Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?
DOI:
https://doi.org/10.2478/saeb-2018-0013Keywords:
Bitcoin, cryptocurrencies, causality, Geweke feedback measures, generalized impulse responseAbstract
This paper investigates the information transmission between the most important cryptocurrencies - Bitcoin, Litecoin, Ripple, Ethereum and Bitcoin Cash. We use a VAR modelling approach, upon which the Geweke’s feedback measures and generalized impulse response functions are computed. This methodology allows us to fully characterize the direction, intensity and persistence of information flows between cryptocurrencies. At the available data granularity, most of information transmission is contemporaneous, that is, it occurs within a day. However, it seems that there are some lagged feedback effects, mainly from other cryptocurrencies to Bitcoin. The generalized impulse-response functions confirm that there is a strong contemporaneous correlation and that there is not much evidence of lagged effects. The exception appears to be related to the overreaction of Bitcoin returns to contemporaneous shocks.
JEL Codes - G10; G14; G15
References
Barber, S., Boyen, X., Shi, E., and Uzun, E., 2012. Bitter to Better -- How to Make Bitcoin a Better Currency. In A. Keromytis (Ed.), Financial Cryptography and Data Security, 7397 (pp. 399-414). Berlin, Heidelberg: Springer. doi:http://dx.doi.org/10.1007/978-3-642-32946-3_29
Bariviera, A. F., 2017. The Inefficiency of Bitcoin Revisited: A Dynamic Approach. Economics Letters, 161, 1-4. doi: http://dx.doi.org/10.1016/j.econlet.2017.09.013
Bariviera, A. F., Basgall, M. J., Hasperue, W., and Naiouf, M., 2017. Some Stylized Facts of the Bitcoin Market. Physica A, 484, 82-90. doi: http://dx.doi.org/10.1016/j.physa.2017.04.159
Baur, D. G., Hong, K., and Lee, A. D., 2018. Bitcoin: Medium of Exchange or Speculative Assets? Journal of International Financial Markets, Institutions and Money.
Böhme, R., Christin, N., Edelman, B., and Moore, T., 2015. Bitcoin: Economics, Technology, and Governance. The Journal of Economic Perspectives, 29(2), 213-238. doi: http://dx.doi.org/10.1257/jep.29.2.213
Bouoiyour, J., and Selmi, R., 2014. What Bitcoin Looks Like? . MPRA Working Paper, 58091.
Bouri, E., Azzi, G., and Dyhrberg, A. H., 2016. On the Return-volatility Relationship in the Bitcoin Market around the Price Crash of 2013. Kiel Institute for the World Economy, Economics Discussion Papers(2016-41).
Bradbury, D., 2013. The Problem with Bitcoin. Computer Fraud & Security, 2013(11), 5-8. doi: http://dx.doi.org/10.1016/S1361-3723(13)70101-5
Chaum, D., 1981. Untraceable Electronic Mail, Return Addresses, and Digital Pseudonyms. Communications of the ACM, 24(2), 84-90. doi: http://dx.doi.org/10.1145/358549.358563
Cheah, E. T., and Fry, J., 2015. Speculative Bubbles in Bitcoin Markets? An Empirical Investigation into the Fundamental Value of Bitcoin. Economics Letters, 130, 32-36. doi: http://dx.doi.org/10.1016/j.econlet.2015.02.029
Cheung, A., Roca, E., and Su, J. J., 2015. Crypto-currency Bubbles: An Application of the Phillips-Shi-Yu (2013) Methodology on Mt.Gox Bitcoin prices. Applied Economics, 47(23), 2348-2358. doi: http://dx.doi.org/10.1080/00036846.2015.1005827
Ciaian, P., Rajcaniova, M., and Kancs, d. A., 2016. The Economics of Bitcoin Price Formation. Applied Economics, 48(19), 1799-1815. doi: http://dx.doi.org/10.1080/00036846.2015.1109038
Ciaian, P., Rajcaniova, M., and Kancs, d. A., 2018. Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets. Journal of International Financial Markets, Institutions and Money, 52, 173-195. doi: http://dx.doi.org/10.1016/j.intfin.2017.11.001
Dastgir, S., Demir, E., Downing, G., Gozgor, G., and Lau, C. K. M., 2018. The Causal Relationship between Bitcoin Attention and Bitcoin Returns: Evidence from the Copula-based Granger Causality Test. Finance Research Letters. doi: http://dx.doi.org/10.1016/j.frl.2018.04.019
Dyhrberg, A. H., and Haubo, A., 2016. Bitcoin, Gold and the Dollar-- A GARCH Volatility Analysis. Finance Research Letters, 16(C), 85-92. doi: http://dx.doi.org/10.1016/j.frl.2015.10.008
Eyal, I., and Sirer, E. G., 2014. Majority is not Enough: Bitcoin Mining is Vulnerable. 436-454. doi: http://dx.doi.org/10.1007/978-3-662-45472-5_28
Fink, C., and Johann, T., 2014. Bitcoin Markets. SSRN. http://dx.doi.org/10.2139/ssrn.2408396.
Gandal, N., and Halaburda, H., 2014. Competition in the Cryptocurrency Market. CESifo Working Paper Series, 4980. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2506577.
Geweke, J., 1982. Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77(378), 304-313. doi: http://dx.doi.org/10.1080/01621459.1982.10477803
Gkillas, K., and Katsiampa, P., 2018. An Application of Extreme Value Theory to Cryptocurrencies. Economics Letters, 164, 109-111. doi: http://dx.doi.org/10.1016/j.econlet.2018.01.020
Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., and Siering, M., 2014. Bitcoin - Asset or Currency? Revealing users’ hidden intentions. Paper presented at the Twenty Second European Conference on Information Systems, Tel Aviv.
Guesmi, K., Saadi, S., Abid, I., and Ftiti, Z., 2018. Portfolio Diversification with Virtual Currency: Evidence from Bitcoin. International Review of Financial Analysis. doi: http://dx.doi.org/10.1016/j.irfa.2018.03.004
Jevons, W. S., 1896. Money and the Mechanism of Exchange. New York: D. Appleton and Company.
Karame, G. O., Androulaki, E., Roeschlin, M., Gervais, A., and Capkun, S., 2015. Misbehavior in Bitcoin: A Study of Double-Spending and Accountability. ACM Transactions on Information and System Security, 18(1), 2-32. doi: http://dx.doi.org/10.1145/2732196
Kim, Y. B., Kim, J. G., Kim, W., Im, J. H., Kim, T. H., Kang, S. J., and Kim, C. H., 2016. Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies. PLoS One, 11(8), e0161197. doi: http://dx.doi.org/10.1371/journal.pone.0161197
Kristoufek, L., 2013. BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era. Scientific Reports, 3(3415), 3415. doi: http://dx.doi.org/10.1038/srep03415
Kristoufek, L., 2015. What are the Main Drivers of the Bitcoin Price? : Evidence from Wavelet Coherence Analysis. doi:http://dx.doi.org/10.1371/journal.pone.0123923
Li, X., and Wang, C. A., 2017. The Technology and Economic Determinants of Cryptocurrency Exchange Rates: The Case of Bitcoin. Decision Support Systems, 95, 49-60. doi: http://dx.doi.org/10.1016/j.dss.2016.12.001
Nadarajah, S., and Chu, J., 2017. On the Inefficiency of Bitcoin. Economics Letters, 150, 6-9. doi: http://dx.doi.org/10.1016/j.econlet.2016.10.033
Nakamoto, S., 2008. Bitcoin: A Peer-to-Peer Electronic Cash System. from https://Bitcoin.org/Bitcoin.pdf
Neudecker, T., 2017. Bitcoin Cash (BCH) Sybil Nodes on the Bitcoin Peer-to-Peer Network. Germany: Institute of Telematics, Karlsruhe Institute of Technology.
Nolting, C., and Muller, M., 2017. CIO Insights Reflections: Cryptocurrencies and Blockchains - Their Importance in the Future". Deutsche Bank Research, Deutsche Oppenheim: Deutsche Bank AG.
