Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2018

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

  • Dades identificatives

    Identificador: RP:2474
    Handle: https://hdl.handle.net/20.500.11797/RP2474
    Autors:
    Martin, Francisco J.Guillen, MontserratSerrà, JoanRodríguez-Aguilar, Juan A.Salas-Molina, Francisco
    Resum:
    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.

  • Altres:

    Autor/s de la URV: Martin, Francisco J. Guillen, Montserrat Serrà, Joan Rodríguez-Aguilar, Juan A. Salas-Molina, Francisco
    Paraules clau: Statistics, forecasting, cash flow, non-linearity, time-series
    Resum: 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.
    Any de publicació de la revista: 2018
    Tipus de publicació: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article

  • Paraules clau:

    Statistics, forecasting, cash flow, non-linearity, time-series

  • Documents:

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