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Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction
From a methodology in the reconstruction scheme, applicable to chaotic time series of economic indices, this paper presents an analysis of the underlying dynamics of stock markets of North America, Europe and Asia. The same global fit model and reconstruction parameters—employed to study the time ev...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339252/ https://www.ncbi.nlm.nih.gov/pubmed/35937975 http://dx.doi.org/10.1016/j.matcom.2022.07.026 |
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author | Alves, P.R.L. |
author_facet | Alves, P.R.L. |
author_sort | Alves, P.R.L. |
collection | PubMed |
description | From a methodology in the reconstruction scheme, applicable to chaotic time series of economic indices, this paper presents an analysis of the underlying dynamics of stock markets of North America, Europe and Asia. The same global fit model and reconstruction parameters—employed to study the time evolution of S&P 500, NASDAQ Composite, IBEX 35, EURONEXT 100, Nikkei 225 and SSE Composite Index—led a convenient simplification in the analysis. The tools chosen to analyse the time dependence of the level of chaos concerning weeks of economic activity were scatter plots, histograms and sample Spearman correlation coefficients. The results permit to evaluate the impact of the pandemic in the underlying dynamics of different stock markets and to compare them to one another. |
format | Online Article Text |
id | pubmed-9339252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93392522022-08-01 Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction Alves, P.R.L. Math Comput Simul Original Articles From a methodology in the reconstruction scheme, applicable to chaotic time series of economic indices, this paper presents an analysis of the underlying dynamics of stock markets of North America, Europe and Asia. The same global fit model and reconstruction parameters—employed to study the time evolution of S&P 500, NASDAQ Composite, IBEX 35, EURONEXT 100, Nikkei 225 and SSE Composite Index—led a convenient simplification in the analysis. The tools chosen to analyse the time dependence of the level of chaos concerning weeks of economic activity were scatter plots, histograms and sample Spearman correlation coefficients. The results permit to evaluate the impact of the pandemic in the underlying dynamics of different stock markets and to compare them to one another. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2022-12 2022-07-31 /pmc/articles/PMC9339252/ /pubmed/35937975 http://dx.doi.org/10.1016/j.matcom.2022.07.026 Text en © 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Articles Alves, P.R.L. Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title | Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title_full | Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title_fullStr | Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title_full_unstemmed | Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title_short | Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction |
title_sort | quantifying chaos in stock markets before and during covid-19 pandemic from the phase space reconstruction |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339252/ https://www.ncbi.nlm.nih.gov/pubmed/35937975 http://dx.doi.org/10.1016/j.matcom.2022.07.026 |
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