Hierarchical fuzzy model applied to oil trading/Modelo difuso jerarquico aplicado al comercio de petroleo/Modelo difuso hierarquico aplicado a negociacao de petroleo

Computer trading is currently relatively limited to quantitative trading in paper markets, such as, futures, swaps, and options, ignoring the large volume of physical commodities trading. Numerical algorithms and mathematical methods are frequently applied in the trading of non- physical commodities...

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Bibliographic Details
Published in:GeSec : Revista de Gestão e Secretariado 2024-04, Vol.15 (4)
Main Authors: Andrade, Gustavo Bastos de, Cosenza, Carlos Alberto Nunes, Andrade, Luciana Bastos de, Oliveira, Antonio Carlos de Lemos, Perez, Edison dos Santos Conde, Grecco, Claudio Henrique dos Santos, Krykhtine, Fabio Luiz
Format: Article
Language:Portuguese
Subjects:
Algorithms
Artificial intelligence
Commodity markets
Computer hardware industry
Computer industry
Decision-making
International economic relations
Options (Finance)
Rankings
Stock markets
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Summary:Computer trading is currently relatively limited to quantitative trading in paper markets, such as, futures, swaps, and options, ignoring the large volume of physical commodities trading. Numerical algorithms and mathematical methods are frequently applied in the trading of non- physical commodities and stock markets. However, the physical trade of oil does not have a computer program that represents an unquestionable development that includes more complex and subjective factors that traders take into consideration when entering a transaction. Using fuzzy logic, this work proposes a new approach to base a method that can rank oils and the variables, commonly involved in the trading. It uses fuzzy logic to blend objective and subjective factors and brings in two key hierarchical steps to the process. It is shown that this model can also be useful for apprising a decision-making process, improving internal communication, and for the management of physical commodities trading. Here the options of trading are assessed accordingly to its numerical and linguistic judgments, considering even abrupt outcomes. The wide-ranging options, successive filters, and factors evaluation that mirror the technical and expert trading decision making process make it possible for the future application of artificial intelligence (AI) in physical commodities trading.
ISSN:2178-9010
2178-9010
DOI:10.7769/gesec.v15i4.3747