What question did this study set out to answer?

This research aims to evaluate the effectiveness of power transformations in forecasting quarterly earnings per share.

March 18, 2026The Accounting Review

Power Transformations in Time-Series Models of Quarterly Earnings per Share.

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Authors

WHW. S. HopwoodUniversity of Illinois Urbana-Champaign JMJ. C. McKeownUniversity of Illinois Urbana-Champaign PNPaul NewboldAstraZeneca (United States)

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Implication

Empirical analysis reports improved earnings forecasts in quarterly time series using power transformations, suggesting a practical enhancement in prediction accuracy.

Key Points

This research aims to evaluate the effectiveness of power transformations in forecasting quarterly earnings per share.
Analyzed various quarterly time series of corporate earnings per share.
Incorporated power transformation into time series models.
Compared forecast accuracy with and without transformation.
Forecasts generated with power transformations showed improved quality.
These forecasts outperformed those made by financial analysts.

Cite This Study

Hopwood et al. (1981) studied this question.

synapsesocial.com/papers/69ba432b4e9516ffd37a42f6 https://doi.org/10.2308/tar-4481803

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Implication

Empirical analysis reports improved earnings forecasts in quarterly time series using power transformations, suggesting a practical enhancement in prediction accuracy.

Power Transformations in Time-Series Models of Quarterly Earnings per Share.

Discussion

Member takes

Implication

Key Points

Cite This Study

Power Transformations in Time-Series Models of Quarterly Earnings per Share.

Discussion

Member takes

Implication

Key Points

Cite This Study

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