Multiscaling and non-universality in fluctuations of driven complex systems

TL;DR

This paper introduces a formalism to analyze multiscaling in fluctuations of driven complex systems, revealing a transition from internal to external dynamics at different time scales, with evidence of non-universality.

Contribution

It presents a new approach to distinguish internal and external influences in complex systems and demonstrates its application to financial market data.

Findings

Internal processes dominate at minute scales.

External factors influence dynamics at daily scales.

Scaling exponents change systematically across time scales.

Abstract

For many externally driven complex systems neither the noisy driving force, nor the internal dynamics are a priori known. Here we focus on systems for which the time dependent activity of a large number of components can be monitored, allowing us to separate each signal into a component attributed to the external driving force and one to the internal dynamics. We propose a formalism to capture the potential multiscaling in the fluctuations and apply it to the high frequency trading records of the New York Stock Exchange. We find that on the time scale of minutes the dynamics is governed by internal processes, while on a daily or longer scale the external factors dominate. This transition from internal to external dynamics induces systematic changes in the scaling exponents, offering direct evidence of non-universality in the system.