Aplicação de metodologias para análise e previsão do preço do fruto de açaí

• Ano de defesa: 2011
• Autor(a) principal: Eder, Karina
• Orientador(a): Pessoa, José Dalton Cruz
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Biotecnologia - PPGBiotec
• País: BR
• Palavras-chave em Português: Estatística; Análise de séries temporais; Previsão; Análise técnica; Açaí - preços
• Palavras-chave em Inglês: Time Series; Forecast; Technical Analysis; Açaí Price
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/6991

Açaí is the fruit of a palm tree found throughout the North of Brazil that has been gaining attention due to its high energetic potential, applications in pharmaceuticals, dentistry, medicine and food industries. So, consumers from all over Brazil and also from other countries are looking for the product, encouraging the extraction and the increase in planted area causing inflating the price. Being a market with strong growth can be invaluable for the agribusiness, producers and middlemen predict the price of fruit. Given this context, the objective of this study is to analyze and predict the price of açaí fruit sold at the Açaí Fair in Belém (Pará), through the following methodologies: time series, specifically ARIMA and SARIMA models and technical analysis using tracking trends and chart Candlestick. The series analysis showed that there is a growing trend of prices and annual seasonality. The results showed about forecast presented Root Mean Squared Error and Mean Absolute Percentage Error low. As for price trends, can be observed that the use of moving averages and MACD with the suggested parameters were the methods that best indicated the beginning of the season and offseason and were able to track the price change, being considered for use as an effective tool of aid in decision making. But the use of exponential moving averages and the intersection of three moving averages, and/or the method of Didi Index, showed that the tool can track the price change, but does not anticipate the entry of season or offseason, being ineffective for use in decision making. So, we conclude that the use of only method to predict the price can be ineffective to assist in decision making, and therefore requires the use a set of methods.