Cash flow disaggregation and prediction of cash flow
Abstract
Purpose
The purpose of this paper is to investigate the incremental information content of estimates of cash flow components in predicting future cash flows.
Design/methodology/approach
The authors examine whether the models incorporating components of operating cash flow from income statements and balance sheets using the direct method are associated with smaller prediction errors than the models incorporating core and non-core cash flow.
Findings
Using data from US and UK firms and multiple regression analysis, the authors find that around 60 per cent of a current year’s cash flow will persist into the next period’s cash flows, and that income statement and balance sheet variables persist similarly. The explanatory power and predictive ability of disaggregated cash flow models are superior to that of an aggregated model, and further disaggregating previously applied core and non-core cash flows provides incremental information about income statement and balance sheet items that enhances prediction of future cash flows. Disaggregated models and their components produce lower out-of-sample prediction errors than an aggregated model.
Research limitations/implications
This study improves our appreciation of the behaviour of cash flow components and confirms the need for detailed cash flow information in accordance with the articulation of financial statements.
Practical implications
The findings are relevant to investors and analysts in predicting future cash flows and to regulators with respect to disclosure requirements and recommendations.
Social implications
The findings are also relevant to financial statement users interested in better predicting a firm’s future cash flows and thereby, its firm’s value.
Originality/value
This paper contributes to the existing literature by further disaggregating cash flow items into their underlying items from income statements and balance sheets.
Keywords
Citation
Khansalar, E. and Namazi, M. (2017), "Cash flow disaggregation and prediction of cash flow", Journal of Applied Accounting Research, Vol. 18 No. 4, pp. 464-479. https://doi.org/10.1108/JAAR-02-2015-0011
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited