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

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

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Salas-Molina, Francisco; Rodríguez-Aguilar, Juan A.; Serrà, Joan; Guillen, Montserrat; Martin, Francisco J.
This document is a artículoDate2019

Este documento está disponible también en : http://hdl.handle.net/10550/70042
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.

    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
https://doi.org/10.2436/20.8080.02.7010.24

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