EARNINGS QUALITY AND EARNINGS FORECASTS BASED ON A CROSS-SECTIONAL MODEL
AbstractThis study examined the effect of earnings quality on the performance of earnings forecasts using a cross-sectional model. Earnings quality is measured by the residuals of a regression analysis that relates working capital accruals to operating cash flows for the current, previous, and next period (SRESID), the lower the earnings quality, the larger the forecasting errors. This result holds for both bias, defined by the difference between the actual and the forecasted values, and accuracy, measured as the absolute value of bias. The relationship between earnings quality and forecasting errors does not change after controlling for other potential earnings attributes. In addition, the basic conclusion remains the same when SRESID is estimated using a time- series model, and when the look-ahead bias inherent in SRESID is removed. These findings suggest that SRESID is useful for market participants in selecting a relevant earnings forecasting model.
Unless otherwise stated, this website and all content within this site are the property of Universiti Teknologi MARA Malaysia and are protected by copyright and other intellectual property laws.
All rights are reserved and users must seek our permission before making any other use of material contained in this site. Modification of any content constitutes a breach of copyright and of Universiti Teknologi MARA Malaysia proprietary rights.