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Analytical debiasing of corporate cash flow forecasts


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Blanc, Sebastian M. ; Setzer, Thomas:
Analytical debiasing of corporate cash flow forecasts.
In: European Journal of Operational Research. 243 (2015) 3. - S. 1004-1015.
ISSN 0377-2217


Link zum Volltext (externe URL): https://doi.org/10.1016/j.ejor.2014.12.035


We propose and empirically test statistical approaches to debiasing judgmental corporate cash flow forecasts. Accuracy of cash flow forecasts plays a pivotal role in corporate planning as liquidity and foreign exchange risk management are based on such forecasts. Surprisingly, to our knowledge there is no previous empirical work on the identification, statistical correction, and interpretation of prediction biases in large enterprise financial forecast data in general, and cash flow forecasting in particular. Employing a unique set of empirical forecasts delivered by 34 legal entities of a multinational corporation over a multi-year period, we compare different forecast correction techniques such as Theil’s method and approaches employing robust regression, both with various discount factors. Our findings indicate that rectifiable mean as well as regression biases exist for all business divisions of the company and that statistical correction increases forecast accuracy significantly. We show that the parameters estimated by the models for different business divisions can also be related to the characteristics of the business environment and provide valuable insights for corporate financial controllers to better understand, quantify, and feedback the biases to the forecasters aiming to systematically improve predictive accuracy over time.

Weitere Angaben

Schlagwörter:Analytics; Judgmental Forecasting; Forecast Bias Correction; Cash Flow Forecasting
Institutionen der Universität:Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > Lehrstuhl für Allgemeine Betriebswirtschaftslehre und Wirtschaftsinformatik
DOI / URN / ID:10.1016/j.ejor.2014.12.035
Titel an der KU entstanden:Nein
Eingestellt am:25. Sep 2020 11:49
Letzte Änderung:06. Okt 2020 15:59
URL zu dieser Anzeige:http://edoc.ku-eichstaett.de/24886/