Derivativos climáticos no Brasil: análise da efetividade da estratégia de hedge nas culturas de soja, milho e café.

Abstract

The objective of the present study was to analyze whether weather derivatives can be applied in different Brazilian regions, considering hedge effectiveness and demonstrate the most appropriate model for pricing when preparing weather derivative contracts in Brazil. To this end, descriptive research was carried out, with a quantitative approach. The research sample comprised the four largest coffee, corn and soy producing cities in Brazil, between the period 2000 and 2021. Regression and the ARIMA model were used to estimate production in the years 2022 and 2023 and in the estimation, all cities and cultures were significant at 95%. As for temperature data, accommodation reduced the temperature variance, resulting in a more homogeneous distribution. The Durbin Watson test demonstrated the absence of autocorrelation. After estimating the production, the pricing of the weather derivative was carried out, first the pricing was carried out using the Monte Carlo simulation, when carrying out the pricing using the method, it was possible to notice that for all the cities analyzed, relevant values were obtained only for the Call (purchase) based on Cooling Degree Days (CDD). The second method used for pricing was Burn Analysis, the results show an average Call value for all seasons and crops. However, in the city of Brejetuba in the state of Espírito Santo, it was possible to notice a Call price (10.83) for the CDD that was higher than the others. This means that the producer has a greater need for cooling grades in coffee production. Regarding pricing based on Price Equilibrium, it was possible to demonstrate that the higher the producer's level of risk aversion, the lower the value of the derivative. Finally, when analyzing the effectiveness through the Value at risk, Certainty equivalent revenues and Mean root square loss methods, all tests showed the effectiveness of protection in weather derivative contracts in soybean, corn and coffee crops in all cities and regions studied.