Articles producció científica> Gestió d'Empreses

Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent

  • Datos identificativos

    Identificador: imarina:9247876
    Autores:
    Arouxet MBBariviera AFPastor VEVampa V
    Resumen:
    Cryptocurrency history begins in 2008 as a means of payment proposal. However, cryptocurrencies evolved into a complex ecosystem of high yield speculative assets. Contrary to traditional financial instruments, they are not (mostly) traded in organized, law-abiding venues, but on online platforms, where anonymity reigns. This paper examines the long term memory in return and volatility, using high frequency time series of seven important coins. Our study covers the pre-Covid-19 and the subsequent pandemic period. We use a recently developed method, based on the wavelet transform, which provides more robust estimators of the Hurst exponent. We detect that, during the peak of Covid-19 pandemic (around March 2020), the long memory of returns was only mildly affected. However, volatility suffered a temporary impact in its long range correlation structure. Our results could be of interest for both academics and practitioners.
  • Otros:

    Autor según el artículo: Arouxet MB; Bariviera AF; Pastor VE; Vampa V
    Departamento: Gestió d'Empreses
    Autor/es de la URV: Fernández Bariviera, Aurelio
    Palabras clave: Wavelet transform Long-range dependence Hurst exponent Cryptocurrencies Covid-19 weak wavelet transform time-series rates noises market informational efficiency inefficiency hurst exponent covid-19
    Resumen: Cryptocurrency history begins in 2008 as a means of payment proposal. However, cryptocurrencies evolved into a complex ecosystem of high yield speculative assets. Contrary to traditional financial instruments, they are not (mostly) traded in organized, law-abiding venues, but on online platforms, where anonymity reigns. This paper examines the long term memory in return and volatility, using high frequency time series of seven important coins. Our study covers the pre-Covid-19 and the subsequent pandemic period. We use a recently developed method, based on the wavelet transform, which provides more robust estimators of the Hurst exponent. We detect that, during the peak of Covid-19 pandemic (around March 2020), the long memory of returns was only mildly affected. However, volatility suffered a temporary impact in its long range correlation structure. Our results could be of interest for both academics and practitioners.
    Áreas temáticas: Statistics and probability Statistical and nonlinear physics Química Psicología Physics, multidisciplinary Physics Nutrição Medicina veterinaria Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Linguística e literatura Interdisciplinar Geociências Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Educação física Economia Direito Condensed matter physics Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: aurelio.fernandez@urv.cat
    Identificador del autor: 0000-0003-1014-1010
    Fecha de alta del registro: 2024-09-07
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://toc5.sustainable.cechire.com/science/article/pii/S0378437122001765
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Physica A-Statistical Mechanics And Its Applications. 596
    Referencia de l'ítem segons les normes APA: Arouxet MB; Bariviera AF; Pastor VE; Vampa V (2022). Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent. Physica A-Statistical Mechanics And Its Applications, 596(), -. DOI: 10.1016/j.physa.2022.127170
    DOI del artículo: 10.1016/j.physa.2022.127170
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2022
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Condensed Matter Physics,Physics,Physics, Multidisciplinary,Statistical and Nonlinear Physics,Statistics and Probability
    Wavelet transform
    Long-range dependence
    Hurst exponent
    Cryptocurrencies
    Covid-19
    weak
    wavelet transform
    time-series
    rates
    noises
    market
    informational efficiency
    inefficiency
    hurst exponent
    covid-19
    Statistics and probability
    Statistical and nonlinear physics
    Química
    Psicología
    Physics, multidisciplinary
    Physics
    Nutrição
    Medicina veterinaria
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Linguística e literatura
    Interdisciplinar
    Geociências
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Educação física
    Economia
    Direito
    Condensed matter physics
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
    Administração, ciências contábeis e turismo
    Administração pública e de empresas, ciências contábeis e turismo
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