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Abstracts
We analytically derive superstatistics (or complex statistics) that accurately model empirical market activity data (supplied by Bogachev, Ludescher, Tsallis, and Bunde) exhibiting transition thresholds. We measure the interevent times between excessive losses (that is, greater than some threshold) and use the mean interevent time as a control variable to derive a universal description of empirical data collapse. Our superstatistic value is a power-law corrected by the lower incomplete gamma function, which asymptotically tends toward robustness but initially gives an exponential. We find that the scaling shape exponent that drives our superstatistics subordinates themselves and a "superscaling" configuration emerges.
Discipline
- 89.75.Da: Systems obeying scaling laws
- 05.40.-a: Fluctuation phenomena, random processes, noise, and Brownian motion(for fluctuations in superconductivity, see 74.40.-n; for statistical theory and fluctuations in nuclear reactions, see 24.60.-k; for fluctuations in plasma, see 52.25.Gj; for nonlinear dynamics and chaos, see 05.45.-a)
Journal
Year
Volume
Issue
Pages
913-916
Physical description
Dates
published
2016-05
Contributors
author
- Faculty of Physics, University of Warsaw, L. Pasteura 5, PL-02-093 Warsaw, Poland
author
- Faculty of Physics, University of Warsaw, L. Pasteura 5, PL-02-093 Warsaw, Poland
- Center for Polymer Studies and Dept. of Physics, Boston Univ., Boston, MA 02215, USA
- Department of Management, Technology and Economics, ETHZ, Scheuchzerstr. 7, CH-8092 Zürich, Switzerland
author
- Faculty of Physics, University of Warsaw, L. Pasteura 5, PL-02-093 Warsaw, Poland
author
- Faculty of Physics, University of Warsaw, L. Pasteura 5, PL-02-093 Warsaw, Poland
author
- Center for Polymer Studies and Dept. of Physics, Boston Univ., Boston, MA 02215, USA
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv129n503kz