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

  • Francisco Salas-Molina [1] ; Juan A. Rodríguez-Aguilar [3] ; Joan Serrà [4] ; Montserrat Guillen [2] ; Francisco J. Martin [5]
    1. [1] Universitat de València

      Universitat de València

      Valencia, España

    2. [2] Universitat de Barcelona

      Universitat de Barcelona

      Barcelona, España

    3. [3] IIIA-CSIC
    4. [4] Telefonica Research
    5. [5] BigML
    Mostrar afiliaciones +
  • Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 42, Nº. 1, 2018, págs. 73-98
  • Idioma: inglés
  • Enlaces
  • Resumen

    • 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.

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