An Investigative Analysis of Volatility in the Cryptocurrency Market
DOI:
https://doi.org/10.48112/tibss.v1i3.652Abstract
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The growing global fascination with cryptocurrencies has sparked heightened interest, driven by their pronounced market volatility. This particular study endeavors to assess the risk and rewards associated with four prominent cryptocurrencies, while also delving into an examination of their interrelationships and fluctuation patterns. The investigation is based on daily closing prices spanning from January 1, 2017, to June 30, 2022. To unravel the spillover and asymmetrical repercussions of volatility, we employ various models from the GARCH family, most notably the DCC GARCH and EGARCH models. In addition, Granger causality is harnessed to uncover any causal connections among these digital assets. The findings underscore a noteworthy spillover phenomenon between Bitcoin and Ethereum, the two foremost cryptocurrencies boasting the maximum market capitalization. This spillover effect manifests as symmetric volatility impacts, setting them apart from Litecoin and RIPPLE.
Keywords:
Bitcoin, Cryptocurrency, Ethereum, Litecoin, RIPPLE, VolatilityReferences
Baur, D. G. (2012). Asymmetric volatility in the gold market. The Journal of Alternative Investments, 14(4), 26-38. https://doi.org/10.3905/jai.2012.14.4.026
Baur, D. G., & Dimpfl, T. (2018). Asymmetric volatility in cryptocurrencies. Economics Letters, 173, 148-151. https://doi.org/10.1016/j.econlet.2018.10.008
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
Brooks, C., & Rew, A. G. (2002). Testing for a unit root in a process exhibiting a structural break in the presence of GARCH errors. Computational Economics, 20, 157-176. https://doi.org/10.1023/A:1020945428824
Brooks, C., Henry, O. T., & Persand, G. (2002). The effect of asymmetries on optimal hedge ratios. The Journal of Business, 75(2), 333-352. https://doi.org/10.1086/338484
Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208
Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). GARCH modelling of cryptocurrencies. Journal of Risk and Financial Management, 10(4), 17. https://doi.org/10.3390/jrfm10040017
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. https://doi.org/10.1016/j.intfin.2017.11.001
Ciaian, P., Rajcaniova, M., & Kancs, D. A. (2016). The economics of BitCoin price formation. Applied economics, 48(19), 1799-1815. https://doi.org/10.1080/00036846.2015.1109038
Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics Letters, 165, 28-34. https://doi.org/10.1016/j.econlet.2018.01.004
Engle, R. (2001). GARCH 101: The use of ARCH/GARCH models in applied econometrics. Journal of Economic Perspectives, 15(4), 157-168. https://doi.org/10.1257/jep.15.4.157
Engle, R. F., Lilien, D. M., & Robins, R. P. (1987). Estimating time varying risk premia in the term structure: The ARCH-M model. Econometrica: journal of the Econometric Society, 391-407. https://doi.org/10.2307/1913242
Fry, J., & Cheah, E. T. (2016). Negative bubbles and shocks in cryptocurrency markets. International Review of Financial Analysis, 47, 343-352. https://doi.org/10.1016/j.irfa.2016.02.008
Gupta, H., Chaudhary, R., Srivastava, K., & Gupta, S. (2022). Volatility modelling of asset classes: An empirical study during different phases of COVID-19. Academy of Accounting and Financial Studies Journal, 26, 1-19.
Härdle, W. K., Harvey, C. R., & Reule, R. C. (2020). Understanding cryptocurrencies. Journal of Financial Econometrics, 18(2), 181-208. https://doi.org/10.1093/jjfinec/nbz033
Horpestad, J. B., Lyócsa, Š., Molnár, P., & Olsen, T. B. (2019). Asymmetric volatility in equity markets around the world. The North American Journal of Economics and Finance, 48, 540-554. https://doi.org/10.1016/j.najef.2018.07.011
Ji, Q., Bouri, E., Lau, C. K. M., & Roubaud, D. (2019). Dynamic connectedness and integration in cryptocurrency markets. International Review of Financial Analysis, 63, 257-272. https://doi.org/10.1016/j.irfa.2018.12.002
Lahajnar, S., & Rozanec, A. (2020). The correlation strength of the most important cryptocurrencies in the bull and bear market. Investment Management and Financial Innovations, 17(3), 67-81. http://dx.doi.org/10.21511/imfi.17(3).2020.06
Ljung, G. M., & Box, G. E. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303. https://doi.org/10.1093/biomet/65.2.297
Phillip, A., Chan, J. S., & Peiris, S. (2018). A new look at cryptocurrencies. Economics Letters, 163, 6-9. https://doi.org/10.1016/j.econlet.2017.11.020
Rastogi, S. (2014). The financial crisis of 2008 and stock market volatility–analysis and impact on emerging economies pre and post crisis. Afro-Asian Journal of Finance and Accounting, 4(4), 443-459. https://doi.org/10.1504/AAJFA.2014.067017
Shahzad, S. J. H., Bouri, E., Roubaud, D., & Kristoufek, L. (2020). Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin. Economic Modelling, 87, 212-224. https://doi.org/10.1016/j.econmod.2019.07.023
Shahzad, S. J. H., Bouri, E., Roubaud, D., Kristoufek, L., & Lucey, B. (2019). Is Bitcoin a better safe-haven investment than gold and commodities?. International Review of Financial Analysis, 63, 322-330. https://doi.org/10.1016/j.irfa.2019.01.002
Stavroyiannis, S. (2018). A note on the Nelson-Cao inequality constraints in the GJR-GARCH model: is there a leverage effect?. International Journal of Economics and Business Research, 16(4), 442-452. https://doi.org/10.1504/IJEBR.2018.095345
Yan, K., Yan, H., & Gupta, R. (2022). Are GARCH and DCC values of 10 cryptocurrencies affected by COVID-19?. Journal of Risk and Financial Management, 15(3), 113. https://doi.org/10.3390/jrfm15030113
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