Favorit: farmers volatility risk treatment

TL;DR

This paper proposes an analytics-based strategy for Indian farmers to select optimal market timing for selling produce, aiming to mitigate the adverse effects of price fluctuations using historical price data.

Contribution

It introduces a data-driven approach for farmers to determine the best sale timing based on historical market prices and variability, applied to specific crops in Maharashtra.

Findings

Effective timing strategy for tomato, onion, and coriander markets.

Potential for crop-wise and market-wise adaptation across India.

Framework encourages local research and data analysis for farmers.

Abstract

This paper seeks to develop a strategy based on analytics, for an individual Indian farmer to tackle market price fluctuations. The idea is to select a month (or a week or a day) on which to take the produce to market for a good return on the sale. The choice is based on the history of price data and associated variability. Market-wise price data for the last decade or so are used. These ideas are applied to three vegetable crops, tomato, onion, and coriander for some markets in the state of Maharashtra. It is proposed that similar work should be done crop-wise and market-wise for different parts of India by local academic groups from any of the subjects such as statistics, analytics, data science, agriculture, business management, commerce, and economics. The objective is to mitigate the adverse impact of price fluctuation on farmers.