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

Abstract

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.

Bitcoin volatility in bull vs. bear market-insights from analyzing on-chain metrics and Twitter posts

“…The findings suggest that cryptocurrencies failed to act as a haven during the COVID-19 pandemic. These findings are in contradiction with the ones reported by Gherghina & Simionescu (2023) .…”

“…A study by Gherghina & Simionescu (2023) investigated the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market. Using daily data from January 2020 to September 2021, the authors found that both adverse and optimistic news had the same effect on Bitcoin returns, indicating that fear of missing out behavior does not prevail.…”

Khảo sát hiệu ứng bất đối xứng trong biến động giá của các chuỗi tiền điện tử

“…Nghiên cứu của Gherghina & Simionescu (2023) tìm hiểu về hiệu ứng bất đối xứng của tin tức về đại dịch COVID-19 đối với thị trường tiền điện tử, bằng cách sử dụng phương pháp hồi quy phi tuyến tính tự hồi quy và phân tích tần số để xác định mối quan hệ nguyên nhân giữa tin tức về COVID-19 và thị trường tiền điện tử cho thấy tin tức về COVID-19 có tác động bất đối xứng đến thị trường tiền điện tử. Cụ thể, tin tức tiêu cực về đại dịch có tác động lớn hơn và kéo dài hơn đến biến động giá trong thị trường tiền điện tử so với tin tức tích cực.…”

Investor Behavior in Gold, US Dollars and Cryptocurrency during Global Pandemics

“…Bitcoin recently emerged as a safe-haven asset which should be integrated with commodities and equities for the purpose of providing an efficient investment strategy and a diverse allocation in assets for investors before and during the COVID-19 pandemic (Trichilli and Abbes 2022). Gherghina and Simionescu (2023) studied data related to COVID-19 such as the Coronavirus Fake News Index, Sentiment Index and Coronavirus Panic Index against bitcoin returns using a non-linear autoregressive distributed lag ap-proach and Granger causality to conclude that Bitcoin was resistant to the pandemic crisis and may serve as a hedge during times of turmoil in the market.…”

“…This study concentrated on examining the collective impact on the preservation value of gold, USD currency, and Bitcoin prices during epidemics such as SARS and COVID-19. Previous studies have primarily focused on individual price fluctuations, i.e., Gherghina and Simionescu (2023) on bitcoin prices, Gautam et al (2022) on gold prices in relation to COVID-19 cases, Bampinas and Panagiotidis (2015) on the hedging capability of gold exclusively, while Ahmed and Ponthus (2021) and Ranjan (2022) focused on the trend of the USD in correlation with 5-year government yield rates.…”