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1.
J. de Souza L. G. Moyano S. M. Duarte Queirós 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):165-168
In this article we study the dependence degree of the traded volume of
the Dow Jones 30 constituent equities
by using a nonextensive generalised form of the Kullback-Leibler
information measure. Our results
show a slow decay of the dependence degree as a function of the lag.
This feature is compatible with the existence
of non-linearities in this type time series. In addition, we introduce a
dynamical mechanism whose associated
stationary probability density function (PDF) presents a good agreement
with the empirical results. 相似文献
2.
Self-organizing Ising model of financial markets 总被引:1,自引:0,他引:1
W.-X. Zhou D. Sornette 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,55(2):175-181
We study a dynamical Ising-like model of agents' opinions (buy or
sell) with learning, in which the coupling coefficients are
re-assessed continuously in time according to how past external news
(time-varying magnetic field) have explained realized market
returns. By combining herding, the impact of external news and
private information, we find that the stylized facts of financial
markets are reproduced only when agents misattribute the success of
news to predict return to herding effects, thereby providing
positive feedbacks leading to the model functioning close to the
Ising critical point. 相似文献
3.
I. Simonsen P. T.H. Ahlgren M. H. Jensen R. Donangelo K. Sneppen 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,57(2):153-158
The value of stocks, indices and other assets, are examples of stochastic processes with unpredictable dynamics. In this paper,
we
discuss asymmetries in short term price movements that can not be
associated with a long term positive trend. These empirical
asymmetries predict that stock index drops are more common on a
relatively short time scale than the corresponding raises. We
present several empirical examples of such asymmetries. Furthermore,
a simple model featuring occasional short periods of synchronized
dropping prices for all stocks constituting the index is introduced
with the aim of explaining these facts. The collective negative
price movements are imagined triggered by external factors in our
society, as well as internal to the economy, that create fear of the
future among investors. This is parameterized by a “fear factor”
defining the frequency of synchronized events. It is demonstrated
that such a simple fear factor model can reproduce several empirical
facts concerning index asymmetries. It is also pointed out that in
its simplest form, the model has certain shortcomings. 相似文献
4.
N. Sazuka 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):129-131
A non-trivial probability structure is evident in the binary data extracted from the up/down price movements of very high
frequency data such as tick-by-tick data for USD/JPY. In this paper, we analyze the Sony bank USD/JPY rates, ignoring the
small deviations from the market price. We then show there is a similar non-trivial probability structure in the Sony bank
rate, in spite of the Sony bank rate's having less frequent and larger deviations than tick-by-tick data. However, this probability
structure is not found in the data which has been sampled from tick-by-tick data at the same rate as the Sony bank rate. Therefore,
the method of generating the Sony bank rate from the market rate has the potential for practical use since the method retains
the probability structure as the sampling frequency decreases. 相似文献
5.
A. P. Nawroth J. Peinke 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):147-151
A new approach is presented to describe the change in the statistics of the log return distribution of financial data as a
function of the timescale. To this purpose a measure is introduced, which quantifies the distance of a considered distribution
to a reference distribution. The existence of a small timescale regime is demonstrated, which exhibits different properties
compared to the normal timescale regime for timescales larger than one minute. This regime seems to be universal for individual
stocks. It is shown that the existence of this small timescale regime is not dependent on the special choice of the distance
measure or the reference distribution. These findings have important implications for risk analysis, in particular for the
probability of extreme events. 相似文献
6.
M. Bartolozzi 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,57(3):337-345
Avalanches, or Avalanche-like, events are often
observed in the dynamical behaviour of many complex systems which
span from solar flaring to the Earth's crust dynamics and from
traffic flows to financial markets. Self-organized criticality
(SOC) is one of the most popular theories able to explain this
intermittent charge/discharge behaviour. Despite a large amount of
theoretical work, empirical tests for SOC are still in their
infancy. In the present paper we address the common problem of
revealing SOC from a simple time series without having much
information about the underlying system. As a working example we
use a modified version of the multifractal random walk originally
proposed as a model for the stock market dynamics. The study
reveals, despite the lack of the typical ingredients of SOC, an
avalanche-like dynamics similar to that of many physical systems.
While, on one hand, the results confirm the relevance of cascade
models in representing turbulent-like phenomena, on the other,
they also raise the question about the current state of
reliability of SOC inference from time series analysis. 相似文献
7.
