Previsão do preço e da volatilidade de commodities agrícolas, por meio de modelos ARFIMA-GARCH

• Autor(a) principal: Bayer, Fabio Mariano
• Data de Publicação: 2008
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/0013000009hnn
• Texto Completo: http://repositorio.ufsm.br/handle/1/8078
• topic: Séries temporais; Memória longa; Volatilidade; Preço de commodities; Time series; Long-memory; Volatility; Price of commodities; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO

This research aims to analyze and predict the prices and volatility of the two major agricultural commodities traded on the market of the Rio Grande do Sul state through ARFIMA-GARCH models. Such models are heteroscedasticity conditional to the volatility, with modeling of integration fraction for the mean conditional. The commodities under study are soy and corn, which represent the two main crops standing of the state of Rio Grande do Sul, in terms of quantity produced in the period, which includes January 1995 to May 2007. The models found to the series of price of soy and corn were ARFIMA (1, d, 0)-GARCH (0, 1) and ARFIMA (1, d, 2)-GARCH (0, 2), respectively. These models are capable of modeling the data satisfactorily, allowing an analysis of their behavior and conduct of forecasts in the short term, signaling possible positions of buying and selling in the market future. Given that the decisions in the context of agribusiness, involving the administration of risk in the purchase and sale in the future market, where risks are related to the volatility of prices, a prediction consistent becomes an important tool in decision-making of the participants of this production process.