HEDGING CROP YIELDS USING TEMPERATURE DERIVATIVES

Abstract

Agriculture production yield varies with weather changes. This causes farmers to incur losses. For instance, extreme temperature leads to low maize yield. This study describes incomplete temperature weather derivatives in agriculture markets and applies risk management hedging techniques. It focuses on hedging crop yield against extreme temperatures during irrigation farming, which is done without a greenhouse. This study primarily aims to hedge maize crop yields using temperature derivatives. This is achieved by (i) developing a daily average temperature stochastical model. (ii) Deriving statistical properties of the model based on the historical data of 31 years of our sample space (1990 – 2020 Kasungu District Temperature data). (iii) Pricing temperature derivatives to hedge maize crop yield. To achieve this, a stochastically Ornstein Uhlenbeck process with the time-varying speed of reversion, seasonal mean, and local volatility that depends on the local average temperature was proposed. Based on the average temperature model, down and output, option pricing models for average temperature and growing degree day are presented. The study's findings suggest that the temperature will rise gradually but steadily. This scenario does not offer a positive outlook for agriculture production since a temperature rise can damage it. The premium for weather derivative options has been calculated as $3.50 per GDD index contract.Farmers and agricultural stakeholders can hedge their crops against extreme temperature-related weather risks with these models. In line with Malawi's 2063 Millennium Development Goals (MDGs), this study acts as an eye opener for the government to put a policy on whether derivatives should be practised in our country hence, increase cash holding by improving the situation of the farmer and country.