Accruals and Forecasting

40 Pages Posted: 14 Mar 2019 Last revised: 18 Mar 2019

See all articles by K.C. Kenneth Chu

K.C. Kenneth Chu

Hong Kong Polytechnic University - School of Accounting and Finance

James A. Ohlson

Hong Kong Polytechnic University - School of Accounting and Finance

Date Written: February 19, 2019

Abstract

Sloan (1996), Richardson et al. (2005, 2006) examine how firms’ accruals relate to subsequent financial performance. They identify a negative correlation and attribute it to accruals lack of reliability. This paper considers the issue from a different starting point: we forecast sales and expenses separately and argue on prior grounds that accruals are generally informative about the changes/growth in the income statement items. Two accruals variables serve as the primary predictors, year-to-year changes in operating assets and operating liabilities. This framework thus implies 2 forecasting equations and where the RHS of each includes the 2 accrual variables, plus controlling variables. Traditional accounting concepts can be applied to gauge the expected magnitudes of the 2x2 load-factors. Moreover, this framework leads to the hypothesis that the 2 accrual variables have a negative effect on the ROA and earnings forecasts, consistent with the literature. However, a closer look at the estimated load-factors shows some subtleties. First, liability accruals are markedly more informative than asset accruals. Second, while both accrual variables forecast ROA robustly, a shift to earnings weakens the results. Third, the 2 accrual variables are more informative about future performance in case of smaller firms. The empirics also highlight the ways in which financial assets and liabilities influence the forecasting and how their effects differ from those of the (operating) accruals.

Keywords: Accruals, Forecasting, Sales, Expenses

JEL Classification: M41

Suggested Citation

Chu, Kenneth and Ohlson, James A., Accruals and Forecasting (February 19, 2019). Available at SSRN: https://ssrn.com/abstract=3340355 or http://dx.doi.org/10.2139/ssrn.3340355

Kenneth Chu (Contact Author)

Hong Kong Polytechnic University - School of Accounting and Finance ( email )

M1059, Li Ka Shing Tower
Hung Hom, Kowloon
Hong Kong, Hong Kong 000000
Hong Kong

James A. Ohlson

Hong Kong Polytechnic University - School of Accounting and Finance ( email )

M715, Li Ka Shing Tower
Hung Hom, Kowloon
China

Register to save articles to
your library

Register

Paper statistics

Downloads
94
rank
271,355
Abstract Views
606
PlumX Metrics
!

Under construction: SSRN citations will be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information