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dc.contributor.authorNikolova, Venelina
dc.contributor.authorTrinidad Segovia, Juan Evangelista
dc.contributor.authorFernández Martínez, Manuel
dc.contributor.authorSánchez Granero, Miguel Ángel
dc.date.accessioned2020-09-02T10:44:32Z
dc.date.available2020-09-02T10:44:32Z
dc.date.issued2020-07-24
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10835/8412
dc.description.abstractOne of the main characteristics of cryptocurrencies is the high volatility of their exchange rates. In a previous work, the authors found that a process with volatility clusters displays a volatility series with a high Hurst exponent. In this paper, we provide a novel methodology to calculate the probability of volatility clusters with a special emphasis on cryptocurrencies. With this aim, we calculate the Hurst exponent of a volatility series by means of the FD4 approach. An explicit criterion to computationally determine whether there exist volatility clusters of a fixed size is described. We found that the probabilities of volatility clusters of an index (S&P500) and a stock (Apple) showed a similar profile, whereas the probability of volatility clusters of a forex pair (Euro/USD) became quite lower. On the other hand, a similar profile appeared for Bitcoin/USD, Ethereum/USD, and Ripple/USD cryptocurrencies, with the probabilities of volatility clusters of all such cryptocurrencies being much greater than the ones of the three traditional assets. Our results suggest that the volatility in cryptocurrencies changes faster than in traditional assets, and much faster than in forex pairs.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectvolatility clusteres_ES
dc.subjectHurst exponentes_ES
dc.subjectFD4 approaches_ES
dc.subjectvolatility serieses_ES
dc.subjectprobability of volatility clusteres_ES
dc.subjectS& P500es_ES
dc.subjectBitcoines_ES
dc.subjectEthereumes_ES
dc.subjectRipplees_ES
dc.titleA Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Marketses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2227-7390/8/8/1216es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional