An empirical investigation of volatility dynamics in the cryptocurrency market

Akyildirim, 2019 Allen, 2017 Baba, 1990 Baek, 2015, Bitcoins as an investment or speculative vehicle? A first look, Appl. Econ. Lett., 22, 30, 10.1080/13504851.2014.916379 Bai, 1997, Estimation of a change point in multiple regression models, Rev. Econ. Stat., 79, 551, 10.1162/003465397557132 Bai, 1998, Estimating and testing linear models with multiple structural changes, Econometrica, 47, 10.2307/2998540 Balcilar, 2017, Can volume predict Bitcoin returns and volatility? A quantiles based approach, Econ. Model., 64, 74, 10.1016/j.econmod.2017.03.019 Bariviera, 2017, The inefficiency of Bitcoin revisited: a dynamic approach, Econ. Lett., 161, 1, 10.1016/j.econlet.2017.09.013 Baur, 2018, Bitcoin: medium of exchange or speculative assets?, J. Int. Financ. Mark. Inst. Money, 54, 177, 10.1016/j.intfin.2017.12.004 Begiazi, 2019, Modelling UK house prices with structural breaks and conditional variance analysis, J. Real Estate Finance Econ., 58, 290, 10.1007/s11146-018-9652-5 Blau, 2017, Price dynamics and speculative trading in bitcoin, Res. Int. Bus. Finance, 41, 493, 10.1016/j.ribaf.2017.05.010 Böhme, 2015, Bitcoin: economics, technology, and governance, J. Econ. Perspect., 29, 213, 10.1257/jep.29.2.213 Boldanov, 2016, Time-varying correlation between oil and stock market volatilities: evidence from oil-importing and oil-exporting countries, Int. Rev. Financ. Anal., 48, 209, 10.1016/j.irfa.2016.10.002 Bouri, 2017, Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?, Appl. Econ., 49, 5063 Brandvold, 2015, Price discovery on Bitcoin exchanges, J. Int. Financ. Mark. Inst. Money, 36, 18, 10.1016/j.intfin.2015.02.010 Brauneis, 2018, Price discovery of cryptocurrencies: Bitcoin and beyond, Econ. Lett., 165, 58, 10.1016/j.econlet.2018.02.001 Caporale, 2018, Persistence in the cryptocurrency market, Res. Int. Bus. Finance, 46, 141, 10.1016/j.ribaf.2018.01.002 Caporin, 2012, Do we really need both BEKK and DCC? A tale of two multivariate GARCH models, J. Econ. Surv., 26, 736, 10.1111/j.1467-6419.2011.00683.x Caporin, 2013, Ten things you should know about the dynamic conditional correlation representation, Econometrics, 1, 115, 10.3390/econometrics1010115 Chang, 2019, The fiction of full BEKK: pricing fossil fuels and carbon emissions, Finance Res. Lett., 28, 11, 10.1016/j.frl.2018.03.008 Chang, 2017, Volatility spillovers and causality of carbon emissions, oil and coal spot and futures for the EU and USA, Sustainability, 9, 1789, 10.3390/su9101789 Cheah, 2015, Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin, Econ. Lett., 130, 32, 10.1016/j.econlet.2015.02.029 Cheung, 2015, Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices, Appl. Econ., 47, 2348, 10.1080/00036846.2015.1005827 Chow, 1960, Tests of equality between sets of coefficients in two linear regressions, Econom. J. Econom. Soc., 591 Chu, 2017, GARCH modelling of cryptocurrencies, J. Risk Financ. Manag., 10, 17, 10.3390/jrfm10040017 Ciaian, 2016, The economics of BitCoin price formation, Appl. Econ., 48, 1799, 10.1080/00036846.2015.1109038 Ciaian, 2018, Virtual relationships: short- and long-run evidence from BitCoin and Altcoin markets, J. Int. Financ. Mark. Inst. Money, 52, 173, 10.1016/j.intfin.2017.11.001 Corbet, 2018, Datestamping the Bitcoin and Ethereum bubbles, Finance Res. Lett., 26, 81, 10.1016/j.frl.2017.12.006 Corbet, 2018, Exploring the dynamic relationships between cryptocurrencies and other financial assets, Econ. Lett., 165, 28, 10.1016/j.econlet.2018.01.004 Corbet, 2019, Cryptocurrencies as a financial asset: a systematic analysis, Int. Rev. Financ. Anal., 62, 182, 10.1016/j.irfa.2018.09.003 Coudert, 2015, Internationalization versus regionalization in the emerging stock markets, Int. J. Financ. Econ., 20, 16, 10.1002/ijfe.1501 Dickey, 1979, Distribution of the estimators for autoregressive time series with a unit root, J. Am. Stat. Assoc., 74, 427, 10.1080/01621459.1979.10482531 Dwyer, 2015, The economics of Bitcoin and similar private digital currencies, J. Financ. Stab., 17, 81, 10.1016/j.jfs.2014.11.006 Dyhrberg, 2016, Bitcoin, gold and