Forecasting onion prices in Pune region of Maharashtra using Dynamic Harmonic Regression

Onion, a staple vegetable, plays a crucial role in both the economy and the livelihoods of people; especially the farmers. Accurate price forecasting is vital for market stakeholders, including consumers, farmers, and policymakers. However, onion prices exhibit fluctuations and multiple seasonal patterns, making prediction challenging. This study delves into a comprehensive analysis of onion prices in the Pune region of Maharashtra using the Dynamic Harmonic Regression (DHR) model, a sophisticated time series technique, adept at capturing multiple seasonalities. The DHR model outperforms traditional forecasting methods, such as Holt-Winters and ARIMA, in predictive accuracy. Furthermore, cointegration analysis examines the relationship between onion prices in the Pune and Vashi markets, providing a deeper understanding of market dynamics. By leveraging historical price data, the study offers valuable insights into future price trends, enabling farmers to make informed decisions and develop strategies to mitigate price fluctuations. To further support farmers, an algorithm is developed to identify the optimal day to sell the produce from the farmer’s perspective. Empowering farmers with this forecasting tool can significantly enhance decision-making with actionable price forecasts.