Forecasting Rice Prices with Holt-Winter Exponential Smoothing Model

Abstract

Rice, as a staple food, plays a crucial role in global food security. Accurate forecasting of rice prices is essential for policymakers, farmers, and consumers alike. This article explores the application of the Holt-Winter exponential smoothing model to predict rice prices. Holt-Winter method is chosen for its ability to capture both trend and seasonality in time series data, which are prominent features in agricultural commodity prices such as rice. The study analyzes historical price data, identifies trends, seasonality, and incorporates smoothing parameters in additive and multiplicative methods. Results indicate that additive method of Holt-Winter exponential smoothing provides a better performance. This research contributes valuable insights to the field of agricultural economics and informs strategies for managing food supply chains and market stability.