Correlations among cryptocurrencies: Evidence from multivariate factor stochastic volatility model

Bouri, 2017, Does bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions, Financ. Res. Lett., 23, 87, 10.1016/j.frl.2017.02.009 Bouri, 2017, On the hedge and safe haven properties of bitcoin: is it really more than a diversifier?, Financ. Res. Lett., 20, 192, 10.1016/j.frl.2016.09.025 Bouri, 2020, The volatility surprise of leading cryptocurrencies: transitory and permanent linkages, Financ. Res. Lett., 10.1016/j.frl.2019.05.006 Bouri, 2020, Do bitcoin and other cryptocurrencies jump together?, Q. Rev. Econ. Finance, 10.1016/j.qref.2019.09.003 Chib, 2006, Analysis of high dimensional multivariate stochastic volatility models, J. Econom., 134, 341, 10.1016/j.jeconom.2005.06.026 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 Ciaian, 2016, The economics of bitcoin price formation, Appl. Econ., 48, 1799, 10.1080/00036846.2015.1109038 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 Dyhrberg, 2016, Hedging capabilities of bitcoin. Is it the virtual gold?, Financ. Res. Lett., 16, 139, 10.1016/j.frl.2015.10.025 Dyhrberg, 2016, Bitcoin, gold and the dollar – a GARCH volatility analysis, Financ. Res. Lett., 16, 85, 10.1016/j.frl.2015.10.008 Guesmi, 2018, Portfolio diversification with virtual currency: evidence from bitcoin, Int. Rev. Financ. Anal., 63, 431, 10.1016/j.irfa.2018.03.004 Ji, 2018, Network causality structures among bitcoin and other financial assets: a directed acyclic graph approach, Q. Rev. Econ. Finance, 70, 203, 10.1016/j.qref.2018.05.016 Ji, 2019, Dynamic connectedness and integration in cryptocurrency markets, Int. Rev. Financ. Anal., 63, 257, 10.1016/j.irfa.2018.12.002 Kastner, 2017, Efficient bayesian inference for multivariate factor stochastic volatility models, J. Comput. Graph. Stat., 26, 905, 10.1080/10618600.2017.1322091 Katsiampa, 2017, Volatility estimation for bitcoin: a comparison of GARCH models, Econ. Lett., 158, 3, 10.1016/j.econlet.2017.06.023 Katsiampa, 2019, Volatility spillover effects in leading cryptocurrencies: a BEKK-MGARCH analysis, Financ. Res. Lett., 29, 68, 10.1016/j.frl.2019.03.009 Katsiampa, 2019, High frequency volatility Co-movements in cryptocurrency markets, J. Int. Financ. Mark. Inst. Money, 62, 35, 10.1016/j.intfin.2019.05.003 Klein, 2018, Bitcoin is not the new gold–a comparison of volatility, correlation, and portfolio performance, Int. Rev. Financ. Anal., 59, 105, 10.1016/j.irfa.2018.07.010 Shahzad, 2019, Is Bitcoin a better safe-haven investment than gold and commodities?, Int. Rev. Financ. Anal., 63, 322, 10.1016/j.irfa.2019.01.002 Tiwari, 2019, Modelling the dynamics of bitcoin and litecoin: GARCH versus stochastic volatility models, Appl. Econ., 51, 4073, 10.1080/00036846.2019.1588951 Tiwari, 2019, Time-varying dynamic conditional correlation between stock and cryptocurrency markets using the Copula-ADCC-EGARCH model, Phys. A Stat. Mech. Its Appl., 535