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

Arouxet, M. Bel 'en; Bariviera, Aurelio F.; Pastor, Ver 'onica E.; Vampa, Victoria

doi:10.1016/j.physa.2022.127170

Cited by 35 publications

(20 citation statements)

References 43 publications

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“…López−Cabarcos et al ( 2021 ) suggested that Bitcoin can be considered a safe-haven during turbulent periods but is desirable for speculative investors during stable terms. Furthermore, Arouxet et al ( 2022 ) also questioned the viability of cryptocurrencies as a safe-haven during the disease outbreak because they were vulnerable to speculative moves, and significant shifts in volatility could indicate the uncertainty surrounding the real price. Hence, the phases of obvious bubble behavior (Corbet et al 2018 ) and the doubting dealing operation (Gandal et al 2018 ) may cast skepticism on Bitcoin’s capability to serve as a safe-haven.…”

Section: Prior Literaturementioning

confidence: 99%

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Gherghina

Simionescu

2023

Financ Innov

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This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the coronavirus indices (Panic, Hype, Fake News, Sentiment, Infodemic, and Media Coverage), on the cryptocurrency market. Using daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heteroskedasticity model, the results revealed that both adverse and optimistic news had the same effect on Bitcoin returns, indicating fear of missing out behavior does not prevail. Furthermore, when the nonlinear autoregressive distributed lag model is estimated, both positive and negative shocks in pandemic indices promote Bitcoin’s daily changes; thus, Bitcoin is resistant to the SARS-CoV-2 pandemic crisis and may serve as a hedge during market turmoil. The analysis of frequency domain causality supports a unidirectional causality running from the Coronavirus Fake News Index and Sentiment Index to Bitcoin returns, whereas daily fluctuations in the Bitcoin price Granger affect the Coronavirus Panic Index and the Hype Index. These findings may have significant policy implications for investors and governments because they highlight the importance of news during turbulent times. The empirical results indicate that pandemic news could significantly influence Bitcoin’s price.

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Section: Prior Literaturementioning

confidence: 99%

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Gherghina

Simionescu

2023

Financ Innov

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“…Information quantifiers have a widespread use in many areas of research [12,29,10,1,30,5]. In particular, they have been useful to characterize the informational content of time series of complex systems [14,21,13,28].…”

Section: Introductionmentioning

confidence: 99%

Cuantificadores de información e impredictibilidad en las series temporales asociadas a la COVID-19

Vampa

Kowalski²,

Losada³

et al. 2023

RMTA

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Aplicamos diferentes cuantificadores de informacion al estudio de series temporales de COVID-19. En primer lugar, analizamos como el hecho de suavizar las curvas altera el contenido de informacion de la serie, aplicando la entropia de permutaciones y la entropia wavelet a la serie de casos diarios nuevos mediante un metodo de ventana movil. Ademas, para estudiar que tan acopladas estan las curvas asociadas con los nuevos casos diarios de infecciones y muertes, calculamos la coherencia wavelet. Nuestros resultados muestran como se pueden utilizar cuantificadores de información para analizar el comportamiento impredecible de esta pandemia en el corto y mediano plazo.

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“…Given this backdrop, our study empirically explores the volatility transmission between NFTs and stock markets in developed countries. There are some recent studies that investigate dynamic volatility spillovers between NFTs volatility and other asset classes, including DeFi, Gold, and S&P500 (Dowling, 2022; Karim et al, 2022; Yousaf & Yarovaya, 2022); oil, currencies, and other commodities (Xia et al, 2022); cryptocurrency markets (Aharon & Demir, 2021; Dowling, 2022; Vidal‐Tomás, 2023a; Zhang et al, 2022); precious and industrial metals (Yousaf et al, 2023); and emerging stock markets (Bejaoui et al, 2023). Our study contributes to the nascent NFTs pricing literature.…”

Section: Introductionmentioning

confidence: 99%

Exploring the time‐frequency connectedness among non‐fungible tokens and developed stock markets

Hemrit,

Benlagha,

Ben Arous

et al. 2023

Intell Sys Acc Fin Mgmt

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SummaryIn this paper, we examine the connectedness between volatilities for various non‐fungible tokens (NFTs) and developed stock markets during the period from July 1, 2018, to June 15, 2022. With the use of the time‐varying connectedness methods to explore the volatility interdependences among these assets, we find that there is a significant volatility connectedness during Russia's invasion of Ukraine and COVID‐19 periods. Evidence emerging from this study advocates the inclusion of NFTs in developed stock markets for medium and long time periods only. The results also suggest that UK and Germany stock markets are the predominant market of spillover transmission, whereas the XTZ is the top net recipient/transmitter of volatility connectedness shocks. Moreover, Chinese stock market and ENJ offer more diversification gains than others, and the volatility connectedness from US stock market to NFTs is more pronounced in the long‐term than the short‐term. Our research provides some urgent and prominent insights to help investors and policymakers to be aware that NFTs are important hedge assets that should be added to stock portfolios during periods of geopolitical stability and in the post‐pandemic times.

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

Cited by 35 publications

References 43 publications

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

Cuantificadores de información e impredictibilidad en las series temporales asociadas a la COVID-19

Exploring the time‐frequency connectedness among non‐fungible tokens and developed stock markets

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