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

In recent years, physicists have started applying concepts and methods of statistical physics
to study economic problems. The word “Econophysics” is sometimes used to refer to this …

The paper proposes an additive cascade model of volatility components defined over
different time periods. This volatility cascade leads to a simple AR-type model in the realized …

We use methods of random matrix theory to analyze the cross-correlation matrix C of stock
price changes of the largest 1000 US companies for the 2-year period 1994–1995. We find …

We study the distribution of fluctuations of the S&P 500 index over a time scale Δ t by
analyzing three distinct databases. Database (i) contains approximately 1 200 000 records …

We study the statistical properties of volatility, measured by locally averaging over a time
window T, the absolute value of price changes over a short time interval Δ t. We analyze 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 …

We present a phenomenological study of stock price fluctuations of individual companies.
We systematically analyze two different databases covering securities from the three major …

This paper investigates the multifractal model of asset returns (MMAR), a class of continuous-
time processes that incorporate the thick tails and volatility persistence exhibited by many …

In this paper, the multifractality degree in a collection of developed and emerging stock
market indices is evaluated. Empirical results suggest that the multifractality degree can be …