Agricultural commodities; Time series; Network Transfer Entropy.
Agricultural commodities are primary products grown on a large scale, which play a
crucial role in the global economy. Its importance is evidenced by its contribution to
food security, international trade and the livelihoods of millions of people around the
world, in addition to directly influencing food prices and the economic stability of many
countries. The study was carried out with the purpose of analyzing the temporal variation
and comparing the price dynamics of 3 groups of Brazilian agricultural commodities:
grains, meat and soft, and to which commodity the price variation is directly related, thus
contributing to the advancement and confirmation of theoretical and computational models
aimed at predicting prices in this sector. For this purpose, the Network Transfer Entropy
methodology was used. Daily price series were proven as well as the series of returns
recorded in the period from January 2010 to August 2022, the data were obtained by the
Centro de Estudos Avançados em Economia Aplicada/ Escola Superior de Agricultura
Luiz de Queiroz/ Universidade de São Paulo - CEPEA / ESALQ / USP. The historical
series of commodity prices were verified, then the return series was calculated, to finally
apply the TE methodology. For each pair of commodities, TE was calculated in both
losses, generating network transfer entropy (Net Transfer Entropy). Data analysis was
carried out using the R Core Team software (2020)