18 research outputs found
Towards identifying the world stock market cross-correlations: DAX versus Dow Jones
Effects connected with the world globalization affect also the financial
markets. On a way towards quantifying the related characteristics we study the
financial empirical correlation matrix of the 60 companies which both the
Deutsche Aktienindex (DAX) and the Dow Jones (DJ) industrial average comprised
during the years 1990-1999. The time-dependence of the underlying
cross-correlations is monitored using a time window of 60 trading days. Our
study shows that if the time-zone delays are properly accounted for the two
distant markets largely merge into one. This effect is particularly visible
during the last few years. It is however the Dow Jones which dictates the
trend.Comment: LaTeX, 6 pages, 8 figure
Are the contemporary financial fluctuations sooner converging to normal?
Based on the tick-by-tick price changes of the companies from the U.S. and
from the German stock markets over the period 1998-99 we reanalyse several
characteristics established by the Boston Group for the U.S. market in the
period 1994-95, which serves to verify their space and time-translational
invariance. By increasing the time scales we find a significantly more
accelerated crossover from the power-law (alpha approximately 3) asymptotic
behaviour of the distribution of returns towards a Gaussian, both for the U.S.
as well as for the German stock markets. In the latter case the crossover is
even faster. Consistently, the corresponding autocorrelation functions of
returns and of the time averaged volatility also indicate a faster loss of
memory with increasing time. This route towards efficiency may reflect a
systematic increase of the information processing when going from past to
present.Comment: 14 pages, revised versio
Self-consistent calculations within the Green's function method including particle-phonon coupling and the single-particle continuum
The Green's function method in the \emph{Quasiparticle Time Blocking
Approximation} is applied to nuclear excitations in Sn and Pb.
The calculations are performed self-consistently using a Skyrme interaction.
The method combines the conventional RPA with an exact single-particle
continuum treatment and considers in a consistent way the particle-phonon
coupling. We reproduce not only the experimental values of low- and high-lying
collective states but we also obtain fair agreement with the data of
non-collective low-lying states that are strongly influenced by the
particle-phonon coupling.Comment: 6 pages, 9 figures, documentclass{svjour
Microscopic description of the pygmy and giant electric dipole resonances in stable Ca isotopes
The properties of the pygmy (PDR) and giant dipole resonance (GDR)in the
stable , and isotopes have been calculated within
the \emph{Extended Theory of Finite Fermi Systems}(ETFFS). This approach is
based on the random phase approximation (RPA) and includes the single particle
continuum as well as the coupling to low-lying collectives states which are
considered in a consistent microscopic way. For we also include
pairing correlations. We obtain good agreement with the experimental data for
the gross properties of both resonances. It is demonstrated that the recently
measured A-dependence of the strength of the PDR below 10 MeV is well
understood in our model:due to the phonon coupling some of the strength in
is simply shifted beyond 10 MeV. The predicted fragmentation of the
PDR can be investigated in and experiments.
Whereas the isovector dipole strength of the PDR is small in all Ca isotopes,
we find in this region surprisingly strong isoscalar dipole states, in
agreement with an experiment. We conclude that for the
detailed understanding of the structure of excited nuclei e.g. the PDR and GDR
an approach like the present one is absolutely necessary.Comment: 6 figure
Prediction oriented variant of financial log-periodicity and speculating about the stock market development until 2010
A phenomenon of the financial log-periodicity is discussed and the characteristics that amplify its predictive potential are elaborated. The principal one is self-similarity that obeys across all the time scales. Furthermore the same preferred scaling factor appears to provide the most consistent description of the market dynamics on all these scales both in the bull as well as in the bear market phases and is common to all the major markets. These ingredients set very desirable and useful constraints for understanding the past market behavior as well as in designing forecasting scenarios. One novel speculative example of a more detailed S&P500 development until 2010 is presented.
Complex Systems: From Nuclear Physics to Financial Markets
We compare correlations and coherent structures in nuclei and financial markets. In the nuclear physics part we review giant resonances which can be interpreted as a coherent structure embedded in chaos. With similar methods we investigate the financial empirical correlation matrix of the DAX and Dow Jones. We will show, that if the time-zone delay is properly accounted for, the two distinct markets largely merge into one. This is reflected by the largest eigenvalue that develops a gap relative to the remaining, chaotic eigenvalues. By extending investigations of the specific character of financial collectivity we also discuss the criticality-analog phenomenon of the financial log-periodicity and show specific examples.
Dynamics of correlations in the stock market
Financial empirical correlation matrices of all the companies which both, the Deutsche Aktienindex (DAX) and the Dow Jones comprised during the time period 1990-1999 are studied using a time window of a limited, either 30 or 60, number of trading days. This allows a clear identification of the resulting correlations. On both these markets the decreases turn out to be always accompanied by a sizable separation of one strong collective eigenstate of the correlation matrix, while increases are more competitive and thus less collective. Generically, however, the remaining eigenstates of the correlation matrix are, on average, consistent with predictions of the random matrix theory. Effects connected with the world globalization are also discussed and a leading role of the Dow Jones is quantified. This effect is particularly spectacular during the last few years, and it turns out to be crucial to properly account for the time-zone delays in order to identify it.
Dynamics of competition between collectivity and noise in the stock market
Detailed study of the financial empirical correlation matrix of the 30 companies comprised by DAX within the period of the last 11 years, using the time-window of 30 trading days, is presented. This allows to clearly identify a nontrivial time-dependence of the resulting correlations. In addition, as a rule, the draw downs are always accompanied by a sizable separation of one strong collective eigenstate of the correlation matrix which, at the same time, reduces the variance of the noise states. The opposite applies to draw ups. In this case the dynamics spreads more uniformly over the eigenstates which results in an increase of the total information entropy.