payne and Thomas (2003) document different results after controlling for classification errors that can arise from using I/B/E/S data adjusted for stock splits/dividends; that is, they find the differential price response for high-growth firms tends to be when firms meet analysts' forecasts-not when they miss. However, both studies indicate that the stock price response to meeting analysts' forecasts is associated with growth.…”

Section: Resultsmentioning

confidence: 95%

“…As discussed in Payne and Thomas (2003), using stock-split adjusted forecast data that is traditionally provided by I/B/E/S can lead to classification errors when trying to determine whether firms MBFE. The classification errors grow in severity over time as stock splits multiply and especially, for high growth firms, which can have relatively large stock split adjustment factors.…”

Section: Descriptive Statisticsmentioning

confidence: 99%

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Abnormal Returns from Predicting Earnings Thresholds

Rees

2005

Rev Acc Stud

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This study examines the performance of a trading strategy based on the prediction of firms concurrently reporting a positive earnings change and meeting analysts' earnings forecasts. The evidence indicates that a model predicting both earnings thresholds concurrently can yield excess returns that are incremental to predicting only one earnings threshold. Further, I find that the prediction of forecast errors is relatively more important than predicting earnings changes as the incremental benefit from predicting earnings changes concurrently with forecast errors is small relative to a model that predicts only forecast errors. The results hold while controlling for various risk factors and known anomalies.Academic research has shown that financial statement analysis can be useful in predicting future earnings changes, which in turn, can yield abnormal profits. 1 and Degeorge et al. (1999) provide evidence suggesting that a positive earnings change is an important earnings threshold that managers strive to obtain. Degeorge et al. (1999) also conclude that meeting analysts' forecasts is another earnings threshold important to managers. 2 In this study, I extend previous research that examines trading strategies based on earnings changes by introducing an additional earnings threshold of meeting/beating analysts' earnings forecasts. Specifically, I examine whether a trading strategy based on the prediction of meeting or beating more than one earnings threshold can be incrementally more profitable than a trading strategy based on only earnings changes.Research evidence suggests that successfully predicting whether firms will meet or beat forecasted earnings (MBFE) can be especially profitable. Bartov et al. (2002), Kasznik andMcNichols (2002), andRees (2002) have all documented a significant stock price premium (penalty) to meeting/beating (missing) analysts' earnings forecasts after controlling for the magnitude of the forecast error. These studies find that within a small window surrounding a firm's earnings announcement, the stock price reaction can be substantial to an earnings surprise of only a penny or less. As the return window expands to allow for earnings preannouncements and other information entering the market, the absolute value of the stock price premium/penalty is increased. Brown and Caylor (2005) find that the market reward to MBFE is greater than meeting other earnings thresholds examined by Degeorge et al. (1999) and .Besides predicting the outcome of meeting more than one earnings threshold, an important factor that distinguishes this research from some previous studies is that

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Section: Resultsmentioning

confidence: 95%

Section: Descriptive Statisticsmentioning

confidence: 99%

Abnormal Returns from Predicting Earnings Thresholds

Rees

2005

Rev Acc Stud

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“…Unexpected earnings (UE) is computed as UE = actual EPS-forecast EPS, where forecast EPS is the most recent quarterly earnings forecast before the earnings announcement date (EAD). 4 Using the most recent individual analyst forecast from the I/B/E/S detail file, rather than the I/B/E/S consensus forecast, avoids measurement error in the I/B/E/S data that potentially results from rounding split-adjusted observations (Baber & Kang, 2002;Payne & Thomas, 2003). 5 To ensure consistency in computing UE, actual EPS also are from I/B/E/S.…”

Section: Data and Samplementioning

confidence: 99%

Stock Price Reaction to Evidence of Earnings Management: Implications for Supplementary Financial Disclosure

2006

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We condition security price reactions to quarterly earnings announcements on whether firms disclose supplementary balance sheet and/or cashflow information that can be used to estimate the consequences of earnings management. Disclosure of supplementary information is voluntary, and thus, we consider the possibility that firms that disclose balance sheet and/or cashflow information differ systematically from firms that do not disclose. Results indicate that investors discount evidence of earnings management at the disclosure date when supplementary information is disclosed. Such results indicate more informed earnings interpretations of quarterly earnings when firms provide balance sheet and/or cashflow information concurrently.

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“…11 We measure forecast errors (AFE) as earnings reported by I/B/E/S less Forecast. We use the non-split-adjusted file to avoid misclassification induced by I/B/E/S split adjustments (Baber and Kang 2002;Payne and Thomas 2003). We deflate AFE by price at the end of the fiscal year, which is roughly 45 days before the fourth-quarter earnings announcement.…”

Section: Defining Market and Analyst Forecast Variablesmentioning

confidence: 99%

Evidence of differing market responses to beating analysts’ targets through tax expense decreases

Gleason

Mills

2008

Rev Acc Stud

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Returns are positive when firms meet or beat analysts' consensus forecasts, but negative when firms miss. Prior research finds little substantial discount for managing earnings to beat the forecasts via accruals generally. We consider whether the market reward for beating the forecast is smaller when firms use tax expense decreases, which are visible and transparent at the earnings announcement date, unlike accruals. When firms beat analysts' forecasts by decreasing their tax expense relative to the third-quarter rate, the market discounts the reward by an economically significant amount: approximately 86%. We document lower persistence of current-year tax changes for those firms that decrease tax expense to beat the target. The observed discount for beating the forecast only because of a third to fourth quarter tax decrease may reflect market perceptions of the lack of persistence of the decrease.

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The Implications of Using Stock-Split Adjusted I/B/E/S Data in Empirical Research

Cited by 279 publications

References 12 publications

Abnormal Returns from Predicting Earnings Thresholds

Abnormal Returns from Predicting Earnings Thresholds

Stock Price Reaction to Evidence of Earnings Management: Implications for Supplementary Financial Disclosure

Evidence of differing market responses to beating analysts’ targets through tax expense decreases

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