Multiplicative model of trend detection and seasonal fluctuations: application to the dynamics of prices for agricultural products

The problem of a trend detection, and periodic and random fluctuations analysis for time series is considered. The problem of the inconsistency of additivity and multiplicativity as two requirements to the methods of selecting components is discussed. This needs developing of alternative methods of time series decomposition with the distinguished components interacting either additively or multiplicatively. A description of additive and multiplicative models for trend detection, seasonal and random fluctuations analysis in the monthly economic data is given. The prices dynamics analysis for agricultural products is considered as an application of the multiplicative model. It justifies the necessity of isolating the trend and seasonal components from the series of monthly prices in order to ensure more efficient planning of agricultural production, reduce risks, and choose optimal storage and sale periods for products, taking into account the action of random factors in the production and sale of products. The expediency of applying the multiplicative version of the component decomposition model for analyzing and forecasting prices is argued. The results of using the model when analyzing the dynamics of prices for certain types of agricultural products in the Irkutsk region are presented.