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- W2337990287 abstract "Last two decades have seen a considerable interest in commodities price behavior as a result of demand pattern changes and the growth of commodities futures markets as a tool to portfolio management in industry. In order to reduce risk and assure prices, agents use different hedging strategies based on futures markets. In this sense forecast models are essential. This paper proposes a mathematical model to agricultural commodity prices forecasting. A hierarchical model is presented. A state space model is considered to identify trends or to describe the structure of the stochastic process. This model is adjusted through a neural network. To analyze the model three commodities were considered: soybeans, alcohol and sugar. The results suggest that this model can be a useful tool to understand markets and to short term forecast." @default.
- W2337990287 created "2016-06-24" @default.
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- W2337990287 date "2010-01-01" @default.
- W2337990287 modified "2023-09-24" @default.
- W2337990287 title "UM MODELO HIERÁRQUICO PARA PREVISÃO DE PREÇOS DE COMMODITIES AGRÍCOLAS A HIERARCHICAL MODEL TO AGRICULTURAL COMMODITIES PRICES FORECAST" @default.
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