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Cross-Correlations in Warsaw Stock Exchange

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EN
We study the inter-stock correlations for the largest companies listed on Warsaw Stock Exchange and included in the WIG20 index. Our results from the correlation matrix analysis indicate that the Polish stock market can be well described by a one-factor model. We also show that the stock- stock correlations tend to increase with the timescale of returns and they approach a saturation level for the timescales of at least 200 min, i.e. an order of magnitude longer than in the case of some developed markets. We also show that the strength of correlations among the stocks crucially depends on their capitalization. These results combined with our earlier findings together suggest that now the Polish stock market situates itself somewhere between an emerging market phase and a mature market phase.
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Modelling Emergence of Money

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issue 4
676-680
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The agent-based computational economic (ACE) model with one free parameter (Thresh) proposed by Yasutomi is analyzed in details. We have found that for a narrow range of the parameter, in the money emergence phase, the money lifetime is finite and the "money switching" effect can be observed for long enough time evolution. Long periods of stability are followed by shorter periods with much shorter money lifetimes. Distributions of the money switching points have been found to have non-Cantor distribution on the time axis, i.e. the Rényi exponents determined by the box-counting algorithm equal 1.0 with high accuracy.
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In this model study of the commodity market, we present some evidence of competition of commodities for the status of money in the regime of parameters, where emergence of money is possible. The competition reveals itself as a rivalry of a few (typically two) dominant commodities, which take the status of money in turn.
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Based on the log-periodic power law methodology, with the universal preferred scaling factor λ ≈2, the negative bubble on the oil market in 2014-2016 has been detected. Over the same period a positive bubble on the so-called commodity currencies expressed in terms of the US dollar appears to take place with the oscillation pattern which largely is mirror reflected relative to oil price oscillation pattern. It documents recent strong anticorrelation between the dynamics of the oil price and of the USD. A related forecast made at the time of FENS 2015 conference (beginning of November) turned out to be quite satisfactory. These findings provide also further indication that such a log-periodically accelerating down-trend signals termination of the corresponding decreases.
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Applicability of the concept of financial log-periodicity is discussed and encouragingly verified for various phases of the world stock markets development in the period 2000-2010. In particular, a speculative forecasting scenario designed in the end of 2004, that properly predicted the world stock market increases in 2007, is updated by setting some more precise constraints on the time of duration of the present long-term equity market bullish phase. A termination of this phase is evaluated to occur in around November 2009. In particular, on the way towards this dead-line, a Spring-Summer 2008 increase is expected. On the precious metals market a forthcoming critical time signal is detected at the turn of March/April 2008 which marks a tendency for at least a serious correction to begin.
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Correlation matrices of foreign exchange rate time series are investigated for 60 world currencies. Minimal spanning tree graphs for the gold, silver and platinum are presented. Inverse power like scaling is discussed for these graphs as well as for four distinct currency groups (major, liquid, less liquid and non-tradable). The worst scaling was found for USD and related currencies.
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Effect of Detrending on Multifractal Characteristics

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Different variants of multifractal detrended fluctuation analysis technique are applied in order to investigate various (artificial and real-world) time series. Our analysis shows that the calculated singularity spectra are very sensitive to the order of the detrending polynomial used within the multifractal detrended fluctuation analysis method. The relation between the width of the multifractal spectrum (as well as the Hurst exponent) and the order of the polynomial used in calculation is evident. Furthermore, type of this relation itself depends on the kind of analyzed signal. Therefore, such an analysis can give us some extra information about the correlative structure of the time series being studied.
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Methodology that recently leads us to predict to an amazing accuracy the date (July 11, 2008) of reverse of the oil price up trend is briefly summarized and some further aspects of the related oil price dynamics elaborated. This methodology is based on the concept of discrete scale invariance whose finance-prediction-oriented variant involves such elements as log-periodic self-similarity, the universal preferred scaling factor λ≈2, and allows a phenomenon of the "super-bubble". From this perspective the present (as of August 22, 2008) violent - but still log-periodically decelerating - decrease of the oil prices is associated with the decay of such a "super-bubble" that has started developing about one year ago on top of the longer-term oil price increasing phase (normal bubble) whose ultimate termination is evaluated to occur in around mid 2010.
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Fractals, Log-Periodicity and Financial Crashes

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EN
Presence of self-similar patterns in the financial dynamics is by now well established and even convincingly quantified within the multifractal formalism. Here we focus attention on one particular aspect of this self-similarity which potentially is related to the discrete-scale invariance underlying the system composition and manifests itself by the log-periodic oscillations cascading self-similarly through various time scales. Such oscillations accumulate at the turning (critical) points that in the financial dynamics are often identified as crashes. This property thus allows us to develop a methodology that may be useful also for prediction. A model Weierstrass-type function is used to illustrate the relevant effects and several examples demonstrating that such effects in the real financial markets take place indeed, are reviewed.
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Agent-Based Modelling of a Commodity Market Dynamics

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EN
A modification of Yasutomi's agent-based model of the commodity market is investigated. It is argued that introduced modification of the microscopic exchange rules allows for emergence of commodity exchange rates in the model. Moreover, the model scaling due to finite size effects is considered and some practical implications of such scaling are discussed.
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EN
We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using multifractal detrended fluctuation analysis. By calculating the singularity spectra f(α) we show that returns of both signs reveal multiscaling. Curiously, these spectra display a significant difference in the scaling properties of returns with opposite sign. The negative price changes are ruled by stronger temporal correlations than the positive ones, which is manifested by larger values of the corresponding Hölder exponents. As regards the properties of dominant trends, a bear market is more persistent than the bull market irrespective of the sign of fluctuations.
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