Exploring the asymmetric effect of COVID‑19 pandemic news on the cryptocurrency market:evidence from nonlinear autoregressive distributed lag approach and frequency domain causality
作者机构：Department of FinanceBucharest University of Economic Studies6 Romana Square010374 BucharestRomania
出 版 物：《Financial Innovation》 (金融创新（英文）)
年 卷 期：2023年第9卷第1期
页 面：692-749页
核心收录：
学科分类：0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 020205[经济学-产业经济学]
主 题：COVID-19 Bitcoin NARDL EGARCH Frequency domain causality
摘 要：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 *** daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heter-oskedasticity 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 ***,when the nonlinear autoregressive distributed lag model is esti-mated,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 *** 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 *** findings may have significant policy implications for investors and governments because they highlight the impor-tance of news during turbulent *** empirical results indicate that pandemic news could significantly influence Bitcoin’s price.
维普期刊数据库