The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19

Kyriazis, Nicholas; Papadamou, Stephanos; Corbet, Shaen

doi:10.1016/j.qref.2022.09.004

Cited by 39 publications

(10 citation statements)

References 57 publications

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“…There are two contributions to this paper. First, it enriches the existing literature on the impact of the pandemic on financial markets, specifically the Bitcoin market ( 18 , 31 , 78 ). This paper finds that pandemic attention significantly affects Bitcoin returns and volatility, and that predicting Bitcoin returns and volatility is more accurate when pandemic attention is taken into account.…”

Section: Introduction and Literature Reviewmentioning

confidence: 85%

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The COVID-19 pandemic and Bitcoin: Perspective from investor attention

Wan

Zhu

2023

Front. Public Health

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The response of the Bitcoin market to the novel coronavirus (COVID-19) pandemic is an example of how a global public health crisis can cause drastic market adjustments or even a market crash. Investor attention on the COVID-19 pandemic is likely to play an important role in this response. Focusing on the Bitcoin futures market, this paper aims to investigate whether pandemic attention can explain and forecast the returns and volatility of Bitcoin futures. Using the daily Google search volume index for the “coronavirus” keyword from January 2020 to February 2022 to represent pandemic attention, this paper implements the Granger causality test, Vector Autoregression (VAR) analysis, and several linear effects analyses. The findings suggest that pandemic attention is a granger cause of Bitcoin returns and volatility. It appears that an increase in pandemic attention results in lower returns and excessive volatility in the Bitcoin futures market, even after taking into account the interactive effects and the influence of controlling other financial markets. In addition, this paper carries out the out-of-sample forecasts and finds that the predictive models with pandemic attention do improve the out-of-sample forecast performance, which is enhanced in the prediction of Bitcoin returns while diminished in the prediction of Bitcoin volatility as the forecast horizon is extended. Finally, the predictive models including pandemic attention can generate significant economic benefits by constructing portfolios among Bitcoin futures and risk-free assets. All the results demonstrate that pandemic attention plays an important and non-negligible role in the Bitcoin futures market. This paper can provide enlightens for subsequent research on Bitcoin based on investor attention sparked by public emergencies.

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Section: Introduction and Literature Reviewmentioning

confidence: 85%

“…It is therefore natural to discuss whether Bitcoin returns and volatility are affected by pandemic attention. Numerous academic studies have examined the determinants of Bitcoin returns and volatility (18,(31)(32)(33)(34). However, there is little literature focusing on investor attention.…”

mentioning

confidence: 99%

The COVID-19 pandemic and Bitcoin: Perspective from investor attention

Wan

Zhu

2023

Front. Public Health

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“…The machine learning approach has seen an increased interest in the recent literature [38], especially with the advent of large transfer learning models, such as BERT and its variants [33]. Two of the most popular topics where sentiment analysis, polarity analysis and stance detection have been widely studied in the literature are COVID-19-related social phenomena, such as the role of China [39], vaccinations [2], [7], [40], [41], and lockdowns [42], and finance-related research, either related to the stock market [42], [43] or cryptocurrencies [44], [45].…”

Section: B Stance Detectionmentioning

confidence: 99%

1000 Days of COVID-19: A Gender-Based Long-Term Investigation into Attitudes With Regards to Vaccination

et al. 2023

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The coronavirus pandemic has undoubtedly been one of the major recent events that have affected our society at the global level. During this period, unprecedented measures have been imposed worldwide by authorities in an effort to contain the spread of the disease. These measures have led to a worldwide debate among the public, occurring not least within the forum of social media, tapping into preexisting trends of skepticism, such as vaccine hesitancy. At the same time, it has become apparent that the pandemic affected women and men differently. With these two themes in view, the paper aims to analyze using a data-driven approach the evolution of opinions with regards to vaccination against COVID-19 throughout the entire duration of the pandemic from the point of view of gender. For this analysis, approximately 1,500,000 short user-contributed texts have been retrieved from the popular microblogging platform Twitter, posted between 30 January 2020 and 30 November 2022. Using a machine learning approach, several classifiers have been trained to identify the likely gender (female or male) of the author, as well as the stance of the specific post towards the COVID-19 vaccines (neutral, in favor, or against), achieving 85.69% and 93.64% weighted accuracy measures for each problem, respectively. Based on this analysis, it can be observed that most tweets exhibit a neutral stance, while the number of tweets in favor of vaccination is greater than the number of tweets opposing vaccination, with the distribution varying across time in response to specific events. The subject matter of the tweets varied more between stances than between genders, suggesting that there is no significant difference between the contents of tweets posted by females and males. We also find that while the overall engagement on Twitter with the topic of vaccination against COVID-19 is on the wane, there has been a rise in the number of against tweets continuing into the present.

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“…Youssef and Waked ( 2022 ) employed the Media Coverage Index but explored the herding behavior in the cryptocurrency market. Most of the previous studies employed Google (Urquhart 2018 ; Salisu and Ogbonna 2021 ; Anastasiou et al 2021 ; Rajput et al 2020 ; Figà−Talamanca and Patacca 2020 ; Zhu et al 2021 ; Bashir and Kumar 2022 ; Vukovic et al 2021 ; Benlagha and Hemrit 2022 ; Dias et al 2022 ; Kim and Orlova 2021 ; Bonaparte and Bernile 2022 ; Raza et al 2022b ; Tong et al 2022 ) or Twitter (Shen et al 2019 ; Kraaijeveld and Smedt, 2020 ; Choi 2021 ; Naeem et al 2020 ; Wu et al 2021b ; Elsayed et al 2022 ; Bashir and Kumar, 2022 ; Kyriazis et al 2022 ; Gök et al 2022 ; Dias et al 2022 ; French, 2021 ; Tong et al 2022 ) data and were oriented toward equity markets (Haroon and Rizvi 2020 ; Shi and Ho, 2021 ; Tan 2021 ) or commodities (Atri et al 2021 ). Because the effects of various kinds of news fluctuate, this paper employs different forms of COVID-19 pandemic news.…”

Section: Introductionmentioning

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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The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19

Cited by 39 publications

References 57 publications

The COVID-19 pandemic and Bitcoin: Perspective from investor attention

The COVID-19 pandemic and Bitcoin: Perspective from investor attention

1000 Days of COVID-19: A Gender-Based Long-Term Investigation into Attitudes With Regards to Vaccination

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

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