Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction
Mathematics and Computers in Simulation (MATCOM), 2022, vol. 202, issue C, 480-499
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.
Keywords: Econophysics; Financial time series; Chaos; Phase space reconstruction (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:202:y:2022:i:c:p:480-499
Access Statistics for this article
Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens
More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().