COVID-19 vaccine and post-pandemic recovery: Evidence from Bitcoin cross-asset implied volatility spillover

Di, Michael; Xu, Ke

doi:10.1016/j.frl.2022.103289

Cited by 12 publications

(7 citation statements)

References 22 publications

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“…Demir et al ( 2020 ) identified a negative connection among Bitcoin value and the number of reported cases and deaths; however, the relationship turns into positive throughout the subsequent period. In this regard, Di and Xu ( 2022 ) argued that despite the increasing number of new COVID-19 cases brought on by Omicron, the vaccine boosted confidence and sped up the financial market recovery, significantly positively impacting the ability of the financial market to recover from the pandemic.…”

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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“…Beberapa hasil penelitian terdahulu menemukan bahwa pengumuman tentang suatu kebijakan terkait dengan pandemi COVID-19 mempengaruhi pasar modal hampir di seluruh dunia, yaitu mempengaruhi harga saham , likuiditas maupun volatilitasnya (Al-awadhi et al, 2020), (Narayan et al, 2021), (Haroon & Rizvi, 2020), (Di & Xu, 2022), dan (Salisu & Shaik, 2022).…”

Section: Kajian Pustakaunclassified

Pencabutan Status Pandemi COVID-19 oleh Presiden Jokowi Terhadap Saham-Saham JII di Bursa EfekIndonesia

Listyaningsih

2023

JRAMM

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Previous research discovered that the stock exchange responded to the announcement of a government policy related to the COVID-19 pandemic. The purpose of this research is to determine the impact of President Jokowi's announcement of the revocation of the COVID-19 pandemic status on stocks that are members of the Jakarta Islamic Index (JII). The event study methodology was applied to 30 JII stocks that adhere to Islamic Sharia, have high liquidity, and a large market capitalization. This study discovered that there were abnormal returns before and after President Jokowi announced the revocation of the COVID-19 pandemic status. Furthermore, a difference in stock trading volume with the average before and after the announcement was discovered. This indicates that this event contains information content, implying that investors should pay close attention to government policy announcements regarding the pandemic, which can be used as a factor in making investment decisions.

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“…The study further found that stock markets responded reasonably quickly to the increase in confirmed cases rather than deaths. Therefore, the impact of the crisis on financial markets and the broader economic environment, including consumer behavior and intentions, has been a topic of concern among many scholars [5][6][7][8][9]. From this standpoint, asset management has become crucial for organizations seeking to optimize their asset utilization and maximize returns in challenging conditions and volatile markets.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models: Evidence from European Financial Markets and Bitcoins

Ampountolas

2023

Forecasting

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This study analyzes the transmission of market uncertainty on key European financial markets and the cryptocurrency market over an extended period, encompassing the pre-, during, and post-pandemic periods. Daily financial market indices and price observations are used to assess the forecasting models. We compare statistical, machine learning, and deep learning forecasting models to evaluate the financial markets, such as the ARIMA, hybrid ETS-ANN, and kNN predictive models. The study results indicate that predicting financial market fluctuations is challenging, and the accuracy levels are generally low in several instances. ARIMA and hybrid ETS-ANN models perform better over extended periods compared to the kNN model, with ARIMA being the best-performing model in 2018–2021 and the hybrid ETS-ANN model being the best-performing model in most of the other subperiods. Still, the kNN model outperforms the others in several periods, depending on the observed accuracy measure. Researchers have advocated using parametric and non-parametric modeling combinations to generate better results. In this study, the results suggest that the hybrid ETS-ANN model is the best-performing model despite its moderate level of accuracy. Thus, the hybrid ETS-ANN model is a promising financial time series forecasting approach. The findings offer financial analysts an additional source that can provide valuable insights for investment decisions.

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COVID-19 vaccine and post-pandemic recovery: Evidence from Bitcoin cross-asset implied volatility spillover

Cited by 12 publications

References 22 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

Pencabutan Status Pandemi COVID-19 oleh Presiden Jokowi Terhadap Saham-Saham JII di Bursa EfekIndonesia

Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models: Evidence from European Financial Markets and Bitcoins

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