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Article

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

1
Faculty of Computer Science and Telecommunications, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland
2
Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, ul. Radzikowskiego 152, 31-342 Kraków, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Ryszard Kutner
Received: 15 June 2021 / Revised: 8 July 2021 / Accepted: 9 July 2021 / Published: 12 July 2021
(This article belongs to the Special Issue Three Risky Decades: A Time for Econophysics?)
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. View Full-Text
Keywords: return distributions; power-law tails; stretched exponentials; q-Gaussians; financial markets; COVID-19 return distributions; power-law tails; stretched exponentials; q-Gaussians; financial markets; COVID-19
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MDPI and ACS Style

Wątorek, M.; Kwapień, J.; Drożdż, S. Financial Return Distributions: Past, Present, and COVID-19. Entropy 2021, 23, 884. https://0-doi-org.brum.beds.ac.uk/10.3390/e23070884

AMA Style

Wątorek M, Kwapień J, Drożdż S. Financial Return Distributions: Past, Present, and COVID-19. Entropy. 2021; 23(7):884. https://0-doi-org.brum.beds.ac.uk/10.3390/e23070884

Chicago/Turabian Style

Wątorek, Marcin, Jarosław Kwapień, and Stanisław Drożdż. 2021. "Financial Return Distributions: Past, Present, and COVID-19" Entropy 23, no. 7: 884. https://0-doi-org.brum.beds.ac.uk/10.3390/e23070884

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