How Elon Musk's Twitter Activity Moves Cryptocurrency Markets

Ante, Lennart

doi:10.2139/ssrn.3778844

Cited by 44 publications

(35 citation statements)

References 60 publications

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“…The results of the study show that tweets can be used to predict bitcoin returns, and in particular, the most influential accounts, rather than all tweets, are the drivers of these returns. In his research, Ante (2021) shares the result that after every Twitter post by Elon Musk about cryptocurrencies, very crucial abnormal transaction volume and returns for Bitcoin and Dogecoin are detected (Ante, 2021).…”

Section: Introductionmentioning

confidence: 91%

Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?

Hamurcu

2022

Fiscaoeconomia

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The main purpose of this study is to examine the effects of Elon Mask's Twitter posts about cryptocurrencies on cryptocurrency markets within the scope of herding behavior bias. For this purpose, the daily price values and transaction volumes of Bitcoin and Dogecoin are analyzed by applying the EGARCH models. The results show that Elon Musk's positive Twitter posts increase dogecoin's volatility more than bitcoin in terms of price and trading volume. In addition, the effect of positive tweets has been found to increase Bitcoin and Dogecoin prices and their market transactions. According to the results, while negative tweet sharing negatively affects bitcoin returns, it manifests itself with an increase in volatility after a certain period of time. Another result is that the Dogecoin return and negative tweet interaction vary according to time intervals, but the presence of the effect on volatility cannot be determined. It is also concluded that after the negative tweet, both bitcoin and dogecoin transaction volumes increased in the first days, but their volatility was not affected. The results are important in terms of showing the effects of an influential person's social media posts on the financial markets by creating a herd behavior effect. Revealing the "influential person effect" as a behavioral finance bias is seen as the originality of the study. It is thought that the findings can be evaluated in terms of pointing out a factor that may pose a potential risk to financial stability in the global sense.

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Section: Introductionmentioning

confidence: 91%

Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?

Hamurcu

2022

Fiscaoeconomia

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“…Social media posts of celebrities and the media coverage of a particular coin can also affect the prices of cryptocurrencies. For example, Ante et al [60] analyzed to what extent Elon Musk's Twitter posts affect short-term returns and volume. Huynh et al [61] represented an analysis of how the movements of the Bitcoin market correlate to tweets of US President Donald Trump by considering nearly 14,000 tweets from January 2017 to January 2020.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning-Based Cryptocurrency Price Prediction Scheme With Inter-Dependent Relations

Tanwar¹,

Patel

et al. 2021

IEEE Access

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Blockchain technology is becoming increasingly popular because of its applications in various fields. It gives an edge over the traditional centralized methods as it provides decentralization, immutability, integrity, and anonymity. The most popular application of this technology is cryptocurrencies, which showed a massive rise in their popularity and market capitalization in recent years. Individual investors, big institutions, and corporate firms are investing heavily in it. However, the crypto market is less stable than traditional commodity markets. It can be affected by many technical, sentimental, and legal factors, so it is highly volatile, uncertain, and unpredictable. Plenty of research has been done on various cryptocurrencies to forecast accurate prices, but the majority of these approaches can not be applied in real-time. Motivated from the aforementioned discussion, in this paper, we propose a deep-learning-based hybrid model (includes Gated Recurrent Units (GRU) and Long Short Term Memory (LSTM)) to predict the price of Litecoin and Zcash with inter-dependency of the parent coin. The proposed model can be used in real-time scenarios and it is well trained and evaluated using standard data sets. Results illustrate that the proposed model forecasts the prices with high accuracy compared to existing models.

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“…A paper focused on how twitter activity influences cryptocurrencies returns proved through event study methodology that the change of Musk's Twitter biography to #bitcoin resulted in significantly positive cumulative abnormal returns which already amounted to 6.31% after 30 minutes and culminated at 18.99% over a period of six hours (Ante, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of Tesla’s bitcoin investment and its plans to accept it as payment method on the evolution of bitcoin

Mironeanu¹,

Irimia²,

Săndulescu³

et al. 2021

Proceedings of the International Conference on Business Excellence

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For the past years, cryptocurrencies have been a hot and controversial topic that has captured the attention of the whole tech world. Even if right now the portfolio of digital assets is considerable in size, the first cryptocurrency, Bitcoin, exploited its pioneer advantage and managed to remain at the center of attention both for the media and investors. During 2020, one of the most chaotic years, Bitcoin boomed in November 2020 almost doubling since the end of 2019. This boom is the result of a combination of factors, such as the fear of missing out translated into a chain reaction of public and private companies to consider Bitcoin a safe reserve asset, a hedging method against inflation, which represents a substitute for traditional hedging instruments, the infrastructure developed around it over the years, and lastly the hype created by influential figures through news and social media platforms. There have been many public figures that exhibited interest in cryptocurrencies through platforms such as Twitter, for instance Elon Musk, Bill Gates, Kanye West, Hugh Laurie, Mike Tyson and Gwyneth Paltrow are just some in a long list of celebrities that backed Bitcoin. This paper aims to analyze the impact that twitter posts have upon the evolution of Bitcoin, coupled with Tesla’s investment and recent statement of introducing Bitcoin as a method of payment in the near future. Our research tries to determine if the news and social media posts, such as tweets have an influence upon Bitcoin’s volatility and fluctuations.

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How Elon Musk's Twitter Activity Moves Cryptocurrency Markets

Cited by 44 publications

References 60 publications

Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?

Can Elon Mask's Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?

Deep Learning-Based Cryptocurrency Price Prediction Scheme With Inter-Dependent Relations

The impact of Tesla’s bitcoin investment and its plans to accept it as payment method on the evolution of bitcoin

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