Inter-markets volatility spillover in U.S. bitcoin and financial markets
Abstract
This paper investigates the volatility spillover dynamics between U.S. Bitcoin and financial markets from July 19, 2010 to December 29, 2017. Diebold and Yilmaz (2012) volatility spillover index, Barunik, Kocenda, and Vacha (2017) Spillover Asymmetry Measure, and Barunik and Krehlik (2018) frequency connectedness methodologies are applied to investigate the time varying dynamics of volatility spillover among U.S. Bitcoin and financial markets. The findings of the study indicate the presence of low level of integration and contagion between U.S. Bitcoin and financial markets. Asymmetric nature of volatility spillover is also detected. The connectedness among the U.S. Bitcoin and financial markets is found to be concentrated at high frequency, suggesting that markets process information rapidly. Moreover, the turbulence in Bitcoin market will have insignificant effect on U.S. financial markets. This non-contagion nature of Bitcoin markets provides significant risk hedging and diversification benefits for domestic and foreign investors in the U.S.
Keyword : bitcoin, stock market, volatility spillover, spillover asymmetry measure, frequency connectedness, foreign exchange market
How to Cite
Qarni, M. O., Gulzar, S., Fatima, S. T., Khan, M. J., & Shafi, K. (2019). Inter-markets volatility spillover in U.S. bitcoin and financial markets. Journal of Business Economics and Management, 20(4), 694-714. https://doi.org/10.3846/jbem.2019.8316
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Dyhrberg, A. H. (2016a). Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters, 16, 85-92. https://doi.org/10.1016/j.frl.2015.10.008
Dyhrberg, A. H. (2016b). 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
Ehrmann, M., Fratzscher, M., & Rigobon, R. (2011). Stocks, bonds, money markets and exchange rates: measuring international financial transmission. Journal of Applied Econometrics, 26(6), 948-974. https://doi.org/10.1002/jae.1173
Force, F. A. T. (2014). Virtual currencies: key definitions and potential AML/CFT risks. FATF Report, June.
Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2018). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2018.03.004
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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
Kerner, S. (2014). Why Marc Andreessen is Bullish on Bitcoin. Eweek, 3.
Kim, B. H., Kim, H., & Lee, B. S. (2015). Spillover effects of the US financial crisis on financial markets in emerging Asian countries. International Review of Economics & Finance, 39, 192-210. https://doi.org/10.1016/j.iref.2015.04.005
King, M. A., & Wadhwani, S. (1990). Transmission of volatility between stock markets. The Review of Financial Studies, 3(1), 5-33. https://doi.org/10.1093/rfs/3.1.5
Kodres, L. E., & Pritsker, M. (2002). A rational expectations model of financial contagion. The Journal of Finance, 57(2), 769-799. https://doi.org/10.1111/1540-6261.00441
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of econometrics, 74(1), 119-147. https://doi.org/10.1016/0304-4076(95)01753-4
Kurihara, Y., & Fukushima, A. (2017). The market efficiency of Bitcoin: A weekly anomaly perspective. Journal of Applied Finance and Banking, 7(3), 57.
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
Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics letters, 58(1), 17-29. https://doi.org/10.1016/S0165-1765(97)00214-0
Phillips, P. C., & Yu, J. (2011). Dating the timeline of financial bubbles during the subprime crisis. Quantitative Economics, 2(3), 455-491. https://doi.org/10.3982/QE82
Qarni, M. O., & Gulzar, S. (2018). Volatility spillover effects of Shanghai stock exchange crash on the stock markets of its major trading partners. Business & Economic Review, 10(3), 1-28.
Raghunathan, S. (2015). Volatility in Indian stock market. Asian Journal of Research in Business Economics and Management, 5(2), 298-311. https://doi.org/10.5958/2249-7307.2015.00049.3
Richardson, V. (2014). Currency kings. Entrepreneur, 42, 40.
Rogers, L. C. G., & Satchell, S. E. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, 504-512. https://doi.org/10.1214/aoap/1177005835
Selgin, G. (2015). Synthetic commodity money. Journal of Financial Stability, 17, 92-99. https://doi.org/10.1016/j.jfs.2014.07.002
Urquhart, A. (2017). Price clustering in Bitcoin. Economics Letters, 159, 145-148. https://doi.org/10.1016/j.econlet.2017.07.035
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
Yusoff, M. B., & Sabit, A. H. (2015). The effects of exchange rate volatility on ASEAN-China bilateral exports. Journal of Economics, Business and Management, 3(5), 479-482. https://doi.org/10.7763/JOEBM.2015.V3.231
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
Authority, E. B. (2014). Eba opinion on virtual currencies. Retrieved from https://www. eba. europa. eu/documents/10180/657547/EBA-Op-2014-08+ Opinion+ on+ Virtual+ Currencies. Pdf
Barunik, J., & Krehlik, T. (2016). Measuring the frequency dynamics of financial and macroeconomic connectedness (No. 54). FinMaP-Working Paper.
Barunik, J., & Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271-296. https://doi.org/10.1093/jjfinec/nby001
Barunik, J., Kocenda, E., & Vacha, L. (2015). Volatility spillovers across petroleum markets. William Davidson Institute Working Paper No. 1093. https://doi.org/10.2139/ssrn.2600204
Barunik, J., Kočenda, E., & Vácha, L. (2017). Asymmetric volatility connectedness on the Forex market. Journal of International Money and Finance, 77, 39-56. https://doi.org/10.1016/j.jimonfin.2017.06.003
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. https://doi.org/10.1016/j.intfin.2017.12.004
Bouri, E., Jalkh, N., Molnár, P., & Roubaud, D. (2017a). Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven? Applied Economics, 49(50), 5063-5073. https://doi.org/10.1080/00036846.2017.1299102
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. https://doi.org/10.1016/j.frl.2016.09.025
Bouri, E., Gupta, R., Tiwari, A., & Roubaud, D. (2017c). Does bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 000, 1-9. https://doi.org/10.1016/j.frl.2017.02.009
Brunnermeier, M. K., & Pedersen, L. H. (2008). Market liquidity and funding liquidity. The Review of Financial Studies, 22(6), 2201-2238. https://doi.org/10.1093/rfs/hhn098
Bubak, V., Kočenda, E., & Žikeš, F. (2011). Volatility transmission in emerging European foreign exchange markets. Journal of Banking & Finance, 35(11), 2829-2841. https://doi.org/10.1016/j.jbankfin.2011.03.012
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
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
Coindesk. (2017). Bitcoin Price Index. Retrieved from https://www.coindesk.com/price/bitcoin
Demir, E., Gozgor, G., Lau, C. K. M., & Vigne, S. A. (2018). Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation. Finance Research Letters. https://doi.org/10.1016/j.frl.2018.01.005
Dew-Becker, I., & Giglio, S. (2016). Asset pricing in the frequency domain: theory and empirics. The Review of Financial Studies, 29(8), 2029-2068. https://doi.org/10.1093/rfs/hhw027
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
Dwyer, G. P. (2015). The economics of Bitcoin and similar private digital currencies. Journal of Financial Stability, 17, 81-91. https://doi.org/10.1016/j.jfs.2014.11.006
Dyhrberg, A. H. (2016a). Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters, 16, 85-92. https://doi.org/10.1016/j.frl.2015.10.008
Dyhrberg, A. H. (2016b). 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
Ehrmann, M., Fratzscher, M., & Rigobon, R. (2011). Stocks, bonds, money markets and exchange rates: measuring international financial transmission. Journal of Applied Econometrics, 26(6), 948-974. https://doi.org/10.1002/jae.1173
Force, F. A. T. (2014). Virtual currencies: key definitions and potential AML/CFT risks. FATF Report, June.
Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2018). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2018.03.004
Gulzar, S., Kayani, G. M., Feng, H. X. Ayub, U., & Rafique, A. (2019). Financial cointegration and spillover effect of global financial crisis: A study of emerging Asian financial markets. Economic Research – Ekonomska Istraživanja.
Investing. (2017). Market indices. Retrieved from https://www.investing.com/indices/
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
Kerner, S. (2014). Why Marc Andreessen is Bullish on Bitcoin. Eweek, 3.
Kim, B. H., Kim, H., & Lee, B. S. (2015). Spillover effects of the US financial crisis on financial markets in emerging Asian countries. International Review of Economics & Finance, 39, 192-210. https://doi.org/10.1016/j.iref.2015.04.005
King, M. A., & Wadhwani, S. (1990). Transmission of volatility between stock markets. The Review of Financial Studies, 3(1), 5-33. https://doi.org/10.1093/rfs/3.1.5
Kodres, L. E., & Pritsker, M. (2002). A rational expectations model of financial contagion. The Journal of Finance, 57(2), 769-799. https://doi.org/10.1111/1540-6261.00441
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of econometrics, 74(1), 119-147. https://doi.org/10.1016/0304-4076(95)01753-4
Kurihara, Y., & Fukushima, A. (2017). The market efficiency of Bitcoin: A weekly anomaly perspective. Journal of Applied Finance and Banking, 7(3), 57.
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
Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics letters, 58(1), 17-29. https://doi.org/10.1016/S0165-1765(97)00214-0
Phillips, P. C., & Yu, J. (2011). Dating the timeline of financial bubbles during the subprime crisis. Quantitative Economics, 2(3), 455-491. https://doi.org/10.3982/QE82
Qarni, M. O., & Gulzar, S. (2018). Volatility spillover effects of Shanghai stock exchange crash on the stock markets of its major trading partners. Business & Economic Review, 10(3), 1-28.
Raghunathan, S. (2015). Volatility in Indian stock market. Asian Journal of Research in Business Economics and Management, 5(2), 298-311. https://doi.org/10.5958/2249-7307.2015.00049.3
Richardson, V. (2014). Currency kings. Entrepreneur, 42, 40.
Rogers, L. C. G., & Satchell, S. E. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, 504-512. https://doi.org/10.1214/aoap/1177005835
Selgin, G. (2015). Synthetic commodity money. Journal of Financial Stability, 17, 92-99. https://doi.org/10.1016/j.jfs.2014.07.002
Urquhart, A. (2017). Price clustering in Bitcoin. Economics Letters, 159, 145-148. https://doi.org/10.1016/j.econlet.2017.07.035
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
Yusoff, M. B., & Sabit, A. H. (2015). The effects of exchange rate volatility on ASEAN-China bilateral exports. Journal of Economics, Business and Management, 3(5), 479-482. https://doi.org/10.7763/JOEBM.2015.V3.231