Short-Term Compumetric Forecast of Crude Oil Prices

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Kaboudan2003365,

• author = "M. A. Kaboudan",
• title = "Short-Term Compumetric Forecast of Crude Oil Prices",
• editor = "R. Neck",
• booktitle = "Modeling and Control of Economic Systems 2001 -- A Proceedings volume from the 10th IFAC Symposium",
• publisher = "Elsevier Science Ltd",
• year = "2003",
• pages = "365--370",
• address = "Klagenfurt, Austria",
• publisher_address = "Oxford",
• month = "6-8 " # sep,
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-08-043858-0",
• DOI = "doi:10.1016/B978-008043858-0/50062-0",
• URL = "http://www.sciencedirect.com/science/article/B86BF-4PF22NC-17/2/96bb656b1958ddb535464abece56273c",
• abstract = "Forecasting oil prices remains an important empirical issue. This paper compares three forecasts of short-term oil prices using two compumetric methods and naive random walk. Compumetric methods use model specifications generated by computers with limited human intervention. Users are responsible only for selecting the appropriate set of explanatory variables. The compumetric methods employed here are genetic programming and artificial neural networks. The variable to forecast is monthly US imports FOB oil prices. Each method is used to forecast one and three months ahead. The results suggest that neural networks deliver better predictions.",

}

Genetic Programming entries for Mahmoud A Kaboudan

Citations