Much of the soybean produced in Brazil is exported and, consequently, the domestic soybean price (R$) is greatly influenced by the price traded at the Chicago Mercantile Exchange Group (CME Group) (US$). Therefore, to model the dependency structure between soybean yield and price, the exchange rate must be incorporated into the modeling. This study aims to model the dependency structure between these three variables using the Copula methodology, calculate the crop revenue insurance rates, and compare with the rates offered in the insurance market. The rates applied by the Brazilian insurance market are overpriced when compared to the methodology presented in this study with the incorporation of the dollar rate in the modeling, which could increase the problem of adverse selection exchange and hamper massification of agricultural insurance in the Brazilian territory.

Resumo Nos últimos anos, o seguro de faturamento agrícola tem sido amplamente discutido. Este tipo de seguro tornou-se um mecanismo importante para o gerenciamento dos riscos climáticos (afetam a produtividade) e de mercado (preços das culturas). No entanto, um estudo mais abrangente é necessário para investigar a estrutura de dependência entre as variáveis analisadas e para calcular a taxa do prêmio atuarialmente justa para o seguro de faturamento. Este estudo propõe formas alternativas para calcular as taxas do prêmio do seguro de faturamento utilizando as funções cópulas paramétricas. Os resultados sugerem que as taxas comerciais médias calculadas pela seguradora estão subestimadas quando comparadas com o modelo de cópulas. A subestimação das taxas podem levar a graves perdas às seguradoras, uma vez que considera um risco menor do que deveria ser levado em consideração.

Abstract Crop revenue insurance has been widely discussed recently. It has become an important mechanism for risk; management of crop yielO anp prices. However, a more comprehensive study is needed to investigate the dependence stmcture between thu variables analyzed ro celculate the premium rate actearially fair for revenue insurance. Tleis study proposes alternatives ao calculate premium rates for revenue insurance using parametric copula functions. The results nuuunsts that the average commnndal rates calculated by the insurer aru undnrestimftnd when compared to tce copula model. The underesSimation om rates can lead to seriou losses to insurers, sinca segy consiher a lower risk than should be tamen into account.