Realization of the complex forecast of an enterprise's cash flows

Authors

DOI:

https://doi.org/10.15587/2312-8372.2017.99137

Keywords:

cash, cash flow, trend model, predictor, balance of variables, forecasting quality

Abstract

The object of research is a complex forecasting of cash flows on the example of PJSC «Odeskabel», which is the largest producer of cable products in Ukraine and abroad. A lot of attention has been paid to the development of a system of forecasting and financial planning of cash flows in modern conditions in scientific economic literature in recent years. However, the issues of determining the most accurate and reliable methods for forecasting cash flows is still open.

There are many mathematical-statistical prediction methods in the literature. They have certain advantages and disadvantages and often give quite satisfactory results in the analysis and forecasting of the series of dynamics that are considered in isolation. However, the situation changes fundamentally when a simultaneous prediction of several interrelated variables is carried out.

In order to avoid these shortcomings in medium- and long-term forecasting of variables between which there are objective interrelations, we propose to supplement the traditional methods of choosing trend forms with the principle of the balance of variables. It can be summarized as follows: the final conclusion about the acceptability of certain analytical functions for the choice of the best predictor is determined by the degree of compliance of the predicted values of the variables to the balance ratio.

The most balanced forecast of the inflows, outflows and net cash flow of PJSC «Odeskabel» using the variable balance criterions provided by the predictor when the series of dynamics of all three investigated indicators are described by a parabola of the second degree. In this prediction the trend coefficients that describe the dynamics of net cash flow are approximately equal to the difference in the corresponding trend coefficients describing the change in the cash in flows and outflows.

The proposed criterion realizes sort of the impossible: it provides a foothold in the future. Therefore, it is quite logical to choose as a predictor such a combination of analytical functions of the studied variables that will ensure the most balanced value of the forecast data.

Author Biographies

Oleksandr Iankovyi, Odessa National Economic University, 8, Preobrazhenska str., Odessa, Ukraine, 65082

Doctor of Economic Sciences, Professor

Department of Economic of Enterprises and Entrepreneurship Organization

Halina Koshelek, Odessa National Economic University, 8, Preobrazhenska str., Odessa, Ukraine, 65082

PhD, Associate Professor

Department of Economic of Enterprises and Entrepreneurship Organization

Volodymyr Iankovyi, Odessa National Economic University, 8, Preobrazhenska str., Odessa, Ukraine, 65082

PhD, Associate Professor

Department of Economy and Planning of Business

References

  1. Tennent, J. (2012). Guide to Cash Management: How to Avoid a Business Credit Crunch. Economist Books, 224.
  2. Bernstein, L., Wild, J. (1999). Analysis of Financial Statements. Ed. 5. McGraw-Hill Education, 529.
  3. Poddierohin, A. M., Nevmerzhytskyi, Ya. I. (2007). Efektyvnist upravlinnia hroshovymy potokamy pidpryiemstva. Finansy Ukrainy, 10, 119–127.
  4. Blank, I. A. (2002). Upravlenie denezhnymi potokami. Kyiv: Nika-Tsentr, Elga, 736.
  5. Kovaliov, V. V. (2015). Upravlenie denezhnymi potokami, pribyl'iu i rentabel'nost'iu. Moscow: Prospekt, 338.
  6. Perevozchikov, A. G. (2006). Prognozirovanie denezhnogo potoka na osnove otraslevyh pokazatelei iz sbornikov finstat. Audit i finansovyi analiz, 3, 142–147.
  7. Salyla, S. Ya., Zavadska, N. O. (2012). Trendovyi analiz hroshovykh potokiv yak zasib informatsiinoho zabezpechennia protsesu biudzhetuvannia v upravlinskomu obliku. Biznes Inform, 6, 178–187.
  8. Bertoneche, M., Knight, R. (2001). Financial Performance. Elsevier, 208. doi:10.1016/b978-075064011-4.50000-4
  9. Iankovyi, O. (1993). Prognozirovanie sotsial'no-ekonomicheskih pokazatelei na osnove printsipa balansa peremennyh. Ekonomika i matematicheskie metody, 29 (1), 108–118.
  10. Chetyrkin, E. M. (1977). Statisticheskie metody prognozirovaniia. Moscow: Statistika, 200.
  11. Iankovyi, O. (2015). Latentni oznaky v ekonomitsi. Odesa: Atlant, 168.
  12. Ivahnenko, A. G., Miuller, I. A. (1985). Samoorganizatsiia prognoziruiushchih modelei. Kyiv: Tehnika, 223.
  13. Stock market infrastructure development agency of Ukraine (SMIDA). Available: https://smida.gov.ua/

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Published

2017-03-30

How to Cite

Iankovyi, O., Koshelek, H., & Iankovyi, V. (2017). Realization of the complex forecast of an enterprise’s cash flows. Technology Audit and Production Reserves, 2(4(34), 52–56. https://doi.org/10.15587/2312-8372.2017.99137

Issue

Section

Economics and Enterprise Management: Original Research