The Predictive Ability and Usefulness of Accounting Operating Cash Flows

Evidence is provided of the usefulness of accounting cash flow (CF) data to investors and creditors by examining the predictive ability of quarterly operating cash flows. In this study, moving window spectral (MWS) analysis, a frequency domain approach, is applied to accounting time series data for the first time. This method is adopted because of its unique ability to capture trend and cyclical components in the data. Our results show that cash flows can be reliably predicted using aggregate data on a firm by firm basis. In addition, our results outperform the results previously reported in the accounting literature. If the FASB were to require CF disclosures on a segment basis, we believe further improvement in prediction would be possible, thereby enhancing the usefulness of reported CF data. This research provides insight into the properties of accounting time series data not possible from a strictly time domain analysis