Abstract
We study the relationship between Bitcoin trading volume, volatility, and returns using financial data for the period July 2010–November 2017. When we compare the raw annualized volatility of the Bitcoin exchange rate against common currencies, we observe that Bitcoin’s is higher. However, when the volume of Bitcoin transactions is considered, the volatility of the Bitcoin stabilizes significantly. Then we divide our sample into four distinct time periods, defined by three important events, namely, the loss of public confidence in the banking system in 2013, the MtGox Bitcoin Exchange hack in early 2014, and the introduction of the Bitcoin legislation in Japan in April 2017. Using asymmetric EGARCH models with the lag of the natural logarithm of the volume of the Bitcoin both as a regressor in the mean equation as well as in the specification of the conditional variance as multiplicative heteroskedasticity we show that volume and volatility are related after 2013, and volume and returns are related before the MtGox hack, positively and significantly. Further, during the euphoric period between the beginning of 2013 and up to the MtGox hack an unexpected rise in Bitcoin returns increases Bitcoin volatility more than an unexpected, equally sized decrease (asymmetry).
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Notes
- 1.
During the first quarter of 2014 the exchange rate of Bitcoin had decreased to $298.73 from $1,128.47 since November 2013. Adverse events such as the closing of the Mount Gox Exchange and the negative outlook from the Chinese government have all played a role in damaging the performance of Bitcoin.
- 2.
The data for the Bitcoin exchange rate as well as the exchange rate of all other currencies was used from the Federal Reserve, www.quandl.com and www.oanda.com. Volume data is available from the 14th of September 2011.
- 3.
Assuming that there are 252 trading days in the year.
- 4.
References
Amihud, Y.: Illiquidity and stock returns: cross-section and time-series effects. J. Financ. Mark. 5(1), 31–56 (2002)
Amihud, Y., Mendelson, H.: Liquidity and stock returns. Financ. Anal. J. 42(3), 43–48 (1986)
Balcilar, M., Bouri, E., Gupta, R., Roubaud, D.: Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Econ. Model. 64, 74–81 (2017)
Baur, D.G., Dimpfl, T.: Excess volatility as an impediment for a digital currency (2018)
Baur, D.G., Glover, K.: A gold bubble? (No. 175) (2012)
Bollerslev, T., Kretschmer, U., Pigorsch, C., Tauchen, G.: A discrete-time model for daily S and P500 returns and realized variations: jumps and leverage effects. J. Econ. 150(2), 151–166 (2009)
Bouri, E., Azzi, G., Dyhrberg, A.H.: On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Econ.-Open-Access Open-Assess. E-J. 11, 1–16 (2017)
Carroll, R., Kearney, C.: Do trading volumes explain the persistence of GARCH effects? Appl. Financ. Econ. 22, 1993–2008 (2012). https://doi.org/10.1080/09603107.2012.692871
Cermak, V.: Can Bitcoin become a viable alternative to fiat currencies? An empirical analysis of Bitcoin’s volatility based on a GARCH model (2017)
European Central Bank (ECB): Virtual Schemes (2012). www.ecb.int/pub/pdf/other/virtualcurrencyschemes201210en.pdf
Gervais, S., Kaniel, R., Mingelgrin, D.H.: The high-volume return premium. J. Financ. 56(3), 877–919 (2001)
Ghysels, E., Santa-Clara, P., Valkanov, R.: There is a risk-return trade- off after all. J. Financ. Econ. 76(3), 509–548 (2005)
Glosten, L.R., Jagannathan, R., Runkle, D.E.: On the relation between the expected value and the volatility of the nominal excess return on stocks. J. Financ. 48, 1779–1801 (1993)
Harrison, P., Zhang, H.H.: An investigation of the risk and return relation at long horizons. Rev. Econ. Stat. 81(3), 399–408 (1999)
Judge, G.G., Griffiths, W.E., Hill, R.C., Lutkepohl, H., Lee, T.C.: The Theory and Practice of Econometrics, 2nd edn. Wiley, New York (1985)
Karpoff, J.M.: The relation between price changes and trading volume: a survey. J. Financ. Quant. Anal. 22, 109–126 (1987). https://doi.org/10.2307/2330874
Kasper, D.: Evolution of Bitcoin-volatility comparisons with least developed countries’ currencies (2017)
Khairuddin, I.E., Sas, C., Clinch, S., Davies, N.: Exploring motivations for Bitcoin technology usage. In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2872–2878. ACM, May 2016
Koutmos, G., Booth, G.G.: Asymmetric volatility transmission in international stock markets. J. Int. Money Financ. 14, 747–762 (1995)
Li, J., Wu, C.: Stochastic volatility, liquidity and intraday information flow. Appl. Econ. Lett. 18(16), 1511–1515 (2011). https://doi.org/10.1080/13504851.2010.543077
Liu, W.: A liquidity-augmented capital asset pricing model. J. Financ. Econ. 82, 631–671 (2006)
Ludvigson, S.C., Ng, S.: The empirical risk–return relation: a factor analysis approach. J. Financ. Econ. 83(1), 171–222 (2007)
Miller, E.M.: Risk, uncertainty, and divergence of opinion. J. Financ. 32(4), 1151–1168 (1977)
Nam, K., Pyun, C.S., Avard, S.L.: Asymmetric reverting behavior of short-horizon stock returns: an evidence of stock market overreaction. J. Bank. Financ. 25(4), 807–824 (2001)
Nelson, D.B.: Conditional heteroskedasticity in asset returns: a new approach. Econometrica 59, 347–370 (1991)
O’Hara, M.: Market Microstructure Theory. Blackwell, Cambridge (1995)
Parker, J.C., Li, C.H.: How Bad is Bad News; How Good is Good News? Bank of Canada (2006)
Schwert, G.W.: Stock market volatility. Financ. Anal. J. 46(3), 23–34 (1990)
Wallace, B.: The rise and fall of Bitcoin. Wired, 23 November (2011)
Wu, L.: Reverse return-volatility asymmetry, and short sale constraints: evidence from the Chinese markets. Presented at the EFMA Annual Meeting 2017 (2017)
Yermack, D.: Is Bitcoin a real currency? An economic appraisal. In: Handbook of Digital Currency, pp. 31–43 (2015)
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Kokkinaki, A., Sapuric, S., Georgiou, I. (2019). The Relationship Between Bitcoin Trading Volume, Volatility, and Returns: A Study of Four Seasons. In: Themistocleous, M., Rupino da Cunha, P. (eds) Information Systems. EMCIS 2018. Lecture Notes in Business Information Processing, vol 341. Springer, Cham. https://doi.org/10.1007/978-3-030-11395-7_1
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