COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling

Apergis, Nicholas

doi:10.1016/j.frl.2021.102659

Cited by 29 publications

(26 citation statements)

References 45 publications

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“…Yousaf and Ali 2020;Polat and Günay 2021;Naeem et al 2021;Demiralay and Golitsis 2021;Raza et al 2022;Kumar et al 2022;Özdemir 2022;Ahmed and Sleem 2022). More importantly, asymmetric characteristics, tail risk, extreme volatility, and pricing bubbles in the cryptocurrency market have all been identified during the COVID-19 pandemic (see Nguyen et al 2020;Xu et al 2021;González et al 2021;Apergis 2022;Iqbal et al 2021;Montasser et al 2022;Ahn 2022;Shahzad et al 2022). Indeed, these typical features are all related to the higher-order moment risks, highlighting the necessity of analyzing the higher-order moment comovement and risk connectedness.…”

Section: Introductionmentioning

confidence: 99%

Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic

Cui

Maghyereh

2022

Financ Innov

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Analyzing comovements and connectedness is critical for providing significant implications for crypto-portfolio risk management. However, most existing research focuses on the lower-order moment nexus (i.e. the return and volatility interactions). For the first time, this study investigates the higher-order moment comovements and risk connectedness among cryptocurrencies before and during the COVID-19 pandemic in both the time and frequency domains. We combine the realized moment measures and wavelet coherence, and the newly proposed time-varying parameter vector autoregression-based frequency connectedness approach (Chatziantoniou et al. in Integration and risk transmission in the market for crude oil a time-varying parameter frequency connectedness approach. Technical report, University of Pretoria, Department of Economics, 2021) using intraday high-frequency data. The empirical results demonstrate that the comovement of realized volatility between BTC and other cryptocurrencies is stronger than that of the realized skewness, realized kurtosis, and signed jump variation. The comovements among cryptocurrencies are both time-dependent and frequency-dependent. Besides the volatility spillovers, the risk spillovers of high-order moments and jumps are also significant, although their magnitudes vary with moments, making them moment-dependent as well and are lower than volatility connectedness. Frequency connectedness demonstrates that the risk connectedness is mainly transmitted in the short term (1–7 days). Furthermore, the total dynamic connectedness of all realized moments is time-varying and has been significantly affected by the outbreak of the COVID-19 pandemic. Several practical implications are drawn for crypto investors, portfolio managers, regulators, and policymakers in optimizing their investment and risk management tactics.

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Section: Introductionmentioning

confidence: 99%

Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic

Cui

Maghyereh

2022

Financ Innov

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“…Nonetheless, volatility undergoes a temporary effect in its long-range correlation structure. Apergis (2021) analyzes how the Covid-19 pandemic can determine and forecast conditional volatility returns during the period 01/02/2020–31/10/2021.The empirical results that the health crisis affects significantly and positively the conditional volatility. James et al (2021) examine the extreme and erratic behaviors of cryptocurrency markets over the period 30/06/2018–24/06/2020.…”

Section: Literature Reviewmentioning

confidence: 99%

On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis

Béjaoui

Mgadmi²,

Moussa³

2022

Resources Policy

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“…They predictive model which includes the new impact can successfully forecast the volatility of cryptocurrency than the benchmark model. Apergis (2022) examines the importance of health crisis in determining and predicting conditional volatility returns for different digital currencies based on asymmetric GARCH model. The empirical results show that the Covid-19 pandemic significantly and positively affects the conditional return volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of the COVID-19 Pandemic on the Cryptocurrency Market

Mgadmi

Béjaoui

Moussa

et al. 2022

Sci. Ann. Econ. Bus.

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The purpose of our paper is to analyze the main factors which influence fiscal balance’s evolution and thereby identify solutions for configuring a sustainable fiscal policy. We have selected as independent variables some of the main macroeconomic measures, respectively public debt, unemployment rate, economy openness degree, population, consumer goods’ price index, current account balance, direct foreign investments and economic growth rate. Our research method uses two econometric models applied on a sample of 22 countries, respectively 14 developed and 8 emergent. The first model is a multiple regression and studies the connection between the fiscal balance and selected independent variables, whereas the second one uses first order differences and introduces economic freedom as a dummy variable to catch the dynamic influences of selected measures upon fiscal result. The time interval considered was 1999-2013. The results generated using the two models revealed that public debt, current account balance and economic growth significantly influence the fiscal balance. As a consequence, the governments need to plan and implement a fiscal policy which resonates with economy priorities and the phase of the economic cycle, as well as ensure a proper management of the public debt, stimulate sustainable economic growth and employment.

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COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling

Cited by 29 publications

References 45 publications

Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic

Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic

On the relationship between Bitcoin and other assets during the outbreak of coronavirus: Evidence from fractional cointegration analysis

The Impact of the COVID-19 Pandemic on the Cryptocurrency Market

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