Model for Identifying and Forecasting Components of Time Series of Prices for Agricultural Products
Year: 2024
Type: article
Abstract: A mathematical model for the allocation of monthly or quarterly data on the dynamics of prices for agricultural products of three components is presented. One of them is the trend — the general trend of price changes. The second is seasonal fluctuations, repeated with a period equal to a year, deviations of the actual price from the trend. The model provides for the possibility of changing the shape and amplitude of seasonal deviations over time. The third component is the residual term, which is sometimes interpreted as random deviations. The estimation of parameters defining a specific expression of trend and seasonal fluctuations is carried out in the model by minimizing the weighted sum of squared deviations. An example of calculating the trend and seasonal fluctuations in the price of one of the types of agricultural products for 2019–2023 on this model is given.
Language: English
Field: Decision Sciences
Domain: Social Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W4411069476