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On Predictability of Revisioning in Corporate Cash Flow Forecasting

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dc.contributor.author Knöll, Florian
dc.contributor.author Setzer, Thomas
dc.contributor.author Laubis, Kevin
dc.date.accessioned 2017-12-28T00:50:47Z
dc.date.available 2017-12-28T00:50:47Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50084
dc.description.abstract 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.
dc.format.extent 7 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Service Analytics
dc.subject Financial Decision Analytics, Corporate Cash Flow, Forecast Revision Process, Organizational Bias, Judgmental Forecasting
dc.title On Predictability of Revisioning in Corporate Cash Flow Forecasting
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.197
Appears in Collections: Service Analytics


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