617 research outputs found
Persistence in a Random Bond Ising Model of Socio-Econo Dynamics
We study the persistence phenomenon in a socio-econo dynamics model using
computer simulations at a finite temperature on hypercubic lattices in
dimensions up to 5. The model includes a ` social\rq local field which contains
the magnetization at time . The nearest neighbour quenched interactions are
drawn from a binary distribution which is a function of the bond concentration,
. The decay of the persistence probability in the model depends on both the
spatial dimension and . We find no evidence of ` blocking\rq in this model.
We also discuss the implications of our results for possible applications in
the social and economic fields. It is suggested that the absence, or otherwise,
of blocking could be used as a criterion to decide on the validity of a given
model in different scenarios.Comment: 11 pages, 4 figure
A model for correlations in stock markets
We propose a group model for correlations in stock markets. In the group
model the markets are composed of several groups, within which the stock price
fluctuations are correlated. The spectral properties of empirical correlation
matrices reported in [Phys. Rev. Lett. {\bf 83}, 1467 (1999); Phys. Rev. Lett.
{\bf 83}, 1471 (1999.)] are well understood from the model. It provides the
connection between the spectral properties of the empirical correlation matrix
and the structure of correlations in stock markets.Comment: two pages including one EPS file for a figur
Mean Field Voter Model of Election to the House of Representatives in Japan
In this study, we propose a mechanical model of a plurality election based on
a mean field voter model. We assume that there are three candidates in each
electoral district, i.e., one from the ruling party, one from the main
opposition party, and one from other political parties. The voters are
classified as fixed supporters and herding (floating) voters with ratios of
and , respectively. Fixed supporters make decisions based on their
information and herding voters make the same choice as another randomly
selected voter. The equilibrium vote-share probability density of herding
voters follows a Dirichlet distribution. We estimate the composition of fixed
supporters in each electoral district and using data from elections to the
House of Representatives in Japan (43rd to 47th). The spatial inhomogeneity of
fixed supporters explains the long-range spatial and temporal correlations. The
estimated values of are close to the estimates obtained from a survey.Comment: 11 pages, 7 figure
Statistical properties of online auctions
We characterize the statistical properties of a large number of online
auctions run on eBay. Both stationary and dynamic properties, like
distributions of prices, number of bids etc., as well as relations between
these quantities are studied. The analysis of the data reveals surprisingly
simple distributions and relations, typically of power-law form. Based on these
findings we introduce a simple method to identify suspicious auctions that
could be influenced by a form of fraud known as shill bidding. Furthermore the
influence of bidding strategies is discussed. The results indicate that the
observed behavior is related to a mixture of agents using a variety of
strategies.Comment: 9 pages, 4 figures, to be published in Int. J. Mod. Phys.
Evidence of discrete scale invariance in DLA and time-to-failure by canonical averaging
Discrete scale invariance, which corresponds to a partial breaking of the
scaling symmetry, is reflected in the existence of a hierarchy of
characteristic scales l0, c l0, c^2 l0,... where c is a preferred scaling ratio
and l0 a microscopic cut-off. Signatures of discrete scale invariance have
recently been found in a variety of systems ranging from rupture, earthquakes,
Laplacian growth phenomena, ``animals'' in percolation to financial market
crashes. We believe it to be a quite general, albeit subtle phenomenon. Indeed,
the practical problem in uncovering an underlying discrete scale invariance is
that standard ensemble averaging procedures destroy it as if it was pure noise.
This is due to the fact, that while c only depends on the underlying physics,
l0 on the contrary is realisation-dependent. Here, we adapt and implement a
novel so-called ``canonical'' averaging scheme which re-sets the l0 of
different realizations to approximately the same value. The method is based on
the determination of a realization-dependent effective critical point obtained
from, e.g., a maximum susceptibility criterion. We demonstrate the method on
diffusion limited aggregation and a model of rupture.Comment: 14 pages, 6 figures, in press in Int. J. Mod. Phys.
