26 research outputs found
Modelling fluctuations of financial time series: from cascade process to stochastic volatility model
In this paper, we provide a simple, ``generic'' interpretation of
multifractal scaling laws and multiplicative cascade process paradigms in terms
of volatility correlations. We show that in this context 1/f power spectra, as
observed recently by Bonanno et al., naturally emerge. We then propose a simple
solvable ``stochastic volatility'' model for return fluctuations. This model is
able to reproduce most of recent empirical findings concerning financial time
series: no correlation between price variations, long-range volatility
correlations and multifractal statistics. Moreover, its extension to a
multivariate context, in order to model portfolio behavior, is very natural.
Comparisons to real data and other models proposed elsewhere are provided.Comment: 21 pages, 5 figure
A multivariate multifractal model for return fluctuations
In this paper we briefly review the recently inrtroduced Multifractal Random
Walk (MRW) that is able to reproduce most of recent empirical findings
concerning financial time-series : no correlation between price variations,
long-range volatility correlations and multifractal statistics. We then focus
on its extension to a multivariate context in order to model portfolio
behavior. Empirical estimations on real data suggest that this approach can be
pertinent to account for the nature of both linear and non-linear correlation
between stock returns at all time scales.Comment: To be published in the Proceeding of the APFA2 conference (Liege,
Belgium, July 2000) in the journal Quantitative Financ
Velocity statistics in excited granular media
We present an experimental study of velocity statistics for a partial layer
of inelastic colliding beads driven by a vertically oscillating boundary. Over
a wide range of parameters (accelerations 3-8 times the gravitational
acceleration), the probability distribution P(v) deviates measurably from a
Gaussian for the two horizontal velocity components. It can be described by
P(v) ~ exp(-|v/v_c|^1.5), in agreement with a recent theory. The characteristic
velocity v_c is proportional to the peak velocity of the boundary. The granular
temperature, defined as the mean square particle velocity, varies with particle
density and exhibits a maximum at intermediate densities. On the other hand,
for free cooling in the absence of excitation, we find an exponential velocity
distribution. Finally, we examine the sharing of energy between particles of
different mass. The more massive particles are found to have greater kinetic
energy.Comment: 27 pages, 13 figures, to appear in Chaos, September 99, revised 3
figures and tex
Long time correlations in Lagrangian dynamics: a key to intermittency in turbulence
New aspects of turbulence are uncovered if one considers flow motion from the
perspective of a fluid particle (known as the Lagrangian approach) rather than
in terms of a velocity field (the Eulerian viewpoint). Using a new experimental
technique, based on the scattering of ultrasounds, we have obtained a direct
measurement of particle velocities, resolved at all scales, in a fully
turbulent flow. It enables us to approach intermittency in turbulence from a
dynamical point of view and to analyze the Lagrangian velocity fluctuations in
the framework of random walks. We find experimentally that the elementary steps
in the 'walk' have random uncorrelated directions but a magnitude that is
extremely long-range correlated in time. Theoretically, we study a Langevin
equation that incorporates these features and we show that the resulting
dynamics accounts for the observed one- and two-point statistical properties of
the Lagrangian velocity fluctuations. Our approach connects the intermittent
statistical nature of turbulence to the dynamics of the flow.Comment: 4 pages, 4 figure
A multifractal random walk
We introduce a class of multifractal processes, referred to as Multifractal
Random Walks (MRWs). To our knowledge, it is the first multifractal processes
with continuous dilation invariance properties and stationary increments. MRWs
are very attractive alternative processes to classical cascade-like
multifractal models since they do not involve any particular scale ratio. The
MRWs are indexed by few parameters that are shown to control in a very direct
way the multifractal spectrum and the correlation structure of the increments.
We briefly explain how, in the same way, one can build stationary multifractal
processes or positive random measures.Comment: 5 pages, 4 figures, uses RevTe
Analysis of random cascades using the wavelet transform: from theoretical concepts to experimental applications
no abstrac