Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …

This review addresses a central question in the field of complex systems: given a fluctuating
(in time or space), sequentially measured set of experimental data, how should one analyze …

In this study, we attempt to revisit how dependent the US stock market returns are on climate
change related risks (CCRR). In this regard, we use a spillover and connectedness network …

As a form of cryptocurrency, the issue of informational efficiency of Bitcoin has received
much attention recently. We add to the literature by investigating nine forms of …

This paper analyzes the connectedness between forex and cryptocurrencies using the
quantile cross-spectral approach. The sample covers six forex and six cryptocurrencies over …

The multifractal nature of agriculture-related stocks and derivatives has been extensively
studied. However, due to the scarcity and lack of representativeness of available data, the …

The detrending moving average (DMA) algorithm is a widely used technique to quantify the
long-term correlations of nonstationary time series and the long-range correlations of fractal …

There are a number of situations in which several signals are simultaneously recorded in
complex systems, which exhibit long-term power-law cross correlations. The multifractal …

Data series generated by complex systems exhibit fluctuations on many time scales and/or
broad distributions of the values. In both equilibrium and non-equilibrium situations, the …

The most suitable paradigms and tools for investigating the scaling structure of financial time
series are reviewed and discussed in the light of some recent empirical results. Different …