A comparative analysis of the volatility nature of cryptocurrency and JSE market
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DOIhttp://dx.doi.org/10.21511/imfi.19(4).2022.03
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Article InfoVolume 19 2022, Issue #4, pp. 23-39
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Despite the rapid growth of developing markets, aided by globalization, comparative studies of cryptocurrency and stock market volatility have focused on the developed markets and neglected developing ones. In this regard, this study compares cryptocurrency volatility with that of the Johannesburg Stock Exchange (JSE), a developing market. GARCH-type models are applied to daily log returns of Bitcoin, Ethereum, and the FTSE/JSE 4O in two ways. Firstly, the models are applied directly; secondly, structural breaks are tested and accounted for in the models. The sample period was from September 18, 2017, to May 27, 2021. The results show higher volatility and higher volatility persistence in cryptocurrency than in the JSE market. They also show that persistence is overestimated for cryptocurrencies when structural breaks are not accounted for. The opposite was true for the JSE.
Moreover, the two cryptocurrencies were found to have close to identical volatility plots that differ from that of the JSE. High volatility periods of cryptocurrency also did not coincide with that of JSE and those of JSE did not coincide with the cryptocurrency ones. There is also evidence of an inverse leverage effect in cryptocurrency, which opposes the normal leverage effect of the JSE market.
- Keywords
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JEL Classification (Paper profile tab)C22, C58, G11, G15
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References59
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Tables6
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Figures7
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- Figure 1. Daily log returns
- Figure 2. ACF plots of returns and squared returns
- Figure 3. Daily log returns
- Figure 4. QQ plots and ACF plots for the standardized residuals
- Figure 5. Volatility plots with Bitcoin atop followed by Ethereum and lastly JSE
- Figure 6. Structural breakpoints as identified by the PELT method
- Figure 7. QQ plots and ACF plots for residuals for models with structural breaks
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- Table 1. Descriptive statistics of daily log-returns Bitcoin, Ethereum, Dogecoin, and JSE
- Table 2. Stationarity tests for the returns
- Table 3. Model selection
- Table 4. Parameter estimates for the selected models
- Table 5. Breakpoints identified in the return series
- Table 6. Parameter estimates for models with structural breaks
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- Akyildirim, E., Corbet, S., Lucey, B., Sensoy, A., & Yarovaya, L. (2020). The relationship between implied volatility and cryptocurrency returns. Finance Research Letters, 33, 101212.
- Aloosh, A., & Ouzan, S. (2020). The psychology of cryptocurrency prices. Finance Research Letters, 33, 101192.
- Baur, D. G., & Dimpfl, T. (2018). Asymmetric volatility in cryptocurrencies. Economics Letters, 173, 148-151.
- Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177-189.
- Bauwens, L., Hafner, C. M., & Laurent, S. (2012). Handbook of volatility models and their applications. John Wiley and Sons.
- Blau, B. M. (2017). Price dynamics and speculative trading in bitcoin. Research in International Business and Finance, 41, 493-499.
- Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327.
- Bouri, E., Azzi, G., & Dyhrberg, A. H. (2017a). On the return-volatility relationship in the bitcoin market around the price crash of 2013. Economics, 11(1), 1-16.
- Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017b). On the hedge and safe haven properties of bitcoin: Is it really more than a diversifier? Finance Research Letters, 20, 192-198.
- Brauneis, A., & Mestel, R. (2018). Price discovery of cryptocurrencies: Bitcoin and beyond. Economics Letters, 165, 58-61.
- Caporin, M., & Costola, M. (2019). Asymmetry and leverage in GARCH models: A news impact curve perspective. Applied Economics, 51(31), 3345-3364.
- Catania, L., & Grassi, S. (2021). Forecasting cryptocurrency volatility. International Journal of Forecasting, 38(3), 878-894.
- Charles, A., & Darné, O. (2019). Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks. Economics Bulletin, 39(2), 954-968.
- Chatzikonstanti, V. (2017). Breaks and outliers when modelling the volatility of the US stock market. Applied Economics, 49(46), 4704-4717.
- Cheah, E.-T., & Fry, J. (2015). Speculative bubbles in bitcoin markets? An empirical investigation into the fundamental value of bitcoin. Economics Letters, 130, 32-36.
- Corbet, S., Lucey, B., Peat, M., & Vigne, S. (2018). Bitcoin futures – What use are they? Economics Letters, 172, 23-27.
- Cubbin, E., Eidne, M., Firer, C., & Gilbert, E. (2006). Mean reversion on the JSE. Investment Analysts Journal, 35(63), 39-47.
- Dasman, S. (2021). Analysis of return and risk of cryptocurrency bitcoin asset as investment instrument. Accounting and Finance Innovations.
- Diebold, F. X. (1986). Modeling the persistence of conditional variances: a comment. Econometric Reviews, 5(1), 51-56.
- Dowd, K. (2014). New private monies: a bit-part player? (Hobart Paper 174). Institute of Economic Affairs Monographs.
- Duffee, G. R. (2002). Balance sheet explanations for asymmetric volatility. University of California at Berkeley.
- Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation. Econometrica, 50(4), 987-1007.
- Engle, R. F., & Patton, A. J. (2007). What good is a volatility model? In Forecasting volatility in the financial markets (pp. 47-63). Elsevier.
- Fama, E. F. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of financial economics, 49(3), 283-306.
- Gbenro, N., & Moussa, R. K. (2019). Asymmetric mean reversion in low liquid markets: Evidence from BRVM. Journal of Risk and Financial Management, 12(1), 38.
- Ghoddusi, H., Morovati, M., & Rafizadeh, N. (2020). Asymmetric bitcoin volatility under structural breaks. SSRN Electronic Journal.
- Gil-Alana, L. A., Abakah, E. J. A., & Rojo, M. F. R. (2020). Cryptocurrencies and stock market indices. Are they related? Research in International Business and Finance, 51, 101063.
- Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). Bitcoin-asset or currency? Revealing users’ hidden intentions. SSRN Electronic Journal.
- Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779-1801.
- Hu, A. S., Parlour, C. A., & Rajan, U. (2019). Cryptocurrencies: Stylized facts on a new investible instrument. Financial Management, 48(4), 1049-1068.
- Huang, J.-Z., Ni, J., & Xu, L. (2022). Leverage effect in cryptocurrency markets. Pacific-Basin Finance Journal, 73, 101773.
- Investing. (n.d.). Main Page.
- John, A., Logubayom, A. I., & Nero, R. (2019). Half-life volatility measure of the returns of some cryptocurrencies. Journal of Financial Risk Management, 8(1), 15-28.
- Kaseke, F., Ramroop, S., & Mhwambi, H. (2021). A comparison of the stylized facts of bitcoin, ethereum and the JSE stock returns. African Finance Journal, 23(2), 50-64.
- Katsiampa, P., Corbet, S., & Lucey, B. (2019). Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis. Finance Research Letters, 29, 68-74.
- Killick, R., & Eckley, I. (2014). Changepoint: An r package for changepoint analysis. Journal of statistical software, 58(3), 1-19.
- Kim, J.-M., Jun, C., & Lee, J. (2021). Forecasting the volatility of the cryptocurrency market by GARCH and stochastic volatility. Mathematics, 9(14), 1614.
- Klein, T., Thu, H. P., & Walther, T. (2018). Bitcoin is not the new gold – a comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105-116.
- Kwon, J. H. (2020). Tail behavior of bitcoin, the dollar, gold and the stock market index. Journal of International Financial Markets, Institutions and Money, 67, 101202.
- Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. Journal of Business and Economic Statistics, 8(2), 225-234.
- Latif, S. R., Mohd, M. A., Amin, M. N. M., & Mohamad, A. I. (2017). Testing the weak form of efficient market in cryptocurrency. Journal of Engineering and Applied Sciences, 12(9), 2285-2288.
- LeBaron, B. (1992). Some relations between volatility and serial correlations in stock market returns. Journal of Business, 65(2), 199-219.
- Liang, J., Li, L., Chen, W., & Zeng, D. (2019). Towards an understanding of cryptocurrency: a comparative analysis of cryptocurrency, foreign exchange, and stock. 2019 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 137-139).
- López-Cabarcos, M., Pérez-Pico, A., Pineiro-Chousa, J., & Ševic, A. (2021). Bitcoin volatility, stock market and investor sentiment. Are they connected? Finance Research Letters, 38, 101399.
- Mariana, C. D., Ekaputra, I. A., & Husodo, Z. A. (2021). Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic? Finance Research Letters, 38, 101798.
- Mensi, W., Al-Yahyaee, K. H., & Kang, S. H. (2019). Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum. Finance Research Letters, 29, 222-230.
- Mert, U., & Demireli, E. (2020). Asymmetric GARCH-type and half-life volatility modelling of USD/KZT exchange rate returns. Eurasian Research Journal, 2(2), 7-18.
- Muguto, L., & Muzindutsi, P.-F. (2022). A comparative analysis of the nature of stock return volatility in BRICS and G7 markets. Journal of Risk and Financial Management, 15(2), 85.
- Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review.
- Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347-370.
- Pavlov, A. (2022, November 25). Momentum vs mean reversion in crypto [Tweet].
- Quigley, L., & Ramsey, D. (2008). Statistical analysis of the log returns of financial assets. University of Limerick.
- Selmi, R., Mensi, W., Hammoudeh, S., & Bouoiyour, J. (2018). Is bitcoin a hedge, a safe haven or a diversifier for oil price movements? A comparison with gold. Energy Economics, 74, 787-801.
- Smith Jr, C. W. (1988). Market volatility: Causes and consequences. Cornell Law Review, 74(5), 953-962.
- Tsay, R. S. (2014). An introduction to analysis of financial data with R. John Wiley and Sons.
- Uzonwanne, G. (2021). Volatility and return spillovers between stock markets and cryptocurrencies. The Quarterly Review of Economics and Finance, 82, 30-36.
- Zaremba, A., Bilgin, M. H., Long, H., Mercik, A., & Szczygielski, J. J. (2021). Up or down? Short-term reversal, momentum, and liquidity effects in cryptocurrency markets. International Review of Financial Analysis, 78, 101908.
- Zhang, C., Ma, H., Arkorful, G. B., & Peng, Z. (2021). The impacts of futures introduction on spot market volatility: Evidence from the bitcoin market. SSRN Electronic Journal.
- Zhang, W., Wang, P., Li, X., & Shen, D. (2018). Some stylized facts of the cryptocurrency market. Applied Economics, 50(55), 5950-5965.