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Elon Musk’ın Kripto Paralar Hakkındaki Twitter Mesajları Bir Sürü Davranışı Eğilimi Yaratarak Kripto Para Piyasalarını Etkileyebilir mi?

Year 2022, Volume: 6 Issue: 1, 215 - 228, 25.01.2022
https://doi.org/10.25295/fsecon.1028730

Abstract

Bu çalışmanın temel amacı, Elon Mask'in kripto paralar ile ilgili Twitter paylaşımlarının kripto para piyasaları üzerindeki etkilerini sürü davranışı eğilimi kapsamında incelemektir. Bu amaçla Bitcoin ve Dogecoin'in günlük fiyat değerleri ve işlem hacimleri EGARCH modelleri uygulanarak analiz edilmiştir. Sonuçlar, Elon Musk'ın olumlu içerikli Twitter gönderilerinin, fiyat ve işlem hacmi açısından dogecoin'in oynaklığını bitcoin'den daha fazla artırdığını göstermektedir. Ayrıca olumlu tweetlerinin etkisi, Bitcoin ve Dogecoin fiyatlarının ve bunlara ait piyasa işlemlerinin artmasına neden olduğu tespit edilmiştir. Sonuçlara göre olumsuz tweet paylaşımı bitcoin getirilerini olumsuz etkilerken belli bir süre sonra oynaklığın artmasıyla kendini göstermektedir. Diğer bir sonuç ise Dogecoin getirisi ve negatif tweet etkileşiminin zaman aralıklarına göre değişiklik göstermesi ancak volatilite üzerindeki etkisinin varlığının tespit edilememesidir. Ayrıca olumsuz tweetin ardından hem bitcoin hem de dogecoin işlem hacimlerinin ilk günlerde arttığı ancak oynaklıklarının etkilenmediği sonucuna varılmaktadır. Sonuçlar, etkili bir kişinin sosyal medya paylaşımlarının bir sürü davranışı etkisi oluşturarak bunun finansal piyasalar üzerindeki etkilerini göstermesi açısından önemlidir. “Etkili kişi etkisinin” davranışsal finans yanlılığı olarak ortaya çıkarılması çalışmanın özgünlüğü olarak görülmektedir. Bulguların küresel anlamda finansal istikrar için potansiyel risk oluşturabilecek bir faktöre işaret etmesi açısından değerlendirilebileceği düşünülmektedir.

References

  • Aharon, D. Y., Demir, E., Lau, C. K. M., & Zaremba, A. (2020). Twitter-Based Uncertainty and Cryptocurrency Returns. http://dx.doi.org/10.2139/ssrn.3735435
  • Ante, L. (2021). How Elon Musk's Twitter Activity Moves Cryptocurrency Markets. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3778844
  • Choi, H. (2021). Investor Attention and Bitcoin Liquidity: Evidence from Bitcoin Tweets. Finance Research Letters, 39, 101555. https://doi.org/10.1016/j.frl.2020.101555
  • Forbes (2021). Forbes World’s Billionaires List: The Richest in 2021. https://www.forbes.com/billionaires/ (accessed 05.11.2021 and 07.06.2021)
  • Kahneman, D. & Tversky, A. (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47, 263–91. Kraaijeveld, O., & De Smedt, J. (2020). The Predictive Power of Public Twitter Sentiment for Forecasting Cryptocurrency Prices. Journal of International Financial Markets, Institutions, and Money, 65, 101188. https://doi.org/10.1016/j.intfin.2020.101188
  • Musk, E. (2021). https://twitter.com/elonmusk. (accessed 05.06.2021)
  • Naeem, M. A., Mbarki, I., & Shahzad, S. J. H. (2021). Predictive Role of Online Investor Sentiment for Cryptocurrency Market: Evidence from Happiness and Fears. International Review of Economics & Finance, 73, 496-514. https://doi.org/10.1016/j.iref.2021.01.008
  • Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347–370.
  • Öztürk, S. S., & Bilgiç, M. E. (2021). Twitter & Bitcoin: Are the Most Influential Accounts Really Influential?. Applied Economics Letters, 1-4. https://doi.org/10.1080/13504851.2021.1904104
  • SEC (U.S. Securities and Exchange Commission). (2018). Elon Musk Settles SEC Fraud Charges; Tesla Charged With and Resolves Securities Law Charge. https://www.sec.gov/news/press-release/2018-226 (accessed 05.11.2021).
  • Shen, D., Urquhart, A., & Wang, P. (2019). Does Twitter Predict Bitcoin?. Economics Letters, 174, 118-122. https://doi.org/10.1016/j.econlet.2018.11.007
  • Tan, L., Chiang, T. C., Mason, J. R., & Nelling, E. (2008). Herding Behavior in Chinese Stock Markets: An Examination of A and B Shares. Pacific-Basin Finance Journal, 16(1-2), 61-77. https://doi.org/10.1016/j.pacfin.2007.04.004
  • Tversky, A., & Kahneman, D. (1974). Judgement Under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131.
  • Zhang, J. (2020). Do Cryptocurrency Markets React to Issuer Sentiments? Evidence from Twitter. Evidence from Twitter. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3675196

