Dynamical Variety of Shapes in Financial Multifractality
The concept of multifractality offers a powerful formal tool to filter out a multitude of the most relevant characteristics of complex time series. The related studies thus far presented in the scientific literature typically limit themselves to evaluation of whether a time series is multifractal, a...
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doaj-1b569c71df974c3ab29e1f304b6ec0992020-11-25T00:56:39ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/70157217015721Dynamical Variety of Shapes in Financial MultifractalityStanisław Drożdż0Rafał Kowalski1Paweł Oświȩcimka2Rafał Rak3Robert Gȩbarowski4Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, PolandComplex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, PolandComplex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, PolandComplex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, PolandFaculty of Physics, Mathematics and Computer Science, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, PolandThe concept of multifractality offers a powerful formal tool to filter out a multitude of the most relevant characteristics of complex time series. The related studies thus far presented in the scientific literature typically limit themselves to evaluation of whether a time series is multifractal, and width of the resulting singularity spectrum is considered a measure of the degree of complexity involved. However, the character of the complexity of time series generated by the natural processes usually appears much more intricate than such a bare statement can reflect. As an example, based on the long-term records of the S&P500 and NASDAQ—the two world-leading stock market indices—the present study shows that they indeed develop the multifractal features, but these features evolve through a variety of shapes, most often strongly asymmetric, whose changes typically are correlated with the historically most significant events experienced by the world economy. Relating at the same time the index multifractal singularity spectra to those of the component stocks that form this index reflects the varying degree of correlations involved among the stocks.http://dx.doi.org/10.1155/2018/7015721 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stanisław Drożdż Rafał Kowalski Paweł Oświȩcimka Rafał Rak Robert Gȩbarowski |
spellingShingle |
Stanisław Drożdż Rafał Kowalski Paweł Oświȩcimka Rafał Rak Robert Gȩbarowski Dynamical Variety of Shapes in Financial Multifractality Complexity |
author_facet |
Stanisław Drożdż Rafał Kowalski Paweł Oświȩcimka Rafał Rak Robert Gȩbarowski |
author_sort |
Stanisław Drożdż |
title |
Dynamical Variety of Shapes in Financial Multifractality |
title_short |
Dynamical Variety of Shapes in Financial Multifractality |
title_full |
Dynamical Variety of Shapes in Financial Multifractality |
title_fullStr |
Dynamical Variety of Shapes in Financial Multifractality |
title_full_unstemmed |
Dynamical Variety of Shapes in Financial Multifractality |
title_sort |
dynamical variety of shapes in financial multifractality |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2018-01-01 |
description |
The concept of multifractality offers a powerful formal tool to filter out a multitude of the most relevant characteristics of complex time series. The related studies thus far presented in the scientific literature typically limit themselves to evaluation of whether a time series is multifractal, and width of the resulting singularity spectrum is considered a measure of the degree of complexity involved. However, the character of the complexity of time series generated by the natural processes usually appears much more intricate than such a bare statement can reflect. As an example, based on the long-term records of the S&P500 and NASDAQ—the two world-leading stock market indices—the present study shows that they indeed develop the multifractal features, but these features evolve through a variety of shapes, most often strongly asymmetric, whose changes typically are correlated with the historically most significant events experienced by the world economy. Relating at the same time the index multifractal singularity spectra to those of the component stocks that form this index reflects the varying degree of correlations involved among the stocks. |
url |
http://dx.doi.org/10.1155/2018/7015721 |
work_keys_str_mv |
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