Research on properties of Bitcoin Based on GARCH model
DOI:
https://doi.org/10.54097/hset.v44i.7314Keywords:
Bitcoin, Cryptocurrencies, GARCH, Price fluctuations, Logarithmic rate of return.Abstract
Cryptocurrencies have become a world-class phenomenon, with governments, companies and investors facing huge challenges and opportunities. Bitcoin is the one of most widely known cryptocurrencies. People prefer to use Bitcoin as an asset to invest for profit and hedge risk than for its payment function. This is the reason for the study of bitcoin market is so important. Many scholars had used daily data on bitcoin to construct different GARCH models to analyse the volatility of its returns. This research builds a GARCH model for the logarithmic return series of the bitcoin price to understand the volatility of the bitcoin price over the experimental time horizon. The experimental results show that the price of bitcoin is more volatile and vulnerable to external shocks. The analysis suggests that Bitcoin is more clearly a speculative financial instrument and that the price of Bitcoin is highly frothy.
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References
R. F. Engle, Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, vol. 50, 1982, pp. 987–1007. DOI:10.2307/1912773.
D. G. Baura, K. Hong, A. D. Lee, Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money. vol. 54, 2018, pp.177–189. DOI:10.1016/j.intfin.2017.12.004.
T. Bollerslev, E. Ghysels, Periodic Autoregressive Conditional Heteroscedasticity, Journal of Business & Economic Statistics, vol. 14 , 2016, pp.139–150.
A. H. Aarhus, M. Peter, D. Erik, What can explain the price, volatility and trading volume of Bitcoin? Finance Research Letters, vol. 29, 2019, pp. 255–265. DOI:10.1016/j.frl.2018.08.010.
A. Urquhart, The inefficiency of Bitcoin, Economics Letters, vol. 148, 2016, pp. 80–82. DOI:10.1016/j.econlet.2016.09.019.
E. Bouri, A. H. Dyhrberg, On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics: The OpenAccess, Open-Assessment E-Journal, vol. 11, 2017, pp. 1–17. DOI:10.5018/economics-ejournal.ja.2017-2.
C. Conrad, A. Custovic, E. Ghysels, Long-and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis, Journal of Risk and Financial Management, vol.11, 2018, pp.1–12. DOI:10.3390/jrfm11020023.
J. Chu, S. Chan, S. Nadarajah, GARCH Modelling of Cryptocurrencies, Journal of Risk and Financial Management, vol.10, 2017, pp.17-25. DOI :10.3390/jrfm10040017.
S. Corbet, B. M. Lucey, L. Yarovaya, Cryptocurrencies as a financial asset: A systematic analysis, International Review of Financial Analysis, 2018. DOI:10.1016/j.irfa.2018.09.003.
L. Catania, S. Grassi, Modelling Crypto-Currencies Financial Time-Series. 2017, DOI:10.2139/ssrn.3028486.
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