You can identify the nature of changes in the value of Y in time and predict this parameter in the future using the moving average. Y is a characteristic of the occurrence under investigation (for example, a price which running in a certain period of time) and it is the dependent variable. X are time intervals and constant variable. The time-series is a set of interconnected values of X and Y. As a result, a smoothed dynamic range of values is obtained which makes it possible to clearly trace the trend of changes in the parameter. ![]() The choice of intervals is carried out by the slip-line method: the first levels are gradually removed, and the subsequent levels are switched on. The essence: the absolute values of a time-series change to average arithmetic values at certain intervals. The moving average method is one of the empirical methods for smoothing and forecasting time-series. Let’s consider the use of the moving average method in more detail. You can implement such effective forecasting methods using Excel tools like exponential smoothing, regression construction, moving average. ![]() Practical modeling of economic situations implies the development of forecasts. Calculation of the moving average in Excel and forecasting
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