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

The development of high frequency data bases allows for empirical investigations of a wide
range of issues in the financial markets. In this paper, we set out some of the many important …

This article tests for nonlinear dependence and chaos in real-time returns on the world's four
most important stock-market indexes. Both the Brock–Dechert–Scheinkman and the Lee …

Ecologists sometimes have a less-than-rigorous background in quantitative methods, yet
research within this broad field is becoming increasingly mathematical. Written in a step-by …

Calvet and Fisher present a powerful, new technique for volatility forecasting that draws on
insights from the use of multifractals in the natural sciences and mathematics and provides a …

This paper tests for the presence of nonlinear dependence and chaos in real-time returns on
the UK FTSE-100 Index, using a six month sample of about 60,000 observations. Since …

Multifractal processes have recently been proposed as a new formalism for modeling the
time series of returns in finance. The major attraction of these processes is their ability to …

“The economy” easily comes to one's mind when looking for examples of a “complex system
with a large ensemble of interacting units”. The layperson usually feels that terms like “out-of …

For the purposes of this research, the optimal MLP neural network topology has been
designed and tested by means the specific genetic algorithm multi-objective Pareto-Based …

This paper uses daily observations on West Texas Intermediate (WTI) crude oil prices at
Chicago and Henry Hub natural gas prices at LA (over the deregulated period of the 1990s) …