【Author】 Apergis, Nicholas
【Source】FINANCE RESEARCH LETTERS
【影响因子】9.848
【Abstract】This paper analyzes the role of COVID-19 pandemic crisis in determining and forecasting conditional volatility returns for a set of eight cryptocurrencies through an asymmetric GARCH modeling approach. The findings report that the COVID-19 pandemic exerts a positive effect on the conditional volatility of those returns, while explicitly considering the pandemic event improves volatility predictions.
【Keywords】Cryptocurrency returns; COVID-19; Conditional volatility
【发表时间】2022 JUN
【收录时间】2022-07-10
【文献类型】实证性文章
【主题类别】
区块链治理-市场治理-数字货币
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