URV's Author/s: Martin, Francisco J. Guillen, Montserrat Serrà, Joan Rodríguez-Aguilar, Juan A. Salas-Molina, Francisco

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

Abstract: 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.

Journal publication year: 2018

Publication Type: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article