Multiscale entropy analysis of crude oil price dynamics
Price formation in crude oil markets is the result of the action of many participants (e.g., producers, governments, speculators, etc.) whose effects are perceived at different time scales, from days to years. The diversity of participants as well as the occurrence of extreme socio-political events yields a market with complex price evolution. This paper uses entropy methods to monitor the evolution of crude oil price movements. As the complexity of the price can depend of the time horizon, entropy computations are performed for different time scales via low-pass filtering of the price difference dynamics. The results are interpreted in term of relative market efficiency concepts in the sense that high entropy values should be related to a more complex and, hence, less predictable market evolution. It is shown that the highest market efficiency is found for small time scales up to one or two weeks. The multiscale entropy pattern for high time scales, longer than one quarter, is interesting as it shows alternating periods of high and low entropy levels. Interestingly, this alternating pattern has a dominant spectral component of about 4.3Â years, which could be related to macroeconomic (Kitchin) business cycles. It is shown that U.S. recessions in the recent 25Â years are coincident with periods of reduced entropy levels, meaning that during economic downturn the long-run market complexity is drastically reduced. The possible effects of extreme events (e.g., Iraq War) are analyzed in terms of the relative market efficiency, suggesting that some events have affected the short-term but not the long-term market complexity. Overall, these results show that methods based on entropy concepts can shed light on the structure of crude oil markets as well as on its link to macroeconomic conditions and socio-political extreme events.
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