Cash flow prediction using a grey-box model

Yang Pang, Kwaku Opong, Luiz Moutinho, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)


This paper tackles the problem of financial forecasting by extending methods developed in automation, engineering and computing science. Current methods existing in the literature for firm-level cash flows are first analysed. Then a grey-box modelling method is developed to elevate the performance of cash-flow prediction. Linear panel data modelling is used as a benchmark model. Experiments with out-of-sample tests are used to validate the grey-box approach. Encouragingly, nonlinear grey-box modelling outperforms linear panel data modelling in both one-period-ahead and multi-period-ahead predictions.

Original languageEnglish
Title of host publicationProceesdings of the 21st International Conference on Automation and Computing
Subtitle of host publicationAutomation, Computing and Manufacturing for New Economic Growth, ICAC 2015
Number of pages6
Publication statusPublished - 30 Oct 2015
Event21st International Conference on Automation and Computing, ICAC 2015 - University of Strathclyde, Glasgow, United Kingdom
Duration: 11 Sep 201512 Sep 2015


Conference21st International Conference on Automation and Computing, ICAC 2015
Country/TerritoryUnited Kingdom


  • cash flow
  • grey-box
  • panel data
  • Prediction

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