Osterrieder, J., Strika, M., and Lorenz, J., 2017. Bitcoin and Cryptocurrencies - Not for the Faint-Hearted. International Finance and Banking, 4(1), 56-65. doi: http://dx.doi.org/10.5296/ifb.v4i1.10451
Pesaran, M. H., and Shin, Y., 1998. Generalized Impulse Response Analysis in Linear Multivariate Models. Economics Letters, 58(1), 17-29. doi: http://dx.doi.org/10.1016/S0165-1765(97)00214-0
Phillip, A., Chan, J. S. K., and Peiris, S., 2018. A New Look at Cryptocurrencies. Economics Letters, 163, 6-9. doi: http://dx.doi.org/10.1016/j.econlet.2017.11.020
Phillips, R. C., and Gorse, D., 2017. Predicting Cryptocurrency Price Bubbles Using Social Media Data and Epidemic Modelling. Paper presented at the Computational Intelligence (SSCI), 2017 IEEE Symposium Series. doi:http://dx.doi.org/10.1109/SSCI.2017.8280809
Phillips, R. C., and Gorse, D., 2018. Cryptocurrency price drivers: Wavelet coherence analysis revisited. PLoS One, 13(4), e0195200. doi: http://dx.doi.org/10.1371/journal.pone.0195200
Polasik, M., Piotrowska, A. I., Wisniewski, T. P., Kotkowski, R., and Lightfoot, G., 2015. Price Fluctuations and the Use of Bitcoin: An Empirical Inquiry. International Journal of Electronic Commerce, 20(1), 9-49.
Reid, F., and Harrigan, M., 2013. An Analysis of Anonymity in the Bitcoin System Security and Privacy in Social Networks (pp. 197-223): Springer. doi:http://dx.doi.org/10.1007/978-1-4614-4139-7_10
Ron, D., and Shamir, A., 2013. Quantitative Analysis of the Full Bitcoin Transaction Graph. In A. R. Sadeghi (Ed.), Financial Cryptography and Data Security. FC 2013. Lecture Notes in Computer Science (Vol. 7859, pp. 6-24). Berlin, Heidelberg: Springer. doi:http://dx.doi.org/10.1007/978-3-642-39884-1_2
Schwartz, D., Youngs, N., and Britto, A., 2014. The Ripple Protocol Consensus Algorithm. from https://Ripple.com/files/Ripple_consensus_whitepaper.pdf
Sebastiao, H., Duarte, A. P., and Guerreiro, G., 2017. Where is the Information on USD/Bitcoin Hourly Prices? Notas Económicas, 45(45), 7-25. doi: http://dx.doi.org/10.14195/2183-203X_45_1
Sovbetov, Y., 2018. Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero. Journal of Economics and Financial Analysis, 2(2), 1-27.
Tiwari, A. K., Jana, R. K., Das, D., and Roubaud, D., 2018. Informational Efficiency of Bitcoin - An Extension. Economics Letters, 163, 106-109. doi: http://dx.doi.org/10.1016/j.econlet.2017.12.006
Tu, K., and Meredith, M., 2015. Rethinking Virtual Currency Regulation in the Bitcoin Age. Washington Law Review (Seattle, Wash.), 90, 271-347.
Urquhart, A., 2016. The Inefficiency of Bitcoin. Economics Letters, 148, 80-82. doi: http://dx.doi.org/10.1016/j.econlet.2016.09.019
Vaddepalli, S., and Antoney, L., 2018. Are Economic Factors Driving Bitcoin Transactions? An Analysis of Select Economies. Finance Research Letters. doi: http://dx.doi.org/10.1016/j.frl.2018.04.002
Wei, W. C., 2018. Liquidity and Market Efficiency in Cryptocurrencies. Economics Letters, 168, 21-24. doi: http://dx.doi.org/10.1016/j.econlet.2018.04.003
Yermack, D., 2014. Is Bitcoin a Real Currency? An Economic Appraisal. NBER Working Paper, 19747.
Ziegeldorf, J. H., Matzutt, R., Henze, M., Grossmann, F., and Wehrle, K., 2018. Secure and Anonymous Decentralized Bitcoin Mixing. Future Generation Computer Systems, 80, 448-466. doi: http://dx.doi.org/10.1016/j.future.2016.05.018
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