Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction

P.R.L. Alves

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 202, issue C, 480-499

Abstract: 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)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:202:y:2022:i:c:p:480-499

DOI: 10.1016/j.matcom.2022.07.026

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