Exploring disorder and complexity in the cryptocurrency space

Stošić, Darko; Stošić, Dušan; Ludermir, Teresa B.; Stošić, Tatijana

doi:10.1016/j.physa.2019.03.091

Cited by 35 publications

(16 citation statements)

References 32 publications

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“…Since their inception, cryptocurrencies have been of great interest to researchers in dynamical systems and econophysics. There has been substantial research on individual cryptocurrencies such as Bitcoin [33] , [34] , [35] , [36] , [37] and the disorder and fractal behaviour within cryptocurrencies in general [38] , [39] , [40] , [41] . Notably, Drozdz and coauthors have analysed several quantitative aspects of the cryptocurrency market closely, including cross-correlations, auto-correlations and scaling effects.…”

Section: Introductionmentioning

confidence: 99%

Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19

James

Menzies

Chan

2021

Physica A: Statistical Mechanics and its Applications

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Section: Introductionmentioning

confidence: 99%

Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19

James

Menzies

Chan

2021

Physica A: Statistical Mechanics and its Applications

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“…Given this, taking into account the permutation entropy as a way to discriminate time series, the previous empirical results showed that better results 16,17 are provided by original series, in this case is the daily incidence of SARS-CoV-2 infection. For each country, the time series of temporal evolution of SARS-CoV-2 pandemic are shown in Fig.…”

Section: Resultsmentioning

confidence: 96%

“…This method taking into account a symbolic sequence of ordinal patterns of segments (words) of a given size (embedding dimension) denoted by d 16,40 . Then, for each ordinal pattern the respective instances are counted in order to construct an ordinal pattern probability distribution 17 . More specifically, these ordinal patterns related to the quantifying of Bandt & Pompe probability distribution are calculated by observing the local ordering of consecutive values within each word.…”

Section: Permatutation Entropymentioning

confidence: 99%

Insights into the dynamics of SARS-CoV-2 pandemicvia Shannon-Fisher causality plane

Fernandes

Araujo

Silva

2020

Preprint

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This paper performs a systematic investigation into the temporal evolution of severe acute respiratory disease coronavirus 2 (SARS-CoV-2) pandemic considering 15 diverse countries. Based on the foundations of Information Theory, we apply the Shannon-Fisher causality plane (SFCP), to map the dynamics behavior inherent to SARS-CoV-2 and their respective locations along the (SFCP). Our results show that this dynamics varies widely along the SFCP from the lower-right region, characterized by high entropy and low degree of reliability in relation to the information extracted from the analyzed data set to the top-right region, characterized by the less entropic and high degree of reliability in relation to the information extracted from the analyzed data set. It reveals that we have three different groups of countries in controlling the SARS-CoV-2 pandemic. A country that was proactive in implementing measures such as social distancing, quarantine, orders to stay at home, testing symptomatic and asymptomatic loads and hygienic measures to limit the impacts of SARS-Cov-2 (China) and that today is clearly in the decay phase with the number of cases tending to zero and is no longer in a pandemic situation (efficient). Moderately proactive countries, ie, implemented measures only when the spread of SARS-Cov-2 was already reaching the country (France, Germany, United Kingdom, Spain, Sweden, Italy, Ireland, USA, Austria, and Canada) (moderately efficient) and the reactive countries, which took a long time to implement the measures and/or the infection came later and as a result are not managing to reduce the number of daily cases of SARS-CoV-2 (Russia, Iran, Brazil, and India) (inefficient) and are the new epicenters of the SARS-COV-2 pandemic. Besides, we applied the Bandt Pompe permutation entropy (H) and the Fisher Information (F) to obtain the rank of the most efficient countries to the fight against the SARS-CoV-2. To the best of our knowledge, no researches have been ranking the most proactive countries in the fight against the SARS-CoV-2 dissemination. We truly believe that the empirical results showed in this research draws new perspectives that can collaborate in the formulation of more efficient healthy public policies to combat SARS-CoV-2 spread.

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“…The almost absent sensitivity of the LZC to fluctuations in the time series indicates most likely errors in the calculation algorithm during the transformation of the time series. The complexity-entropy causality plane is employed in order to explore disorder and complexity in the space of cryptocurrencies [33]. They are found to exist on distinct planar locations in the representation space, ranging from structured to stochastic-like behavior Crashes and critical events that took place on this market as well as the reasons that led to them, did not go unheeded.…”

Section: Analysis Of Previous Studiesmentioning

confidence: 99%

Lempel-Ziv Complexity and Crises of Cryptocurrency Market

Soloviev¹,

Семеріков²,

Solovieva³

2020

Proceedings of the III International Scientific Congress Society of Ambient Intelligence 2020 (ISC-SAI 2020)

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The informational (Kolmogorov) measure of complexity in accordance with the Lempel-Ziv algorithm (LZC) is calculated for the logarithmic returns of daily Bitcoin/$ values. The calculations were carried out for a moving window with a variation in its size (50-250 days) in increments of one day in the framework of the implemented coarse graining procedure. It is shown that in both mono-and multi-scaling versions, LZC is sensitive to noticeable fluctuations in the Bitcoin price that occur as a result of critical events in the cryptocurrency market. In equilibrium, stable state, having a relatively low value, LZC rapidly increases immediately before the crisis, which proves the dominance of the chaotic component of the time series. The classification and periodization of crisis phenomena in the cryptocurrency market for the period 2010-2020 has been carried out. The results demonstrate the possibility of using the LZC measure as an indicatorprecursor of crisis phenomena in the cryptocurrency market.

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Exploring disorder and complexity in the cryptocurrency space

Cited by 35 publications

References 32 publications

Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19

Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19

Insights into the dynamics of SARS-CoV-2 pandemicvia Shannon-Fisher causality plane

Lempel-Ziv Complexity and Crises of Cryptocurrency Market

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