Measuring the effects of Bitcoin forks on selected cryptocurrencies using event study methodology
Abstract
Cryptocurrencies have been at the center of interest of both academic and professional community for over a decade. Due to the highly volatile exchange rate against convertible currencies, investors use cryptocurrencies as an instrument of speculative investment, while their use in payments are negligible. Over the last few years, all leading cryptocurrencies have recorded highly volatile rates of return, which have often had a negative value. The paper uses the event study methodology to determine the statistical significance of the abnormal return of leading cryptocurrencies after the three Bitcoin forks. The forks were viewed as three isolated events, with the estimations windows and the event windows constructed separately for each of them. There were statistically significant negative effects during the second and third event, related to the creation of Bitcoin Gold and Bitcoin SV. Contrary to the expectations, in the case of the first and most famous Bitcoin fork, which created the Bitcoin Cash, there was no statistically significant effect
References
Brown, S., & Warner, J. (1985). Using daily stock returns. Journal of financial economics, 14(1), 3-31. https://doi.org/10.1016/0304-405x(85)90042-x
Campbell, J.Y., Lo, A.W., & MacKinlay, A.C. (1997). The Econometrics of Financial Markets. Princeton, NJ: Princeton university press, 2nd ed.
Chaparro, F. (2017). Bitcoin is sliding after bitcoin gold goes live, Business Insider, October 24
Corrado, C.J. (1989). A nonparametric test for abnormal security-price performance in event studies. Journal of financial economics, 23(2), 385-395. https://doi.org/10.1016/0304-405x(89)90064-0
Cowan, A.R. (1992). Nonparametric Event Study Tests. Review of Quantitative Finance and accounting, 2(4), 343-358. https://doi.org/10.1007/bf00939016
Dodd, P., & Warner, J.B. (1983). On corporate study: A study of Proxy contest. Journal of Financial Economics, 11(1-4), 401-438. https://doi.org/10.1016/0304-405X(83)90018-1
Dolley, J. (1933). Characteristics and procedure of common stock split-ups. Harvard business review, 11, 316-326
Fama, E., Fischer, L., Jensen, M.C., & Roll, R. (1969). The adjustment of stock prices to new information. International Economic Review, 10(1), 1-2. https://doi.org/10.2307/2525569
Fenech, G. (2018). Bitcoin Cash Forks -- Mayhem On The Markets, Forbes, November 16
Kolari, J.W., & Pynnonen, S. (2008). Nonparametric rank test for event studies. 21st Australasian Finance and Banking Conference
Lee, D., & Chen, K. (2017). Handbook of digital currency – Bitcoin, Innovation, Financial Instruments, and Big Data. London, UK: Elsevier
Luoma, T. (2011). A Sign Test of Cumulative Abnormal Returns in Event Studies Based on Generalized Standardized Abnormal Returns. Wasa, Finland: Universitas Wasaensis
MacKinlay, A.C. (1997). Event Studies in Economics and Finance. Journal of Economic Literature, 35(1), 13-39. Retrieved from www.jstor.org/stable/2729691
Nakamoto, S. (2008) Bitcoin: A Peer-to-Peer Electronic Cash System, retireved from: http://bitcoin.org
Samitas, A.G., & Kenourgios, D.F. (2004) Market Efficiency and Signaling: An Event Study Analysis for Athens Stock Exchange, 1st Applied Financial Economics International Conference “Advances in Applied Financial Economics”, Samos island, Greece
Serra, A.P. (2002). EVENT STUDY TESTS - A brief survey. Working Papers da FEP no. 117
Williams-Grut, O. & Price, R. (2017). A Bitcoin civil war is threatening to tear the digital currency in 2 — here's what you need to know, Business Insider, July 2
https://coinmarketcap.com/all/views/all/ (retrieved March 20, 2020)
https://cointelegraph.com/news/the-cream-of-the-crypto-crop-10-best-performing-assets-in-2017 (retrieved March 20, 2020)