313 research outputs found

    Log-periodic self-similarity: an emerging financial law?

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    A hypothesis that the financial log-periodicity, cascading self-similarity through various time scales, carries signatures of a law is pursued. It is shown that the most significant historical financial events can be classified amazingly well using a single and unique value of the preferred scaling factor lambda=2, which indicates that its real value should be close to this number. This applies even to a declining decelerating log-periodic phase. Crucial in this connection is identification of a "super-bubble" (bubble on bubble) phenomenon. Identifying a potential "universal" preferred scaling factor, as undertaken here, may significantly improve the predictive power of the corresponding methodology. Several more specific related results include evidence that: (i) the real end of the high technology bubble on the stock market started (with a decelerating log-periodic draw down) in the begining of September 2000; (ii) a parallel 2000-2002 decline seen in the Standard & Poor's 500 from the log-periodic perspective is already of the same significance as the one of the early 1930s and of the late 1970s; (iii) all this points to a much more serious global crash in around 2025, of course from a level much higher (at least one order of magnitude) than in 2000.Comment: Talk given by S. Drozdz at International Econophysics Conference, Bali, August 28-31, 2002; typos correcte

    Decomposing the stock market intraday dynamics

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    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.Comment: 15 pages, 13 PostScript figure

    Quantifying dynamics of the financial correlations

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    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.Comment: 10 pages, 7 PostScript figures, talk presented by the first Author at the NATO ARW on Econophysics, Prague, February 8-10, 2001; to be published in proceedings (Physica A

    Quantum Monte Carlo calculation of the finite temperature Mott-Hubbard transition

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    We present clear numerical evidence for the coexistence of metallic and insulating dynamical mean field theory(DMFT) solutions in a half-filled single-band Hubbard model with bare semicircular density of states at finite temperatures. Quantum Monte Carlo(QMC) method is used to solve the DMFT equations. We discuss important technical aspects of the DMFT-QMC which need to be taken into account in order to obtain the reliable results near the coexistence region. Among them are the critical slowing down of the iterative solutions near phase boundaries, the convergence criteria for the DMFT iterations, the interpolation of the discretized Green's function and the reduction of QMC statistical and systematic errors. Comparison of our results with those of other numerical methods is presented in a phase diagram.Comment: 4 pages, 5 figure

    Variety and Volatility in Financial Markets

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    We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the nn stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of ensemble return distribution central moments by investigating their probability density functions and temporal correlation properties. In general, time-averaged and portfolio-averaged price returns have different statistical properties. We infer from these differences information about the relative strength of correlation between stocks and between different trading days. Lastly, we compare our empirical results with those predicted by the single-index model and we conclude that this simple model is unable to explain the statistical properties of the second moment of the ensemble return distribution.Comment: 10 pages, 11 figure

    Persistence Probabilities of the German DAX and Shanghai Index

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    We present a relatively detailed analysis of the persistence probability distributions in financial dynamics. Compared with the auto-correlation function, the persistence probability distributions describe dynamic correlations non-local in time. Universal and non-universal behaviors of the German DAX and Shanghai Index are analyzed, and numerical simulations of some microscopic models are also performed. Around the fixed point z0=0z_0=0, the interacting herding model produces the scaling behavior of the real markets

    Anomalous Diffusion in Aperiodic Environments

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    We study the Brownian motion of a classical particle in one-dimensional inhomogeneous environments where the transition probabilities follow quasiperiodic or aperiodic distributions. Exploiting an exact correspondence with the transverse-field Ising model with inhomogeneous couplings we obtain many new analytical results for the random walk problem. In the absence of global bias the qualitative behavior of the diffusive motion of the particle and the corresponding persistence probability strongly depend on the fluctuation properties of the environment. In environments with bounded fluctuations the particle shows normal diffusive motion and the diffusion constant is simply related to the persistence probability. On the other hand in a medium with unbounded fluctuations the diffusion is ultra-slow, the displacement of the particle grows on logarithmic time scales. For the borderline situation with marginal fluctuations both the diffusion exponent and the persistence exponent are continuously varying functions of the aperiodicity. Extensions of the results to disordered media and to higher dimensions are also discussed.Comment: 11 pages, RevTe

    A novel proviral clone of HIV-2: Biological and phylogenetic relationship to other primate immunodeficiency viruses.

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    Infectious molecular clones of the human immunodeficiency virus type 2 (HIV-2) will be valuable tools for the study of regulatory gene functions and the development of an animal model for the human acquired immunodeficiency syndrome (AIDS). To this end, we have cloned and sequenced a novel HIV-2 isolate, HIV-2BEN. One clone, designated MK6, is infectious for various human T-cell lines and for human and macaque peripheral blood lymphocytes (PBL), allowing molecular studies of HIV-2 infection and replication. Since MK6 is highly cytopathic in MT-2 and Molt-4 clone 8 cells, antiviral agents and neutralizing sera may be tested. Cluster analysis of HIV-1, HIV-2, and simian immunodeficiency virus (SIV) env and gag genes revealed that HIV-2BEN yielded the earliest node of phylogenetic divergence for all reported HIV-2 sequences. Noise analysis showed that, with the current data, no specification of any branching order can be made among the four groups of primate lentiviruses, HIV-1, HIV-2/SIVSMM/MAC, SIVAGM, and SIVMND

    A New Method to Estimate the Noise in Financial Correlation Matrices

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    Financial correlation matrices measure the unsystematic correlations between stocks. Such information is important for risk management. The correlation matrices are known to be ``noise dressed''. We develop a new and alternative method to estimate this noise. To this end, we simulate certain time series and random matrices which can model financial correlations. With our approach, different correlation structures buried under this noise can be detected. Moreover, we introduce a measure for the relation between noise and correlations. Our method is based on a power mapping which efficiently suppresses the noise. Neither further data processing nor additional input is needed.Comment: 25 pages, 8 figure

    Surface metal-insulator transition in the Hubbard model

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    The correlation-driven metal-insulator (Mott) transition at a solid surface is studied within the Hubbard model for a semi-infinite lattice by means of the dynamical mean-field theory. The transition takes place at a unique critical strength of the interaction. Depending on the surface geometry, the interaction strength and the wave vector, we find one-electron excitations in the coherent part of the surface-projected metallic spectrum which are confined to two dimensions.Comment: LaTeX, 9 pages, 5 eps figures included, Phys. Rev. B (in press
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