Generic Multifractality in Exponentials of Long Memory Processes
Abstract
We find that multifractal scaling is a robust property of a large class of continuous stochastic processes, constructed as exponentials of long-memory processes. The long memory is characterized by a power law kernel with tail exponent , where . This generalizes previous studies performed only with (with a truncation at an integral scale), by showing that multifractality holds over a remarkably large range of dimensionless scales for . The intermittency multifractal coefficient can be tuned continuously as a function of the deviation from 1/2 and of another parameter embodying information on the short-range amplitude of the memory kernel, the ultra-violet cut-off (``viscous'') scale and the variance of the white-noise innovations. In these processes, both a viscous scale and an integral scale naturally appear, bracketing the ``inertial'' scaling regime. We exhibit a surprisingly good collapse of the multifractal spectra on a universal scaling function, which enables us to derive high-order multifractal exponents from the small-order values and also obtain a given multifractal spectrum by different combinations of and .
Cite
@article{arxiv.cond-mat/0602660,
title = {Generic Multifractality in Exponentials of Long Memory Processes},
author = {A. Saichev and D. Sornette},
journal= {arXiv preprint arXiv:cond-mat/0602660},
year = {2009}
}
Comments
10 pages + 9 figures