V. Alfi M. Cristelli L. Pietronero A. Zaccaria 《The European Physical Journal B - Condensed Matter and Complex Systems》2009,67(3):385-397
We introduce a minimal agent based model for financial markets to understand the nature and self-organization of the stylized
facts. The model is minimal in the sense that we try to identify the essential ingredients to reproduce the most important
deviations of price time series from a random walk behavior. We focus on four essential ingredients: fundamentalist agents
which tend to stabilize the market; chartist agents which induce destabilization; analysis of price behavior for the two strategies;
herding behavior which governs the possibility of changing strategy. Bubbles and crashes correspond to situations dominated
by chartists, while fundamentalists provide a long time stability (on average). The stylized facts are shown to correspond
to an intermittent behavior which occurs only for a finite value of the number of agents N. Therefore they correspond to finite
size effects which, however, can occur at different time scales. We propose a new mechanism for the self-organization of this
state which is linked to the existence of a threshold for the agents to be active or not active. The feedback between price
fluctuations and number of active agents represents a crucial element for this state of self-organized intermittency. The
model can be easily generalized to consider more realistic variants. 相似文献
8.
F. F. Gong F. X. Gong F. Y. Gong 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,49(3):267-268
Open dynamic behaviour of financial markets with internal
interactions between agents and with external “fields” from other systems
are investigated using the approach of Grossman and Stiglitz for inefficient
markets, and Keynes for interference of the market using physics of finance
(referred to hereafter as phynance). The simulation results indicate that
the NYSE data analyzed in Plerou, V. et al., Nature 421, 130 (2003) can be fitted
by an equation of order parameter Φ and local deviation R of type:
-(R+0.03) Φ+ 0.6 Φ3 + 0.02 = 0, which is shown to be in
remarkable agreement with Plerou's data. 相似文献
9.
M. Bartolozzi C. Mellen T. Di Matteo T. Aste 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,58(2):207-220
In the present work we investigate the multiscale nature of the
correlations for high frequency data (1 min) in different
futures markets over a period of two years, starting on the
1st of January 2003 and ending on the 31st of
December 2004. In particular, by using the concept of local
Hurst exponent, we point out how the behaviour of this parameter,
usually considered as a benchmark for persistency/antipersistency
recognition in time series, is largely time-scale dependent in the
market context. These findings are a direct consequence of the
intrinsic complexity of a system where trading strategies are
scale-adaptive. Moreover, our analysis points out different
regimes in the dynamical behaviour of the market indices under
consideration. 相似文献
10.
We present a review of our recent research in econophysics, and focus on the comparative study of Chinese and western financial markets. By virtue of concepts and methods in statistical physics, we investigate the time correlations and spatial structure of financial markets based on empirical high-frequency data. We discover that the Chinese stock market shares common basic properties with the western stock markets, such as the fat-tail probability distribution of price returns, the long-range auto-correlation of volatilities, and the persistence probability of volatilities, while it exhibits very different higher-order time correlations of price returns and volatilities, spatial correlations of individual stock prices, and large-fluctuation dynamic behaviors. Furthermore, multi-agent-based models are developed to simulate the microscopic interaction and dynamic evolution of the stock markets. 相似文献
11.
This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear
dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency
trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional
in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge
symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold
fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried
out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching
the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade
to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons
discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely
indicates a new science paradigm in the economy and society domains beyond physics.
相似文献
12.
L. Gazola C. Fernandes A. Pizzinga R. Riera 《The European Physical Journal B - Condensed Matter and Complex Systems》2008,61(3):355-362
This paper intends to meet recent claims for the attainment of more rigorous
statistical methodology within the econophysics literature. To this end, we
consider an econometric approach to investigate the outcomes of the
log-periodic model of price movements, which has been largely used to
forecast financial crashes. In order to accomplish reliable statistical
inference for unknown parameters, we incorporate an autoregressive dynamic
and a conditional heteroskedasticity structure in the error term of the
original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the
original and the extended models are fitted to financial indices of U. S.
market, namely S&P500 and NASDAQ. Our analysis reveal two main points:
(i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better
statistical properties and (ii) the estimation of the parameter concerning
the time of the financial crash has been improved. 相似文献
13.
14.
Hui Peng Tohru Ozaki Valerie Haggan-Ozaki 《The European Physical Journal B - Condensed Matter and Complex Systems》2003,31(2):285-293
On the basis of the market microstructure theory and the continuous time stochastic volatility-style microstructure model,
a discrete time stochastic volatility microstructure model with state-observability is proposed for describing the dynamics
of financial markets. From the discrete time microstructure model proposed, estimates of two immeasurable state variables
representing the market excess demand and liquidity respectively may be obtained. A simple trading strategy for dynamic asset
allocation, based on the indirectly obtained excess demand information instead of the prediction for price, is presented.
