149 research outputs found
Generalized Central Limit Theorem and Renormalization Group
We introduce a simple instance of the renormalization group transformation in
the Banach space of probability densities. By changing the scaling of the
renormalized variables we obtain, as fixed points of the transformation, the
L\'evy strictly stable laws. We also investigate the behavior of the
transformation around these fixed points and the domain of attraction for
different values of the scaling parameter. The physical interest of a
renormalization group approach to the generalized central limit theorem is
discussed.Comment: 16 pages, to appear in J. Stat. Phy
The effective bandwidth problem revisited
The paper studies a single-server queueing system with autonomous service and
priority classes. Arrival and departure processes are governed by marked
point processes. There are buffers corresponding to priority classes,
and upon arrival a unit of the th priority class occupies a place in the
th buffer. Let , denote the quota for the total
th buffer content. The values are assumed to be large, and
queueing systems both with finite and infinite buffers are studied. In the case
of a system with finite buffers, the values characterize buffer
capacities.
The paper discusses a circle of problems related to optimization of
performance measures associated with overflowing the quota of buffer contents
in particular buffers models. Our approach to this problem is new, and the
presentation of our results is simple and clear for real applications.Comment: 29 pages, 11pt, Final version, that will be published as is in
Stochastic Model
Long-Time Fluctuations in a Dynamical Model of Stock Market Indices
Financial time series typically exhibit strong fluctuations that cannot be
described by a Gaussian distribution. In recent empirical studies of stock
market indices it was examined whether the distribution P(r) of returns r(tau)
after some time tau can be described by a (truncated) Levy-stable distribution
L_{alpha}(r) with some index 0 < alpha <= 2. While the Levy distribution cannot
be expressed in a closed form, one can identify its parameters by testing the
dependence of the central peak height on tau as well as the power-law decay of
the tails. In an earlier study [Mantegna and Stanley, Nature 376, 46 (1995)] it
was found that the behavior of the central peak of P(r) for the Standard & Poor
500 index is consistent with the Levy distribution with alpha=1.4. In a more
recent study [Gopikrishnan et al., Phys. Rev. E 60, 5305 (1999)] it was found
that the tails of P(r) exhibit a power-law decay with an exponent alpha ~= 3,
thus deviating from the Levy distribution. In this paper we study the
distribution of returns in a generic model that describes the dynamics of stock
market indices. For the distributions P(r) generated by this model, we observe
that the scaling of the central peak is consistent with a Levy distribution
while the tails exhibit a power-law distribution with an exponent alpha > 2,
namely beyond the range of Levy-stable distributions. Our results are in
agreement with both empirical studies and reconcile the apparent disagreement
between their results
Probability distribution of the sizes of largest erased-loops in loop-erased random walks
We have studied the probability distribution of the perimeter and the area of
the k-th largest erased-loop in loop-erased random walks in two-dimensions for
k = 1 to 3. For a random walk of N steps, for large N, the average value of the
k-th largest perimeter and area scales as N^{5/8} and N respectively. The
behavior of the scaled distribution functions is determined for very large and
very small arguments. We have used exact enumeration for N <= 20 to determine
the probability that no loop of size greater than l (ell) is erased. We show
that correlations between loops have to be taken into account to describe the
average size of the k-th largest erased-loops. We propose a one-dimensional
Levy walk model which takes care of these correlations. The simulations of this
simpler model compare very well with the simulations of the original problem.Comment: 11 pages, 1 table, 10 included figures, revte
Power-law distributions and Levy-stable intermittent fluctuations in stochastic systems of many autocatalytic elements
A generic model of stochastic autocatalytic dynamics with many degrees of
freedom is studied using computer simulations. The time
evolution of the 's combines a random multiplicative dynamics at the individual level with a global coupling through a
constraint which does not allow the 's to fall below a lower cutoff given
by , where is their momentary average and is a
constant. The dynamic variables are found to exhibit a power-law
distribution of the form . The exponent
is quite insensitive to the distribution of the random factor
, but it is non-universal, and increases monotonically as a function
of . The "thermodynamic" limit, N goes to infty and the limit of decoupled
free multiplicative random walks c goes to 0, do not commute:
for any finite while (which is the common range
in empirical systems) for any positive . The time evolution of exhibits intermittent fluctuations parametrized by a (truncated)
L\'evy-stable distribution with the same index . This
non-trivial relation between the distribution of the 's at a given time
and the temporal fluctuations of their average is examined and its relevance to
empirical systems is discussed.Comment: 7 pages, 4 figure
Thermodynamic Limit for the Invariant Measures in Supercritical Zero Range Processes
We prove a strong form of the equivalence of ensembles for the invariant
measures of zero range processes conditioned to a supercritical density of
particles. It is known that in this case there is a single site that
accomodates a macroscopically large number of the particles in the system. We
show that in the thermodynamic limit the rest of the sites have joint
distribution equal to the grand canonical measure at the critical density. This
improves the result of Gro\ss kinsky, Sch\"{u}tz and Spohn, where convergence
is obtained for the finite dimensional marginals. We obtain as corollaries
limit theorems for the order statistics of the components and for the
fluctuations of the bulk
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An extreme value theory approach to calculating minimum capital risk requirements
This paper investigates the frequency of extreme events for three LIFFE futures contracts for
the calculation of minimum capital risk requirements (MCRRs). We propose a semiparametric
approach where the tails are modelled by the Generalized Pareto Distribution and
smaller risks are captured by the empirical distribution function. We compare the capital
requirements form this approach with those calculated from the unconditional density and
from a conditional density - a GARCH(1,1) model. Our primary finding is that both in-sample
and for a hold-out sample, our extreme value approach yields superior results than either of
the other two models which do not explicitly model the tails of the return distribution. Since
the use of these internal models will be permitted under the EC-CAD II, they could be widely
adopted in the near future for determining capital adequacies. Hence, close scrutiny of
competing models is required to avoid a potentially costly misallocation capital resources
while at the same time ensuring the safety of the financial system
Statistics of the gravitational force in various dimensions of space: from Gaussian to Levy laws
We discuss the distribution of the gravitational force created by a
Poissonian distribution of field sources (stars, galaxies,...) in different
dimensions of space d. In d=3, it is given by a Levy law called the Holtsmark
distribution. It presents an algebraic tail for large fluctuations due to the
contribution of the nearest neighbor. In d=2, it is given by a marginal
Gaussian distribution intermediate between Gaussian and Levy laws. In d=1, it
is exactly given by the Bernouilli distribution (for any particle number N)
which becomes Gaussian for N>>1. Therefore, the dimension d=2 is critical
regarding the statistics of the gravitational force. We generalize these
results for inhomogeneous systems with arbitrary power-law density profile and
arbitrary power-law force in a d-dimensional universe
On the continuation of the limit distributions of the extreme and central terms of a sample
Order statistics, extreme value distributions, central value distributions, weak convergence, continuation of the convergence, Primary 62G30, secondary 62E20, 60F05,
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