Francisco Salas Molina, Juan A. Rodríguez Aguilar, Joan Serrà, Montserrat Guillén Estany, Francisco J. Martin
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.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados