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Empirical Evidence of the Relationships Between Bitcoin and Stock Exchanges: Case of Return and Volatility Spillover

  • M. KamisliEmail author
  • S. Kamisli
  • F. Temizel
Chapter
Part of the Contributions to Economics book series (CE)

Abstract

Especially with the sharp increase in the trading volume of Bitcoin, researchers have focused on the topic of cryptocurrencies. Besides the high risks they carry, these vehicles give investors the opportunity of gaining high returns. For this reason, many investors consider cryptocurrencies as an investment vehicle and include them into their portfolios, notably Bitcoin. Bitcoin is a new alternative for investors who desire to invest in different assets besides traditional ones. This new investment vehicle is also used for portfolio diversification. But, to provide the desired benefits, the relationships between the bitcoin and asset or assets that will be included in the portfolio. Therefore, the purpose of this study is to analyze the return and volatility relationships between Bitcoin and stock markets from different regions. For this purpose, Diebold and Yilmaz spillover test are applied to the return series. The empirical results indicate both return and volatility spillovers between the Bitcoin and the selected stock markets that should be considered in portfolio and risk management processes.

References

  1. Andrianto, Y., & Diputra, Y. (2017). The effect of cryptocurrency on investment portfolio effectiveness. Journal of Finance and Accounting, 5(6), 229–238.  https://doi.org/10.11648/j.jfa.20170506.14 CrossRefGoogle Scholar
  2. Antonakakis, N. (2012). Exchange return co-movements and volatility spillovers before and after the introduction of euro. Journal of International Financial Markets, Institutions and Money, 22(5), 1091–1109.  https://doi.org/10.1016/j.intfin.2012.05.009 CrossRefGoogle Scholar
  3. Awartani, B., Maghyereh, A. I., & Al Shiab, M. (2013). Directional spillovers from the US and the Saudi market to equities in the Gulf Cooperation Council countries. Journal of International Financial Markets, Institutions and Money, 27, 224–242.  https://doi.org/10.1016/j.intfin.2013.08.002 CrossRefGoogle Scholar
  4. Baek, C., & Elbeck, M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 22(1), 30–34.  https://doi.org/10.1080/13504851.2014.916379 CrossRefGoogle Scholar
  5. Bariviera, A. F. (2017). The inefficiency of Bitcoin revisited: A dynamic approach. Economics Letters, 161, 1–4.  https://doi.org/10.1016/j.econlet.2017.09.013 CrossRefGoogle Scholar
  6. Bariviera, A. F., Basgall, M. J., Hasperué, W., & Naiouf, M. (2017). Some stylized facts of the Bitcoin market. Physica A: Statistical Mechanics and its Applications, 484, 82–90.  https://doi.org/10.1016/j.physa.2017.04.159 CrossRefGoogle Scholar
  7. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.  https://doi.org/10.1016/0304-4076(86)90063-1 CrossRefGoogle Scholar
  8. Bouoiyour, J., & Selmi, R. (2016). Bitcoin: A beginning of a new phase. Economics Bulletin, 36(3), 1430–1440.Google Scholar
  9. Bouoiyour, J., Selmi, R., Tiwari, A. K., & Olayeni, O. R. (2016). What drives Bitcoin price? Economics Bulletin, 36(2), 843–850.Google Scholar
  10. Bouri, E., Azzi, G., & Dyhrberg, H. (2017). On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics-The Open-Access, Open-Assessment E-Journal, 11, 1–16.  https://doi.org/10.5018/economics-ejournal.ja.2017-2 CrossRefGoogle Scholar
  11. Bouri, E., Gupta, R., Tiwari, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87–95.  https://doi.org/10.1016/j.frl.2017.02.009 CrossRefGoogle Scholar
  12. Carpenter, A. (2016). Portfolio diversification with Bitcoin. Journal of Undergraduate Research in Finance, 6(1), 1–27.Google Scholar
  13. Chan, W. H., Le, M., & Wu, Y. W. (2019). Holding Bitcoin longer: The dynamic hedging abilities of Bitcoin. The Quarterly Review of Economics and Finance, 71, 107–113.  https://doi.org/10.1016/j.qref.2018.07.004 CrossRefGoogle Scholar
  14. 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.  https://doi.org/10.1016/j.econlet.2015.02.029 CrossRefGoogle Scholar
  15. Cheung, A., Roca, E., & 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.  https://doi.org/10.1080/00036846.2015.1005827 CrossRefGoogle Scholar
  16. Chevallier, J., & Ielpo, F. (2013). Volatility spillovers in commodity markets. Applied Economics Letters, 20(13), 1211–1227.  https://doi.org/10.1080/13504851.2013.799748 CrossRefGoogle Scholar
  17. 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 CrossRefGoogle Scholar
  18. Corbet, S., Lucey, B., & Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81–88.  https://doi.org/10.1016/j.frl.2017.12.006 CrossRefGoogle Scholar
  19. Cronin, D. (2014). The interaction between money and asset markets: A spillover index approach. Journal of Macroeconomics, 39, 185–202.  https://doi.org/10.1016/j.jmacro.2013.09.006 CrossRefGoogle Scholar
  20. Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158–171.  https://doi.org/10.1111/j.1468-0297.2008.02208.x CrossRefGoogle Scholar
  21. Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66.  https://doi.org/10.1016/j.ijforecast.2011.02.006 CrossRefGoogle Scholar
  22. Dyhrberg, A. H. (2016). Hedging capabilities of bitcoin. Is it the virtual gold? Finance Research Letters, 16, 139–144.  https://doi.org/10.1016/j.frl.2015.10.025 CrossRefGoogle Scholar
  23. Engle, R. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 391–407.  https://doi.org/10.2307/1912773 CrossRefGoogle Scholar
  24. 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 CrossRefGoogle Scholar
  25. Hameed, S., & Farooq, S. (2016). The art of crypto currencies: A comprehensive analysis of popular crypto currencies. International Journal of Advanced Computer Science and Applications, 7(12), 426–435.  https://doi.org/10.14569/IJACSA.2016.071255 CrossRefGoogle Scholar
  26. Kajtazi, A., & Moro, A. (2018). The role of bitcoin in well diversified portfolios: A comparative global study. International Review of Financial Analysis.  https://doi.org/10.1016/j.irfa.2018.10.003 CrossRefGoogle Scholar
  27. Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3–6.  https://doi.org/10.1016/j.econlet.2017.06.023 CrossRefGoogle Scholar
  28. Kristoufek, L. (2015). What are the main drivers of the bitcoin price? Evidence from wavelet coherence analysis. PLoS One, 10(4), 1–15.  https://doi.org/10.1371/journal.pone.0123923 CrossRefGoogle Scholar
  29. Kristoufek, L. (2018). On Bitcoin markets (in)efficiency and its evolution. Physica A: Statistical Mechanics and its Applications, 503, 257–262.  https://doi.org/10.1016/j.physa.2018.02.161 CrossRefGoogle Scholar
  30. Lee, H. C., & Chang, S. L. (2013). Spillovers of currency carry trade returns, market risk sentiment, and US market returns. The North American Journal of Economics and Finance, 26, 197–216.  https://doi.org/10.1016/j.najef.2013.10.001 CrossRefGoogle Scholar
  31. Lucey, B. M., Larkin, C., & O’Connor, F. (2014). Gold markets around the world—who spills over what, to whom, when? Applied Economics Letters, 21(13), 887–892.  https://doi.org/10.1080/13504851.2014.896974 CrossRefGoogle Scholar
  32. Maghyereh, A. I., & Awartani, B. (2016). Dynamic transmissions between Sukuk and bond markets. Research in International Business and Finance, 38, 246–261.  https://doi.org/10.1016/j.ribaf.2016.04.016 CrossRefGoogle Scholar
  33. Maghyereh, A. I., Awartani, B., & Bouri, E. (2016). The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes. Energy Economics, 57, 78–93.  https://doi.org/10.1016/j.eneco.2016.04.010 CrossRefGoogle Scholar
  34. Nadarajah, S., & Chu, J. (2017). On the inefficiency of Bitcoin. Economics Letters, 150, 6–9.  https://doi.org/10.1016/j.econlet.2016.10.033 CrossRefGoogle Scholar
  35. Narayan, P. K., Narayan, S., & Prabheesh, K. P. (2014). Stock returns, mutual fund flows and spillover shocks. Pacific-Basin Finance Journal, 29, 146–162.  https://doi.org/10.1016/j.pacfin.2014.03.007 CrossRefGoogle Scholar
  36. Öztürk, M. B., Arslan, H., Kayhan, T., & Uysal, M. (2018). Bitcoin as a new hedge instrument tool: Bitconomy. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 11(2), 217–232.  https://doi.org/10.25287/ohuiibf.415713 CrossRefGoogle Scholar
  37. Phillips, R. C., & Gorse, D. (2018). Cryptocurrency price drivers: Wavelet coherence analysis revisited. PLoS One, 13(4), 1–21.  https://doi.org/10.1371/journal.pone.0195200 CrossRefGoogle Scholar
  38. Pichl, L., & Kaizoji, T. (2017). Volatility analysis of Bitcoin price time series. Quantitative Finance and Economics, 1(4), 474–485.  https://doi.org/10.3934/QFE.2017.4.474 CrossRefGoogle Scholar
  39. Sehgal, S., Ahmad, W., & Deisting, F. (2015). An investigation of price discovery and volatility spillovers in India’s foreign exchange market. Journal of Economic Studies, 42(2), 261–284.  https://doi.org/10.1108/JES-11-2012-0157 CrossRefGoogle Scholar
  40. Sugimoto, K., Matsuki, T., & Yoshida, Y. (2014). The global financial crisis: An analysis of the spillover effects on African stock markets. Emerging Markets Review, 21, 201–233.  https://doi.org/10.1016/j.ememar.2014.09.004 CrossRefGoogle Scholar
  41. Tsai, I. C. (2014). Spillover of fear: Evidence from the stock markets of five developed countries. International Review of Financial Analysis, 33, 281–288.  https://doi.org/10.1016/j.irfa.2014.03.007 CrossRefGoogle Scholar
  42. Teichmann, F. M. J. (2018). Financing terrorism through cryptocurrencies—a danger for Europe? Journal of Money Laundering Control, 21(4), 513–519.  https://doi.org/10.1108/JMLC-06-2017-0024 CrossRefGoogle Scholar
  43. Tiwari, A. K., Jana, R. K., Das, D., & Roubaud, D. (2018). Informational efficiency of Bitcoin—An extension. Economics Letters, 163, 106–109.  https://doi.org/10.1016/j.econlet.2017.12.006 CrossRefGoogle Scholar
  44. Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80–82.  https://doi.org/10.1016/j.econlet.2016.09.019 CrossRefGoogle Scholar
  45. Urquhart, A., & Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis.  https://doi.org/10.1016/j.irfa.2019.02.009 CrossRefGoogle Scholar
  46. Yarovaya, L., Brzeszczyński, J., & Lau, C. K. M. (2016). Intra-and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures. International Review of Financial Analysis, 43, 96–114.  https://doi.org/10.1016/j.irfa.2015.09.004 CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Banking and Finance, Faculty of Applied SciencesBilecik Seyh Edebali UniversityBozüyükTurkey
  2. 2.Department of Business Administration, Faculty of Economics and Administrative SciencesAnadolu UniversityEskişehirTurkey

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