EXAMINING THE RELATIONSHIP BETWEEN BITCOIN AND ALTCOINS

Year 2023, Volume: 18 Issue: 1, 92 - 94, 15.01.2024

Esra Aksoylu

https://doi.org/10.17261/Pressacademia.2023.1864

Abstract

Purpose- The purpose of this study is to examine the long and short-term relationship between Bitcoin and altcoins selected based on their market capitalization through an empirical analysis. For this purpose, the daily data of Bitcoin and nine altcoins consisting of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin for the period 07/08/2015-08/01/2020 were used.
Methodology- The long-run relationship between Bitcoin and altcoins is first analyzed by Vector Autoregression (VAR) analysis. Granger causality test was utilized to determine the short-run causality relationship between the variables. The tests were conducted with the Eviews program.
Findings- According to the results of the VAR analysis conducted to investigate the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. After determining the long-run relationship between the variables, the relationships between the variables were analyzed with the help of impulse response functions. Impulse response function shows the effect of a one-unit shock to one variable on the other variable. Accordingly, when the results of impulse response functions are analyzed; it is seen that a one-unit random shock in Bitcoin has a negative effect on Ripple, Nem, Litecoin, Dash, Litecoin, Dogecoin in the first two periods, the effect decreases in the second period, and this effect disappears in the third period. A random shock to Bitcoin causes a positive effect on Stellar that lasts for two periods. This positive effect ends in the third period. After analyzing the relationship between Bitcoin and altcoins with impulse response functions, the source of the changes in the variance of the variables is analyzed through variance decomposition. According to the variance decomposition results, the effect of Bitcoin on Dogecoin is 25% in the first period and 22% in the other periods. The variance decomposition of Dash shows that approximately 18% of the change in standard deviation was caused by Bitcoin in the first period and this percentage increased to 25.5% in the following periods. Litecoin's variance decomposition results show that 33% of the change in standard deviation from the first period to the last period was caused by Bitcoin. It is observed that approximately 8% of the change in Nem's standard deviation in the first period was caused by Bitcoin, while this rate increased to 21.5% in the last period. From the first period to the last period, 13.5% of the change in Stellar's standard deviation was caused by Bitcoin. When the variance decomposition of Ripple is analyzed, it is observed that 10% of the difference in the standard deviation is due to Bitcoin. This situation continued similarly from the first period to the last period. Following the VAR analysis, Granger causality test was conducted to explain the short-term relationship between the variables. According to the test results, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. When the Granger causality relationship between altcoins is analyzed, a causality relationship was observed from Tether to Stellar, while no causality was found from Stellar to Tether. Similarly, while Granger causality is observed from Tether to Ripple, there is no causality from Ripple to Tether. The variance decomposition of Stellar and Ripple shows that Tether does not contribute to the change in standard deviation. The variance decomposition test supports the Granger test results. All altcoin variables except these are Granger causes of each other.
Conclusion- At the end of the study, according to the results of the VAR analysis to determine the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. There is no long-run relationship between Tether, Monero, Ether and Bitcoin. According to the Granger causality analysis test results conducted to observe the short-term relationship, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. As a result, it is observed that Bitcoin has a short-term relationship with all 9 altcoins subject to the study, and a long-term relationship with Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple. These results show that the price movements in Bitcoin have an impact on altcoins.

Keywords

Bitcoin, altcoin, cryptocurrency, causality analysis, VAR analysis

References

• Akaike, H. (1978). On the likelihood of a time series model. The Statistician, 217-235.
• Akçalı, B., Y., & Şişmanoğlu, E. (2019). Kripto para birimleri arasındaki ilişkinin Toda-Yamamoto nedensellik testi ile analizi. Ekev Akademi Dergisi, 23(78), 99-122.
• Ay, M., & Adıyaman, G. (2022). Bitcoin ve altcoinler arasındaki ilişkinin incelenmesi. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 47, 31-46. https://doi.org/10.52642/susbed.1010149
• Çağlı, E.Ç. (2019). Explosive behavior in the prices of bitcoin and altcoins. Finance Research Letters, 29, 398-403.
• Ciaian, P., & Rajcaniova, M. (2018). Virtual relationships: short-and long-run evidence from bitcoin and altcoin markets. Journal of International Financial Markets, Institutions and Money, 52, 173-195.
• Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
• Granger, C. ve Newbold, P. (1974). Spurious Regression in Econometrics. Journal of Econometrics, 2, 111-120.
• Granger, C.W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 424-438.
• Gujaratı, D; (1999), Basic Econometrics, Forth Edition. McGroww,Hill.
• Kim, M. J., Canh, N. Phuc & Park, S. Y. (2020). Causal relationship among cryptocurrencies: a conditional quantile approach. Finance Research Letters, 1544-6123.
• Kubar, Y., & Toprak, Y. (2021). Bitcoin ve altcoin’ler arasındaki ilişkinin Granger nedensellik testi ile analizi. JOEEP: Journal of Emerging Economies and Policy, 6(1), 233-247.
• Philips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrica, 75(2), 335-346.
• Silva, W. A., Martins, N. C., Miranda, I. d., Penha, R. S., & Reina, D. (2020). Cryptocurrencies And Finance: The Relationship Between The Return Of Bitcoin And The Main Digital Currencies. Revista de Administração da Universidade Federal de Santa Maria, 13(2)., 88-97.
• Sims, C. A. (1972). Money, income, and causality. The American Economic Review, 540-552.
• Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 1-48.
• Vardar, G., Taçoğlu, C. ve Aydoğan B. (2022). Quantifying return and volatility spillovers among major cryptocurrencies: A VAR-BEKK-GARCH Analysis. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 17(3), 911 – 933.
• www.coinmarket.com