Stochastic Opinion Formation in Scale-Free Networks
The dynamics of opinion formation in large groups of people is a complex
non-linear phenomenon whose investigation is just at the beginning. Both
collective behaviour and personal view play an important role in this
mechanism. In the present work we mimic the dynamics of opinion formation of a
group of agents, represented by two state , as a stochastic response of
each of them to the opinion of his/her neighbours in the social network and to
feedback from the average opinion of the whole. In the light of recent studies,
a scale-free Barab\'asi-Albert network has been selected to simulate the
topology of the interactions. A turbulent-like dynamics, characterized by an
intermittent behaviour, is observed for a certain range of the model
parameters. The problem of uncertainty in decision taking is also addressed
both from a topological point of view, using random and targeted removal of
agents from the network, and by implementing a three state model, where the
third state, zero, is related to the information available to each agent.
Finally, the results of the model are tested against the best known network of
social interactions: the stock market. A time series of daily closures of the
Dow Jones index has been used as an indicator of the possible applicability of
our model in the financial context. Good qualitative agreement is found.Comment: 24 pages and 13 figures, Physical Review E, in pres
Scaling of the distribution of price fluctuations of individual companies
We present a phenomenological study of stock price fluctuations of individual
companies. We systematically analyze two different databases covering
securities from the three major US stock markets: (a) the New York Stock
Exchange, (b) the American Stock Exchange, and (c) the National Association of
Securities Dealers Automated Quotation stock market. Specifically, we consider
(i) the trades and quotes database, for which we analyze 40 million records for
1000 US companies for the 2-year period 1994--95, and (ii) the Center for
Research and Security Prices database, for which we analyze 35 million daily
records for approximately 16,000 companies in the 35-year period 1962--96. We
study the probability distribution of returns over varying time scales , where varies by a factor of ---from 5 min up to
4 years. For time scales from 5~min up to approximately 16~days, we
find that the tails of the distributions can be well described by a power-law
decay, characterized by an exponent ---well outside the
stable L\'evy regime . For time scales days, we observe results consistent with a slow
convergence to Gaussian behavior. We also analyze the role of cross
correlations between the returns of different companies and relate these
correlations to the distribution of returns for market indices.Comment: 10pages 2 column format with 11 eps figures. LaTeX file requiring
epsf, multicol,revtex. Submitted to PR
Data clustering and noise undressing for correlation matrices
We discuss a new approach to data clustering. We find that maximum likelihood
leads naturally to an Hamiltonian of Potts variables which depends on the
correlation matrix and whose low temperature behavior describes the correlation
structure of the data. For random, uncorrelated data sets no correlation
structure emerges. On the other hand for data sets with a built-in cluster
structure, the method is able to detect and recover efficiently that structure.
Finally we apply the method to financial time series, where the low temperature
behavior reveals a non trivial clustering.Comment: 8 pages, 5 figures, completely rewritten and enlarged version of
cond-mat/0003241. Submitted to Phys. Rev.
How to quantify deterministic and random influences on the statistics of the foreign exchange market
It is shown that prize changes of the US dollar - German Mark exchange rates
upon different delay times can be regarded as a stochastic Marcovian process.
Furthermore we show that from the empirical data the Kramers-Moyal coefficients
can be estimated.
Finally, we present an explicite Fokker-Planck equation which models very
precisely the empirical probabilitiy distributions.Comment: 3 figure
Community characterization of heterogeneous complex systems
We introduce an analytical statistical method to characterize the communities
detected in heterogeneous complex systems. By posing a suitable null
hypothesis, our method makes use of the hypergeometric distribution to assess
the probability that a given property is over-expressed in the elements of a
community with respect to all the elements of the investigated set. We apply
our method to two specific complex networks, namely a network of world movies
and a network of physics preprints. The characterization of the elements and of
the communities is done in terms of languages and countries for the movie
network and of journals and subject categories for papers. We find that our
method is able to characterize clearly the identified communities. Moreover our
method works well both for large and for small communities.Comment: 8 pages, 1 figure and 2 table
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