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Crude oil market and geopolitical events: an analysis based on information-theory-based quantifiers

Aurelio F. Bariviera. Department of Business Management, Universitat Rovira i Virgili, Spain.

Luciano Zunino. Centro de Investigaciones Ópticas (CONICET La Plata-CIC), Argentina | Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de la Plata, Argentina.

Osvaldo A. Rosso. Instituto de Física, Universidad Federal de Alagoas, Brazil | Instituto Tecnológico de Buenos Aires (ITBA), Argentina | Complex Systems Group, Universidad de los Andes, Chile.


This paper analyzes the informational efficiency of oil market during the last three decades, and examines changes in informational efficiency with major geopolitical events, such as terrorist attacks, financial crisis and other important events. The series under study is the daily prices of West Texas Intermediate (WTI) in USD/BBL, commonly used as a benchmark in oil pricing. The analysis is performed using information-theory-derived quantifiers, namely permutation entropy and permutation statistical complexity. These metrics allow capturing the hidden structure in the market dynamics, and allow discriminating different degrees of informational efficiency. We find that some geopolitical events impact on the underlying dynamical structure of the market.


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