Detecting and interpreting distortions in hierarchical organization of complex time series

Stanis{\l}aw Dro\.zd\.z and Pawe{\l} O\'swi\k{e}cimka

Papers from arXiv.org

Abstract: Hierarchical organization is a cornerstone of complexity and multifractality constitutes its central quantifying concept. For model uniform cascades the corresponding singularity spectra are symmetric while those extracted from empirical data are often asymmetric. Using the selected time series representing such diverse phenomena like price changes and inter-transaction times in the financial markets, sentence length variability in the narrative texts, Missouri River discharge and Sunspot Number variability as examples, we show that the resulting singularity spectra appear strongly asymmetric, more often left-sided but in some cases also right-sided. We present a unified view on the origin of such effects and indicate that they may be crucially informative for identifying composition of the time series. One particularly intriguing case of this later kind of asymmetry is detected in the daily reported Sunspot Number variability. This signals that either the commonly used famous Wolf formula distorts the real dynamics in expressing the largest Sunspot Numbers or, if not, that their dynamics is governed by a somewhat different mechanism.

Date: 2015-03
New Economics Papers: this item is included in nep-ets
References: Add references at CitEc
Citations:

Published in Phys. Rev. E 91, 030902(R) (2015)

Downloads: (external link)
http://arxiv.org/pdf/1503.02405 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1503.02405

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().