Effect of detrending on multifractal characteristics

Different variants of MFDFA 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 MFDFA 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.Comment: Presented by P. O\'swi\k{e}cimka at FENS2012 conference, 17 pages, 9 figure

The components of empirical multifractality in financial returns

We perform a systematic investigation on the components of the empirical multifractality of financial returns using the daily data of Dow Jones Industrial Average from 26 May 1896 to 27 April 2007 as an example. The temporal structure and fat-tailed distribution of the returns are considered as possible influence factors. The multifractal spectrum of the original return series is compared with those of four kinds of surrogate data: (1) shuffled data that contain no temporal correlation but have the same distribution, (2) surrogate data in which any nonlinear correlation is removed but the distribution and linear correlation are preserved, (3) surrogate data in which large positive and negative returns are replaced with small values, and (4) surrogate data generated from alternative fat-tailed distributions with the temporal correlation preserved. We find that all these factors have influence on the multifractal spectrum. We also find that the temporal structure (linear or nonlinear) has minor impact on the singularity width $\Delta\alpha$ of the multifractal spectrum while the fat tails have major impact on $\Delta\alpha$, which confirms the earlier results. In addition, the linear correlation is found to have only a horizontal translation effect on the multifractal spectrum in which the distance is approximately equal to the difference between its DFA scaling exponent and 0.5. Our method can also be applied to other financial or physical variables and other multifractal formalisms.Comment: 6 epl page

World Financial 2014-2016 Market Bubbles: Oil Negative - US Dollar Positive

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

Fractals, Log-Periodicity and Financial Crashes

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

Modelling Emergence of Money

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

Fractals, Log-Periodicity and Financial Crashes

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

Minimal Spanning Tree Graphs and Power Like Scaling in FOREX Networks

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

Minimal Spanning Tree Graphs and Power Like Scaling in FOREX Networks

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

Agent-based modelling of a commodity market dynamics

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