Conditional statistical properties of the complex systems having long-range interactions
Zhifu Huang, Congjie Ou, Bihong Lin, Guozhen Su, Jincan Chen

TL;DR
This paper introduces a new analytical framework using the concept of available force to analyze the conditional statistical properties of complex systems with long-range interactions, demonstrated on currency exchange data.
Contribution
It proposes a novel analytical form for the CPDF based on available force, applicable to various complex systems with long-range interactions or memory.
Findings
The analytical CPDF fits well with currency exchange data.
Conditional expectation of velocity is non-monotonic, variance is monotonic.
The method is general for complex systems with long-range interactions.
Abstract
A new concept of the available force is proposed to investigate the performance of the complex systems having long-range interactions. Since the covariance of average velocity in double time interval and available force equals zero, it is possible to calculate the conditional probability distribution function (CPDF) within the systems. It is found that the asymmetric CPDF of the velocity between two adjacent time intervals can be derived from the symmetrical CPDF between the available force and the double time interval velocity. Two typical currency exchange databases, i.e., EUR/USD and GBP/USD, which collect the minutely opening exchange prices from 1 January 1999 to 31 December 2011, are adopted as examples. It is found that the analytical CPDF needs only six parameters for an arbitrary system. By calculating the CPDF in the currency exchange databases, it is shown that the results…
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