Application of Permutation Entropy and Statistical Complexity Measure in Crude Oil Price Time Series
نویسندگان
چکیده
The extensive fluctuations in oil prices have vast impacts on economies. The economical instability may be observed for both oil-exporting and oil-importing countries due to high volatility of oil prices. Oil price data as a time series is a highly nonlinear system which exhibits complex patterns. Traditional oil time series analysis employs statistical methods to model and explain the oil data and predict future values of the oil price. The two objectives of this research include (1) discovering the deterministic and random pattern of oil price series by estimating the permutation entropy and forbidden patterns of Brent crude oil markets during the last decades (1990.08.02–2012.08.21), (2) monitoring crude oil market efficiency by computing SCM for finding an associated ranking of relative efficiency of oil spot series from 1990 to 2012. This ranking is quantifying the presence of hidden market efficiency behavior in the oil market. Permutation entropy, forbidden patterns and statistical complexity measure are calculated to quantify the degree of uncertainty and efficient behavior of Brent crude-oil markets for judging whether the oil price series is highly or lowly predictable. Research results show that volatility in the Brent oil price series have certain seasonal behavior and market efficient of Brent oil market is getting apparent after 2010. This phenomenon reveals the oil market is getting unpredictable from 2010.
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