Are cryptocurrencies becoming more interconnected?
Tài liệu tham khảo
Andersen, 2001, The distribution of realized stock return volatility, J. Financ. Econ., 61, 43, 10.1016/S0304-405X(01)00055-1
Aslanidis, 2019, An analysis of cryptocurrencies conditional cross correlations, Finance Res. Lett., 31, 130, 10.1016/j.frl.2019.04.019
Bai, 2016, Cross-sectional dependence in panel data models: A special issue, J. Appl. Econometrics, 31, 1, 10.1002/jae.2507
Bariviera, 2017, The inefficiency of bitcoin revisited: A dynamic approach, Econom. Lett., 161, 1, 10.1016/j.econlet.2017.09.013
Barunik, 2018, Measuring the frequency dynamics of financial connectedness and systemic risk, J. Financ. Econ., 16, 271
Bouri, 2020, Return equicorrelation in the cryptocurrency market: Analysis and determinants, Finance Res. Lett.
Coinmap, 2020
Coinmarket, 2020
Corbet, 2019, Cryptocurrencies as a financial asset: A systematic analysis, Int. Rev. Financ. Anal., 62, 182, 10.1016/j.irfa.2018.09.003
Corbet, 2018, Exploring the dynamic relationships between cryptocurrencies and other financial assets, Econom. Lett., 165, 28, 10.1016/j.econlet.2018.01.004
Demirer, 2018, Estimating global bank network connectedness, J. Appl. Econometrics, 33, 1, 10.1002/jae.2585
Diebold, 2009, Measuring financial asset return and volatility spillovers, with application to global equity markets, Econom. J., 119, 158
Diebold, 2012, Better to give than to receive: Predictive directional measurement of volatility spillovers, Int. J. Forecast., 28, 57, 10.1016/j.ijforecast.2011.02.006
Diebold, 2014, On the network topology of variance decompositions: Measuring the connectedness of financial firms, J. Econometrics, 182, 119, 10.1016/j.jeconom.2014.04.012
Diebold, 2016, Trans-atlantic equity volatility connectedness: U.S. and European financial institutions 2004–2014, J. Financ. Econ., 14, 1479
Garcia, 2015, Social signals and algorithmic trading of Bitcoin, Royal Soc. Open Sci., 2, 10.1098/rsos.150288
Garcia, 2014, The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy, J. R. Soc. Interface, 11, 10.1098/rsif.2014.0623
Garman, 1980, On the estimation of security price volatilities from historical data, J. Bus., 53, 67, 10.1086/296072
Goodell, 2020, Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis, Finance Res. Lett.
Ji, 2019, Dynamic connectedness and integration in cryptocurrency markets, Int. Rev. Financ. Anal., 63, 257, 10.1016/j.irfa.2018.12.002
Kristoufek, 2013, Bitcoin meets google trends and wikipedia: Quantifying the relationship between phenomena of the internet era, Sci. Rep., 3, 3415, 10.1038/srep03415
Kristoufek, 2015, What are the main drivers of the bitcoin price? Evidence from wavelet coherence analysis, PLoS One, 10, 10.1371/journal.pone.0123923
Kurka, 2019, Do cryptocurrencies and traditional asset classes influence each other?, Finance Res. Lett., 31, 38, 10.1016/j.frl.2019.04.018
Merediz-Solà, 2019, A bibliometric analysis of Bitcoin scientific production, Res. Int. Bus. Finance, 50, 294, 10.1016/j.ribaf.2019.06.008
Nakamoto, 2009
Pesaran, 2015, Testing weak cross-sectional dependence in large panels, Econometric Rev., 34, 1089, 10.1080/07474938.2014.956623
Tiwari, 2018, Informational efficiency of Bitcoin – An extension, Econom. Lett., 163, 106, 10.1016/j.econlet.2017.12.006
Urquhart, 2016, The inefficiency of Bitcoin, Econom. Lett., 148, 80, 10.1016/j.econlet.2016.09.019
Vidal-Tomás, 2019, Herding in the cryptocurrency market: CSSD and CSAD approaches, Finance Res. Lett., 30, 181, 10.1016/j.frl.2018.09.008
Wei, 2019, 139
Yelowitz, 2015, Characteristics of Bitcoin users: an analysis of Google search data, Appl. Econ. Lett., 22, 1030, 10.1080/13504851.2014.995359
Yi, 2018, Volatility connectedness in the cryptocurrency market: Is bitcoin a dominant cryptocurrency?, Int. Rev. Financ. Anal., 60, 98, 10.1016/j.irfa.2018.08.012
Yilmaz, 2020