12 research outputs found
Multifractal Height Cross-Correlation Analysis: A New Method for Analyzing Long-Range Cross-Correlations
We introduce a new method for detection of long-range cross-correlations and
multifractality - multifractal height cross-correlation analysis (MF-HXA) -
based on scaling of qth order covariances. MF-HXA is a bivariate generalization
of the height-height correlation analysis of Barabasi & Vicsek [Barabasi, A.L.,
Vicsek, T.: Multifractality of self-affine fractals, Physical Review A 44(4),
1991]. The method can be used to analyze long-range cross-correlations and
multifractality between two simultaneously recorded series. We illustrate a
power of the method on both simulated and real-world time series.Comment: 6 pages, 4 figure
Quantitative features of multifractal subtleties in time series
Based on the Multifractal Detrended Fluctuation Analysis (MFDFA) and on the
Wavelet Transform Modulus Maxima (WTMM) methods we investigate the origin of
multifractality in the time series. Series fluctuating according to a qGaussian
distribution, both uncorrelated and correlated in time, are used. For the
uncorrelated series at the border (q=5/3) between the Gaussian and the Levy
basins of attraction asymptotically we find a phase-like transition between
monofractal and bifractal characteristics. This indicates that these may solely
be the specific nonlinear temporal correlations that organize the series into a
genuine multifractal hierarchy. For analyzing various features of
multifractality due to such correlations, we use the model series generated
from the binomial cascade as well as empirical series. Then, within the
temporal ranges of well developed power-law correlations we find a fast
convergence in all multifractal measures. Besides of its practical significance
this fact may reflect another manifestation of a conjectured q-generalized
Central Limit Theorem
The foreign exchange market: return distributions, multifractality, anomalous multifractality and Epps effect
We present a systematic study of various statistical characteristics of
high-frequency returns from the foreign exchange market. This study is based on
six exchange rates forming two triangles: EUR-GBP-USD and GBP-CHF-JPY. It is
shown that the exchange rate return fluctuations for all the pairs considered
are well described by the nonextensive statistics in terms of q-Gaussians.
There exist some small quantitative variations in the nonextensivity
q-parameter values for different exchange rates and this can be related to the
importance of a given exchange rate in the world's currency trade. Temporal
correlations organize the series of returns such that they develop the
multifractal characteristics for all the exchange rates with a varying degree
of symmetry of the singularity spectrum f(alpha) however. The most symmetric
spectrum is identified for the GBP/USD. We also form time series of triangular
residual returns and find that the distributions of their fluctuations develop
disproportionately heavier tails as compared to small fluctuations which
excludes description in terms of q-Gaussians. The multifractal characteristics
for these residual returns reveal such anomalous properties like negative
singularity exponents and even negative singularity spectra. Such anomalous
multifractal measures have so far been considered in the literature in
connection with the diffusion limited aggregation and with turbulence. We find
that market inefficiency on short time scales leads to the occurrence of the
Epps effect on much longer time scales. Although the currency market is much
more liquid than the stock markets and it has much larger transaction
frequency, the building-up of correlations takes up to several hours - time
that does not differ much from what is observed in the stock markets. This may
suggest that non-synchronicity of transactions is not the unique source of the
observed effect