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

Published online by Cambridge University Press:  06 April 2009

Tom W. Miller  and
Bernell K. Stone
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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.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 20 , Issue 3 , September 1985 , pp. 335 - 351
Copyright
Copyright © School of Business Administration, University of Washington 1985

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References

[1]Box, E. P., and Jenkins, M.. Time Series Analysis: Forecasting and Control. Revised edition. San Francisco: Holden-Day (1976).Google Scholar
[2]Daniel, C., and Wood, F. S.. Fitting Equations to Data. New York: John Wiley & Sons (1971).Google Scholar
[3]Draper, N. R., and Smith, H.. Applied Regression Analysis. New York: John Wiley & Sons (1966).Google Scholar
[4]Furnwal, G. M., and Wilson, R. W. M. Jr, “Regression by Leaps and Bounds.” Technometrics, Vol. 16 (1974), pp. 499–511.Google Scholar
[5]Hocking, R. R. “The Analysis and Selection of Variables in Linear Regression.” Biometrics, Vol. 32 (1976), pp. 1–49.Google Scholar
[6]Little, D. C. “Models and Managers: The Concept of a Decision Calculus.” Management Science, Vol. 16 (04 1970), pp. B–466 to B–485.Google Scholar
[7]Maier, S. F.; Robinson, D. W. and Weide, J. H. Vander. “A Short-Term Disbursement Forecasting Model.” Financial Management, Vol. 10 (Spring 1981), pp. 9–20.Google Scholar
[8]Montgomery, D. C., and Peck, E. A.. Introduction to Regression Analysis. New York: John Wiley & Sons (1980).Google Scholar
[9]Rinne, H., and Wood, R. A.. “Daily Sales Measurement and Control.” Working Paper, Finance Department, Penn State University (11 1983).Google Scholar
[10]Sharpe, K. L., and Tweedy, D. L.. “Cash Forecasting: A New Approach at Boise Cascade.” Working Paper, Boise Cascade Corp. (1982).Google Scholar
[11]Stone, B. K. “The Payments-Pattern Approach to the Forecasting and Control of Accounts Receivable.” Financial Management, Vol. 5 (Autumn 1976), pp. 65–82.CrossRefGoogle Scholar
[12]Stone, B. K., and Wood, R. A.. “Daily Cash Forecasting: A Simple Method for Implementing the Distribution Approach.” Financial Management, Vol. 6 (Fall 1977), pp. 40–50.CrossRefGoogle Scholar
[13]Stone, B. K., and Miller, T. W.. “Daily Cash Forecasting: A Structuring Framework.” Journal of Cash Management, Vol. 1 (10 1981), pp. 35–50.Google Scholar
[14]Theil, H.Principles of Econometrics. New York: John Wiley & Sons, Inc. (1971).Google Scholar
[15]Thompson, M. L. “Selection of Variables in Multiple Regression: Part I. A Review and Evaluation.” International Statistical Review, Vol. 46 (1978), pp. 1–19.CrossRefGoogle Scholar
[16]Thompson, M. L. “Selection of Variables in Multiple Regression: Part II. Chosen Procedures, Computations and Examples.” International Statistical Review, Vol. 46 (1978), pp. 129–146.CrossRefGoogle Scholar