Empirical analysis of daily cash flow time-series and its implications for forecasting

Francisco Salas-Molina, Juan A. Rodríguez-Aguilar, Joan Serrà, Montserrat Guillen, Francisco J. Martin

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

Abstract

© 2018 Institut d'Estadistica de Catalunya. All Rights Reserved. Usual assumptions on the statistical properties of daily net cash flows include normality, absence of correlation and stationarity. We provide a comprehensive study based on a real-world cash flow data set showing that: (i) the usual assumption of normality, absence of correlation and stationarity hardly appear; (ii) non-linearity is often relevant for forecasting; and (iii) typical data transformations have little impact on linearity and normality. This evidence may lead to consider a more data-driven approach such as time-series forecasting in an attempt to provide cash managers with expert systems in cash management.
Original languageEnglish
Pages (from-to)73-98
JournalSORT
Volume42
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Cash flow
  • Forecasting
  • Non-linearity
  • Statistics
  • Time-series

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