Considering that both the entropy-based market information and the Hurst exponent are
useful tools for determining whether the efficient market hypothesis holds for a given asset …

We determine the amount of information contained in a time series of price returns at a given
time scale, by using a widespread tool of the information theory, namely the Shannon …

University campuses, Supercomputer centers and R&E networks are challenged to architect,
build and support IT infrastructure to deal effectively with the data deluge facing most …

Behavioral studies have shown that human cognition is characterized by properties such as
temporal scale invariance, heavy-tailed non-Gaussian distributions, and long-range …

Scale-invariant processes, and hereafter processes with broken versions of this symmetry,
are studied by means of the Lamperti transformation, a one-to-one transformation linking …

The inverse Lamperti transform of a fractional Brownian motion (fBm) is a stationary process.
We determine the empirical Hurst exponent of such a composite process with the help of a …

The multifractional model with random exponent (MPRE) is one of the most recent fractional
models which extend the fractional Brownian motion (fBm). This paper is an empirical …

Abstract The well-known Ornstein–Uhlenbeck process (OUP) is the central go-to Gaussian
model for statistical-equilibrium processes. The recently-introduced power Brownian motion …

Diffusion in a logarithmic potential (DLP) attracted significant interest in physics recently. The
dynamics of DLP are governed by a Langevin stochastic differential equation (SDE) whose …

We are interested in the nonparametric estimation of the probability density of price returns,
using the kernel approach. The output of the method heavily relies on the selection of a …