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On Predictability of Revisioning in Corporate Cash Flow Forecasting

Knoell, Florian; Setzer, Thomas; Laubis, Kevin

Financial services within corporations usually are part of an information system on which many business functions depend. As of the importance of forecast quality for financial services, means of forecast accuracy improvement, such as data-driven statistical prediction techniques and/or forecast support systems, have been subject to IS research since decades. In this paper we consider means of forecast improvement due to regular patterns in forecast revisioning. We analyze how business forecasts are adjusted to exploit possible improvements for the accuracy of forecasts with lower lead time. The empirical part bases on an unique dataset of experts' cash flow forecasts and accountants' actuals realizations of companies in a global corporation. We find that direction and magnitude of the final revision in aggregated forecasts can be related to suggested targets in earnings management, providing the means of improving the accuracy of longer-term cash flow forecasts.

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Verlagsausgabe §
DOI: 10.5445/IR/1000079445
Veröffentlicht am 26.01.2018
Cover der Publikation
Zugehörige Institution(en) am KIT Forschungszentrum Informatik, Karlsruhe (FZI)
Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 03.01.2018
Sprache Englisch
Identifikator ISBN: 978-0-9981331-1-9
KITopen-ID: 1000079445
Erschienen in Proceedings of the 51st Hawaii International Conference on System Sciences (HICSS-51), Big Island, HI, January 3-6, 2018
Verlag HICSS, Big Island, HI
Seiten 1583-1589
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