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

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

dc.contributor.author	Salas-Molina, Francisco
dc.contributor.author	Rodríguez-Aguilar, Juan A.
dc.contributor.author	Serrà, Joan
dc.contributor.author	Guillen, Montserrat
dc.contributor.author	Martin, Francisco J.
dc.date.accessioned	2019-05-03T08:46:04Z
dc.date.available	2019-05-03T08:46:04Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/10550/70042
dc.description.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.
dc.language.iso	eng
dc.relation.ispartof	Sort-Statistics And Operations Research Transactions, 2019, vol. 42, num. 1, p. 73-98
dc.rights.uri	info:eu-repo/semantics/openAccess
dc.source	Salas-Molina, Francisco Rodríguez-Aguilar, Juan A. Serrà, Joan Guillen, Montserrat Martin, Francisco J. 2019 Empirical analysis of daily cash flow time-series and its implications for forecasting Sort-Statistics And Operations Research Transactions 42 1 73 98
dc.subject	Economia
dc.title	Empirical analysis of daily cash flow time-series and its implications for forecasting
dc.type	info:eu-repo/semantics/article
dc.date.updated	2019-05-03T08:46:04Z
dc.identifier.doi	https://doi.org/10.2436/20.8080.02.7010.24
dc.identifier.idgrec	131384