TítuloEmpirical analysis of daily cash flow time-series and its implications for forecasting
Publication TypeJournal Article
Year of Publication2018
AuthorsSalas-Molina F, Rodríguez-Aguilar JA, Serrà J, Guillén M, Martin F
JournalSORT-Statistics and Operation Research Transactions
Volume42
Incidencia1
Paginación73-98
Date Published01/2018
EditorialStatistical Institute of Catalonia
Palabras clavecash flow, forecasting, non-linearity, statistics, time-series
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.