arXiv subjects

J. Kwapien

Publications and source records attributed to J. Kwapien.

26 records · Page 2Linked to original sources

arXiv2003

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.

cond-mat.soft↗

arXiv2003

Alternation of different fluctuation regimes in the stock market dynamics

Based on the tick-by-tick stock prices from the German and American stock markets, we study the statistical properties of the distribution of the individual stocks and the index returns in highly collective and noisy intervals of trading, separately. We show that periods characterized by the strong inter-stock couplings can be associated with the distributions of index fluctuations which reveal more pronounced tails than in the case of weaker couplings in the market. During periods of strong correlations in the German market these distributions can even reveal an apparent Lévy-stable component.

cond-mat.soft↗

arXiv2001

Identifying Complexity by Means of Matrices

Complexity is an interdisciplinary concept which, first of all, addresses the question of how order emerges out of randomness. For many reasons matrices provide a very practical and powerful tool in approaching and quantifying the related characteristics. Based on several natural complex dynamical systems, like the strongly interacting quantum many-body systems, the human brain and the financial markets, by relating empirical observations to the random matrix theory and quantifying deviations in term of a reduced dimensionality, we present arguments in favour of the statement that complexity is a pheomenon at the edge between collectivity and chaos.

cond-mat.soft↗

arXiv2001

Decomposing the stock market intraday dynamics

The correlation matrix formalism is used to study temporal aspects of the stock market evolution. This formalism allows to decompose the financial dynamics into noise as well as into some coherent repeatable intraday structures. The present study is based on the high-frequency Deutsche Aktienindex (DAX) data over the time period between November 1997 and September 1999, and makes use of both, the corresponding returns as well as volatility variations. One principal conclusion is that a bulk of the stock market dynamics is governed by the uncorrelated noise-like processes. There exists however a small number of components of coherent short term repeatable structures in fluctuations that may generate some memory effects seen in the standard autocorrelation function analysis. Laws that govern fluctuations associated with those various components are different, which indicates an extremely complex character of the financial fluctuations.

cond-mat.soft↗

arXiv2001

Quantifying dynamics of the financial correlations

A novel application of the correlation matrix formalism to study dynamics of the financial evolution is presented. This formalism allows to quantify the memory effects as well as some potential repeatable intradaily structures in the financial time-series. The present study is based on the high-frequency Deutsche Aktienindex (DAX) data over the time-period between November 1997 and December 1999 and demonstrates a power of the method. In this way two significant new aspects of the DAX evolution are identified: (i) the memory effects turn out to be sizably shorter than what the standard autocorrelation function analysis seems to indicate and (ii) there exist short term repeatable structures in fluctuations that are governed by a distinct dynamics. The former of these results may provide an argument in favour of the market efficiency while the later one may indicate origin of the difficulty in reaching a Gaussian limit, expected from the central limit theorem, in the distribution of returns on longer time-horizons.

cond-mat.soft↗

arXiv2000

Temporal correlations versus noise in the correlation matrix formalism: an example of the brain auditory response

We adopt the concept of the correlation matrix to study correlations among sequences of time-extended events occuring repeatedly at consecutive time-intervals. As an application we analyse the magnetoencephalography recordings obtained from human auditory cortex in epoch mode during delivery of sound stimuli to the left or right ear. We look into statistical properties and the eigenvalue spectrum of the correlation matrix C calculated for signals corresponding to different trials and originating from the same or opposite hemispheres. The spectrum of C largely agrees with the universal properties of the Gaussian orthogonal ensemble of random matrices, with deviations characterised by eigenvectors with high eigenvalues. The properties of these eigenvectors and eigenvalues provide an elegant and powerful way of quantifying the degree of the underlying collectivity during well defined latency intervals with respect to stimulus onset. We also extend this analysis to study the time-lagged interhemispheric correlations, as a computationally less demanding alternative to other methods such as mutual information.

cond-mat.stat-mech↗

arXiv1999

Collectivity in the Brain Sensory Response

A question of cooperative effects in auditory brain processing on various space- and time-scales is addressed. The experimental part of our study is based on Multichannel Magnetoencephalography recordings in normal human subjects. Left, right and binaural stimulations were used, in separate runs, for each subject. The resulting time-series representing left and right auditory cortex activity provide a clear evidence for two levels of neuronal cooperation. One is the local hemispheric collective response, termed M100 for its maximum at around 100ms after a stimulus onset. Its only global characteristics turn out to be time-locked to a stimulus, however, which means that the detailed neuronal evolution is largely stochastic. This, together with the $1/f$ character of the corresponding power spectrum indicates self-organized criticality as an underlying mechanism. The second level is communication between the two hemispheres with clear laterality effects: as a rule, the contralateral hemisphere leads by $\sim$10ms. Mutual information analysis points to a direct information transport as a way of this communication.

cond-mat↗

arXiv1998

Cooperative dynamics in auditory brain response

Simultaneous estimates of the activity in the left and right auditory cortex of five normal human subjects were extracted from Multichannel Magnetoencephalography recordings. Left, right and binaural stimulation were used, in separate runs, for each subject. The resulting time-series of left and right auditory cortex activity were analysed using the concept of mutual information. The analysis constitutes an objective method to address the nature of inter-hemispheric correlations in response to auditory stimulations. The results provide a clear evidence for the occurrence of such correlations mediated by a direct information transport, with clear laterality effects: as a rule, the contralateral hemisphere leads by 10-20ms, as can be seen in the average signal. The strength of the inter-hemispheric coupling, which cannot be extracted from the average data, is found to be highly variable from subject to subject, but remarkably stable for each subject.

physics.bio-ph↗