An approach to the estimation of the discrete time microstructure model using the extended Kalman filter and the maximum likelihood
method is also presented. Case studies on financial market modeling and the estimated model-based asset dynamic allocation
control for the JPY/USD (Japanese Yen/US Dollar) exchange rate and Japan TOPIX (TOkyo stock Price IndeX) show satisfactory
modeling precision and control performance.
Received 11 March 2002 / Received in final form 4 November 2002 Published online 4 February 2003
RID="a"
ID="a"Currently a visiting researcher at the Institute of Statistical Mathematics, 4-6-7 Minami Azabu, Minato-ku, Tokyo 106-8569,
Japan e-mail: peng@ism.ac.jp 相似文献
15.
E. Bompard Y. C. Ma E. Ragazzi 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):153-160
Competition has been introduced in the electricity markets with
the goal of reducing prices and improving efficiency. The basic idea which
stays behind this choice is that, in competitive markets, a greater quantity
of the good is exchanged at a lower price, leading to higher
market efficiency.
Electricity markets are pretty different from other commodities
mainly due to the physical constraints related to the network structure that
may impact the market performance. The network structure of the system on
which the economic transactions need to be undertaken poses strict physical
and operational constraints.
Strategic interactions among producers that game the market with the
objective of maximizing their producer surplus must be taken into account
when modeling competitive electricity markets. The physical constraints,
specific of the electricity markets, provide additional opportunity of
gaming to the market players. Game theory provides a tool to model such a
context. This paper discussed the application of game theory to physical constrained
electricity markets with the goal of providing tools for assessing the market
performance and pinpointing the critical network constraints that may impact
the market efficiency. The basic models of game theory specifically designed
to represent the electricity markets will be presented. IEEE30 bus test
system of the constrained electricity market will be discussed to show the
network impacts on the market performances in presence of strategic bidding
behavior of the producers. 相似文献
16.
In this paper, we use the generalized Hurst exponent approach to study the multi-scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multi-scaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal model, autoregressive fractionally integrated moving average processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality. 相似文献
17.
A. Dionisio R. Menezes D. A. Mendes 《The European Physical Journal B - Condensed Matter and Complex Systems》2006,50(1-2):161-164
In recent years there has been a closer interrelationship between several scientific areas trying
to obtain a more realistic and rich explanation of the natural and social phenomena. Among these it should be
emphasized the increasing interrelationship between physics and financial theory. In this field the analysis
of uncertainty, which is crucial in financial analysis, can be made using measures of physics statistics and
information theory, namely the Shannon entropy. One advantage of this approach is that the entropy is a more
general measure than the variance, since it accounts for higher order moments of a probability distribution function.
An empirical application was made using data collected from the Portuguese Stock Market. 相似文献
18.
S. M.D. Queirós L. G. Moyano J. de Souza C. Tsallis 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,55(2):161-167
We present results about financial market observables, specifically
returns and traded volumes. They are obtained within the current nonextensive statistical mechanical framework based on the
entropy
. More precisely, we present stochastic dynamical mechanisms which mimic probability density functions empirically observed.
These mechanisms provide possible interpretations for the emergence of the entropic
indices q in the time evolution of the corresponding observables. In addition to this, through multi-fractal analysis of return
time series, we verify that the dual relation qstat+qsens=2 is numerically satisfied, qstat and qsens being associated to the probability density function and to the sensitivity to initial conditions respectively. This type
of simple relation, whose understanding remains ellusive, has been empirically verified in various other systems. 相似文献
19.
J.-P. Bouchaud L. Laloux M. A. Miceli M. Potters 《The European Physical Journal B - Condensed Matter and Complex Systems》2007,55(2):201-207
We present a general method to detect and extract
from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality.
Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval where
singular values are expected in the absence of any true correlations between the variables under study. Our result can be
seen as the natural generalization of the Marčenko-Pastur distribution for the case of rectangular correlation matrices. We
illustrate the interest of our method on a set of macroeconomic time series. 相似文献
20.
In financial markets, the relation between fluctuations of stock prices and trading behaviors is complex. It is intriguing to quantify this kind of meta-correlation between market fluctuations and the synchronous behaviors. We refine the theoretical index leverage model proposed by Reigneron et al., to exactly quantify the meta-correlation under various levels of price fluctuations [Reigneron P A, Allez R and Bouchaud J P 2011 Physica A 390 3026]. The characteristics of meta-correlations in times of market losses, are found to be significantly different in Chinese and American financial markets. In addition,unlike the asymmetric results at the daily scale, the correlation behaviors are found to be symmetric at the high-frequency scale. 相似文献