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Daily Cash Forecasting and Seasonal Resolution: Alternative Models and Techniques for Using the Distribution Approach

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  • Miller, Tom W.
  • Stone, Bernell K.

Abstract

Daily cash forecasting generally requires some method to reflect day-of-month and day-of-week effects. It requires the resolution of multiple seasonals, a problem given scant treatment in the econometrics literature. This paper first presents multiplticative and mixed-effects specifications of day-of-month and day-of-week effects as alternatives to the additive specifications. Then, several important estimation issues pertinent to each specification are investigated, namely collinearity, holiday effects, length-of-month distortion, varying weekly-monthly pattern mix, and daily-monthly consistency. The paper develops a broad class of distribution-based linear forecasting models in great generality similar to the way that Box and Jenkins [1] provide a broad class of time-series models that can be specialized via parameter selection (specification). In our case, parameter selection (specification) gives particular members of the linear class of distribution models. A particular version can be tested against an alternative specification via hypothesis tests on model parameters.

Suggested Citation

  • Miller, Tom W. & Stone, Bernell K., 1985. "Daily Cash Forecasting and Seasonal Resolution: Alternative Models and Techniques for Using the Distribution Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 20(3), pages 335-351, September.
    • Handle: RePEc:cup:jfinqa:v:20:y:1985:i:03:p:335-351_01
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    Cited by:

    1. Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll., 2017. "Empowering cash managers to achieve cost savings by improving predictive accuracy," International Journal of Forecasting, Elsevier, vol. 33(2), pages 403-415.
    2. Francisco Salas-Molina & Juan A. Rodríguez-Aguilar & Montserrat Guillen, 2023. "A multidimensional review of the cash management problem," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-35, December.
    3. Francisco Salas-Molina & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Montserrat Guillen & Francisco J. Martin, 2016. "Empirical analysis of daily cash flow time series and its implications for forecasting," Papers 1611.04941, arXiv.org, revised Jun 2017.
    4. Berezhkovskii, A.M. & Zitserman, V.Yu., 1992. "Multidimensional activated rate processes with slowly relaxing mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 187(3), pages 519-550.
    5. Francisco Salas-Molina & Juan A. Rodríguez-Aguilar, 2018. "Data-driven multiobjective decision-making in cash management," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 77-91, June.

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