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Financial Return Distributions: Past, Present, and COVID-19

We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017–2020, we model tails of the return distributions at different time scales b...

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Autores principales: Wątorek, Marcin, Kwapień, Jarosław, Drożdż, Stanisław
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8303836/
https://www.ncbi.nlm.nih.gov/pubmed/34356425
http://dx.doi.org/10.3390/e23070884
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author Wątorek, Marcin
Kwapień, Jarosław
Drożdż, Stanisław
author_facet Wątorek, Marcin
Kwapień, Jarosław
Drożdż, Stanisław
author_sort Wątorek, Marcin
collection PubMed
description We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017–2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions. We focus on the fitted function parameters and how they change over the years by comparing our results with those from earlier studies and find that, on the time horizons of up to a few minutes, the so-called “inverse-cubic power-law” still constitutes an appropriate global reference. However, we no longer observe the hypothesized universal constant acceleration of the market time flow that was manifested before in an ever faster convergence of empirical return distributions towards the normal distribution. Our results do not exclude such a scenario but, rather, suggest that some other short-term processes related to a current market situation alter market dynamics and may mask this scenario. Real market dynamics is associated with a continuous alternation of different regimes with different statistical properties. An example is the COVID-19 pandemic outburst, which had an enormous yet short-time impact on financial markets. We also point out that two factors—speed of the market time flow and the asset cross-correlation magnitude—while related (the larger the speed, the larger the cross-correlations on a given time scale), act in opposite directions with regard to the return distribution tails, which can affect the expected distribution convergence to the normal distribution.
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spelling pubmed-83038362021-07-25 Financial Return Distributions: Past, Present, and COVID-19 Wątorek, Marcin Kwapień, Jarosław Drożdż, Stanisław Entropy (Basel) Article We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017–2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions. We focus on the fitted function parameters and how they change over the years by comparing our results with those from earlier studies and find that, on the time horizons of up to a few minutes, the so-called “inverse-cubic power-law” still constitutes an appropriate global reference. However, we no longer observe the hypothesized universal constant acceleration of the market time flow that was manifested before in an ever faster convergence of empirical return distributions towards the normal distribution. Our results do not exclude such a scenario but, rather, suggest that some other short-term processes related to a current market situation alter market dynamics and may mask this scenario. Real market dynamics is associated with a continuous alternation of different regimes with different statistical properties. An example is the COVID-19 pandemic outburst, which had an enormous yet short-time impact on financial markets. We also point out that two factors—speed of the market time flow and the asset cross-correlation magnitude—while related (the larger the speed, the larger the cross-correlations on a given time scale), act in opposite directions with regard to the return distribution tails, which can affect the expected distribution convergence to the normal distribution. MDPI 2021-07-12 /pmc/articles/PMC8303836/ /pubmed/34356425 http://dx.doi.org/10.3390/e23070884 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wątorek, Marcin
Kwapień, Jarosław
Drożdż, Stanisław
Financial Return Distributions: Past, Present, and COVID-19
title Financial Return Distributions: Past, Present, and COVID-19
title_full Financial Return Distributions: Past, Present, and COVID-19
title_fullStr Financial Return Distributions: Past, Present, and COVID-19
title_full_unstemmed Financial Return Distributions: Past, Present, and COVID-19
title_short Financial Return Distributions: Past, Present, and COVID-19
title_sort financial return distributions: past, present, and covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8303836/
https://www.ncbi.nlm.nih.gov/pubmed/34356425
http://dx.doi.org/10.3390/e23070884
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