Abstract
AbstractWe consider the α re-scaled energy source (ES) daily positive returns r(t)α and negative returns (−r(t))α that we call, after normalization, the α positive fluctuations and α negative fluctuations, respectively. We use the Kolmogorov-Smirnov statistical test as a method to find the values of α that optimize the data collapse of the histogram of the α fluctuations with the truncated Bramwell-Holdsworth-Pinton (BHP) probability density function. Using the optimal α′s we compute analytical approximations of the probability distributions of the normalized positive and negative energy source (ES) daily returns r(t). Since the BHP probability density function appears in several other dissimilar phenomena, our results reveal a universal feature of energy source prices and a new measure that allows the comparison between the intensity of gains and losses of market activity in different energy sources prices.KeywordsEnergy SourceProbability Density FunctionDaily ReturnPositive ReturnNegative ReturnThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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