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

Identifier:  RP:2474

Handle: https://hdl.handle.net/20.500.11797/RP2474

Authors:  Martin, Francisco J.; Guillen, Montserrat; Serrà, Joan; Rodríguez-Aguilar, Juan A.; Salas-Molina, Francisco

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.