Manara - Qatar Research Repository
Browse
1-s2.0-S2214635020303415-main.pdf (446.33 kB)

The prediction of future cash flows based on operating cash flows, earnings and accruals in the French context

Download (446.33 kB)
journal contribution
submitted on 2023-10-03, 09:01 and posted on 2023-10-03, 09:10 authored by Benjamin Noury, Helmi Hammami, A.A. Ousama, Rami Zeitun

This study investigates the aptitudes of the cash-based and accrual-based accounting data for predicting future cash flows from operations in the French context. In addition, our paper aims to investigate the effect of the economic crisis on the prediction of future cash flow. The sample consists of 61 non-financial French listed companies, using annual data over the period 1999–2016.​ The study found that, regardless of the period, the model based on the operating cash flows combined with disaggregate accruals has a stronger explanatory power for predicting future operating cash flows, compared to both earnings and operating cash flows combined with the aggregate accruals models. Moreover, our results show that the aggregation of earnings falsifies the contribution of each accrual item and, as a result, the decomposition of earnings into cash flows and disaggregate accrual enables a much more accurate explanation of future operating cash flows.

Other Information

Published in: Journal of Behavioral and Experimental Finance
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.jbef.2020.100414

Funding

Open Access funding provided by the Qatar National Library

History

Language

  • English

Publisher

Elsevier BV

Publication Year

  • 2020

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • College of Business and Economics - QU

Geographic coverage

France

Usage metrics

    Qatar University

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC