Price Forecasting of Feed Raw Materials Used in Dairy Farming: A Methodological Comparison

Year 2024, Volume: 12 Issue: 3, 249 - 280, 31.12.2024

Merve Kılınç Yılmaz , Yusuf Şahin , Kenan Oğuzhan Oruç

https://doi.org/10.17093/alphanumeric.1504096

Abstract

Milk is among the products of strategic importance for countries due to its nutritional value and being a priority foodstuff. Feed raw materials are one of the most important input items in the dairy cattle sector. Ensuring the balance of milk/feed parity is of great importance for producers to maintain their activities and profitability. In countries like Turkey, where inflationary effects are observed, the prices of feed raw materials are not stable. In an environment of high price fluctuations, forecasting feed raw material prices for producers is of vital importance for future planning. In this study, price forecasting of 43 feed raw materials, which are used extensively in the ration preparation process in the dairy cattle sector, was carried out. The performances of 11 methods based on Time Series, Statistics and Grey System Theory are compared. After the comparison using model success criteria, it was found that the DGM (1,1) method forecasts more effectively than Exponential Smoothing and Regression models as well as other Grey Forecasting models. Based on MAD, MSE and MAPE values, it is concluded that Grey Forecasting methods can be a good alternative for price forecasting of feed ingredients.

Keywords

Price Forecasting, Exponential Smoothing, Regression Analysis, Grey Forecasting

Ethical Statement

This study is derived from Merve Kılınç Yılmaz's PhD thesis titled " Developing a Decision Support System for the Determination of Minimum Cost Ration Preparation Cost in the Livestock Sector".

Supporting Institution

Burdur Mehmet Akif Ersoy Üniversitesi

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