Disentangling sources of multifractality in time series

TL;DR

This paper investigates the sources of multifractality in time series, emphasizing the roles of temporal correlations and heavy-tailed distributions, and proposes methods to disentangle their individual contributions.

Contribution

It introduces a procedure to quantify the influence of heavy tails on multifractality while accounting for temporal correlations, using $q$-Gaussian adjustments and multifractal analysis.

Findings

Gaussian distribution ($q=1$) serves as a baseline for multifractality.

Heavy tails increase the width of multifractal spectra when correlations are present.

The proposed method effectively separates the effects of distribution tails from correlations.

Abstract

This contribution addresses the question commonly asked in scientific literature about the sources of multifractality in time series. Two primary sources are typically considered. These are temporal correlations and heavy tails in the distribution of fluctuations. Most often, they are treated as two independent components, while true multifractality cannot occur without temporal correlations. The distributions of fluctuations affect the span of the multifractal spectrum only when correlations are present. These issues are illustrated here using series generated by several model mathematical cascades, which by design build correlations into these series. The thickness of the tails of fluctuations in such series is then governed by an appropriate procedure of adjusting them to $q$-Gaussian distributions, and $q$ is treated as a variable parameter that, while preserving correlations, allows to tune these distributions to the desired functional form. Multifractal detrended fluctuation analysis (MFDFA), as the most commonly used practical method for quantifying multifractality, is then used to identify the influence of the thickness of the fluctuation tails in the presence of temporal correlations on the width of multifractal spectra. The obtained results point to the Gaussian distribution, so $q=1$, as the appropriate reference distribution to evaluate the contribution of fatter tails to the width of multifractal spectra. An appropriate procedure is presented to make such estimates.