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

Year 2022, Volume: 6 Issue: 1, 215 - 228, 25.01.2022
https://doi.org/10.25295/fsecon.1028730

Abstract

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.

References

  • Aharon, D. Y., Demir, E., Lau, C. K. M., & Zaremba, A. (2020). Twitter-Based Uncertainty and Cryptocurrency Returns. http://dx.doi.org/10.2139/ssrn.3735435
  • Ante, L. (2021). How Elon Musk's Twitter Activity Moves Cryptocurrency Markets. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3778844
  • Choi, H. (2021). Investor Attention and Bitcoin Liquidity: Evidence from Bitcoin Tweets. Finance Research Letters, 39, 101555. https://doi.org/10.1016/j.frl.2020.101555
  • Forbes (2021). Forbes World’s Billionaires List: The Richest in 2021. https://www.forbes.com/billionaires/ (accessed 05.11.2021 and 07.06.2021)
  • Kahneman, D. & Tversky, A. (1979). Prospect Theory: An Analysis of Decision Under Risk. Econometrica, 47, 263–91. Kraaijeveld, O., & De Smedt, J. (2020). The Predictive Power of Public Twitter Sentiment for Forecasting Cryptocurrency Prices. Journal of International Financial Markets, Institutions, and Money, 65, 101188. https://doi.org/10.1016/j.intfin.2020.101188
  • Musk, E. (2021). https://twitter.com/elonmusk. (accessed 05.06.2021)
  • Naeem, M. A., Mbarki, I., & Shahzad, S. J. H. (2021). Predictive Role of Online Investor Sentiment for Cryptocurrency Market: Evidence from Happiness and Fears. International Review of Economics & Finance, 73, 496-514. https://doi.org/10.1016/j.iref.2021.01.008
  • Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347–370.
  • Öztürk, S. S., & Bilgiç, M. E. (2021). Twitter & Bitcoin: Are the Most Influential Accounts Really Influential?. Applied Economics Letters, 1-4. https://doi.org/10.1080/13504851.2021.1904104
  • SEC (U.S. Securities and Exchange Commission). (2018). Elon Musk Settles SEC Fraud Charges; Tesla Charged With and Resolves Securities Law Charge. https://www.sec.gov/news/press-release/2018-226 (accessed 05.11.2021).
  • Shen, D., Urquhart, A., & Wang, P. (2019). Does Twitter Predict Bitcoin?. Economics Letters, 174, 118-122. https://doi.org/10.1016/j.econlet.2018.11.007
  • Tan, L., Chiang, T. C., Mason, J. R., & Nelling, E. (2008). Herding Behavior in Chinese Stock Markets: An Examination of A and B Shares. Pacific-Basin Finance Journal, 16(1-2), 61-77. https://doi.org/10.1016/j.pacfin.2007.04.004
  • Tversky, A., & Kahneman, D. (1974). Judgement Under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131.
  • Zhang, J. (2020). Do Cryptocurrency Markets React to Issuer Sentiments? Evidence from Twitter. Evidence from Twitter. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3675196
There are 14 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Cagri Hamurcu 0000-0002-3248-6733

Publication Date January 25, 2022
Published in Issue Year 2022 Volume: 6 Issue: 1

Cite

APA Hamurcu, C. (2022). Can Elon Mask’s Twitter Posts About Cryptocurrencies Influence Cryptocurrency Markets by Creating a Herding Behavior Bias?. Fiscaoeconomia, 6(1), 215-228. https://doi.org/10.25295/fsecon.1028730

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