the dollar–a GARCH volatility analysis, Finance Res. Lett., 16, 85, 10.1016/j.frl.2015.10.008 Engle, 2002, Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models, J. Bus. Econ. Stat., 20, 339, 10.1198/073500102288618487 Engle, 1995, Multivariate simultaneous generalized ARCH, Econ. Theory, 11, 122, 10.1017/S0266466600009063 Feng, 2018, Informed trading in the Bitcoin market, Finance Res. Lett., 26, 63, 10.1016/j.frl.2017.11.009 Foley, 2019, Sex, drugs, and Bitcoin: how much illegal activity is financed through cryptocurrencies?, Rev. Financ. Stud., 32, 1798, 10.1093/rfs/hhz015 Frisby, 2014 Fry, 2016, Negative bubbles and shocks in cryptocurrency markets, Int. Rev. Financ. Anal., 47, 343, 10.1016/j.irfa.2016.02.008 Georgoula, 2015 Gkillas, 2018, An application of extreme value theory to cryptocurrencies, Econ. Lett., 164, 109, 10.1016/j.econlet.2018.01.020 Glaser, 2014 Glosten, 1993, On the relation between the expected value and the volatility of the nominal excess return on stocks, J. Finance, 48, 1779, 10.1111/j.1540-6261.1993.tb05128.x Karame, 2016 Katsiampa, 2017, Volatility estimation for Bitcoin: a comparison of GARCH models, Econ. Lett., 158, 3, 10.1016/j.econlet.2017.06.023 Katsiampa, 2018, Volatility co-movement between Bitcoin and Ether, Finance Res. Lett. Katsiampa, 2018 Koutmos, 2018, Bitcoin returns and transaction activity, Econ. Lett., 167, 81, 10.1016/j.econlet.2018.03.021 Kristoufek, 2013, BitCoin meets Google Trends and Wikipedia: quantifying the relationship between phenomena of the Internet era, Sci. Rep., 3, 3415, 10.1038/srep03415 Kroll, 2013, The economics of Bitcoin mining, or Bitcoin in the presence of adversaries, Proceedings of WEIS, Vol. 2013, 11 Kroner, 1998, Modeling asymmetric comovements of asset returns, Rev. Financ. Stud., 11, 817, 10.1093/rfs/11.4.817 Kwiatkowski, 1992, Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root?, J. Econom., 54, 159, 10.1016/0304-4076(92)90104-Y Lahmiri, 2018, Long-range memory, distributional variation and randomness of Bitcoin volatility, Chaos Solitons Fractals, 107, 43, 10.1016/j.chaos.2017.12.018 Lee, 2018, Cryptocurrency: a new investment opportunity?, J. Altern. Invest., 20, 16 Liu, 2017, GARCH model with fat-tailed distributions and Bitcoin exchange rate returns, J. Account. Bus. Finance Res., 1, 71, 10.20448/2002.11.71.75 Mensi, 2018, Structural breaks and double long memory of cryptocurrency prices: a comparative analysis from Bitcoin and Ethereum, Finance Res. Lett. Nadarajah, 2017, On the inefficiency of Bitcoin, Econ. Lett., 150, 6, 10.1016/j.econlet.2016.10.033 Narayanan, 2016 Osterrieder, 2017, A statistical risk assessment of Bitcoin and its extreme tail behavior, Ann. Financ. Econ., 12, 1750003, 10.1142/S2010495217500038 Osterrieder, 2017, Bitcoin and cryptocurrencies – not for the faint-hearted, Int. Finance Bank., 4, 56, 10.5296/ifb.v4i1.10451 Panagiotidis, 2018, On the determinants of bitcoin returns: a LASSO approach, Finance Res. Lett., 27, 235, 10.1016/j.frl.2018.03.016 Phillip, 2018, A new look at cryptocurrencies, Econ. Lett., 163, 6, 10.1016/j.econlet.2017.11.020 Phillips, 1988, Testing for a unit root in time series regression, Biometrika, 75, 335, 10.1093/biomet/75.2.335 Phillips, 2015, Testing for multiple bubbles: historical episodes of exuberance and collapse in the S&P 500, Int. Econ. Rev., 56, 1043, 10.1111/iere.12132 Takaishi, 2018, Statistical properties and multifractality of Bitcoin, Phys. A Stat. Mech. Appl., 506, 507, 10.1016/j.physa.2018.04.046 Terrell, 2006 Tiwari, 2018, Informational efficiency of Bitcoin—an extension, Econ. Lett., 163, 106, 10.1016/j.econlet.2017.12.006 Tse, 2000, A test for constant correlations in a multivariate GARCH model, J. Econom., 98, 107, 10.1016/S0304-4076(99)00080-9 Tse, 2002, A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations, J. Bus. Econ. Stat., 20, 351, 10.1198/073500102288618496 Urquhart, 2016, The inefficiency of Bitcoin, Econ. Lett., 148, 80, 10.1016/j.econlet.2016.09.019 Weber, 2014, Bitcoin and the legitimacy crisis of money, Cambridge J. Econ., 40, 17, 10.1093/cje/beu067 Yermack, 2015, Is Bitcoin a real currency? An economic appraisal