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

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.