Trading volume and the predictability of return and volatility in the cryptocurrency market

Balcilar, 2017, Can volume predict Bitcoin returns and volatility? A quantiles-based approach, Econ. Model., 64, 74, 10.1016/j.econmod.2017.03.019

Bouri, 2018, Co-explosivity in the cryptocurrency market, Finance Res. Lett.

Bouri, 2018, Bitcoin and global financial stress: a copula-based approach to dependence and causality in the quantiles, Q. Rev. Econ. Finance, 69, 297, 10.1016/j.qref.2018.04.003

Clark, 1973, A subordinated stochastic process model with finite variance for speculative prices, Econometrica, 41, 135, 10.2307/1913889

Corbet, S., Meegan, A., Larkin, C., Lucey, B. and Yarovaya, L. (2018). Exploring the dynamic relationships between cryptocurrencies and other financial assets. 165, 28–34.

Gandal, 2018, Price manipulation in the Bitcoin ecosystem, J. Monet. Econ., 95, 86, 10.1016/j.jmoneco.2017.12.004

Gebka, 2013, Causality between trading volume and returns: evidence from quantile regressions, Int. Rev. Econ. Finance, 27, 144, 10.1016/j.iref.2012.09.009

Jiang, 2017, Time-varying long-term memory in Bitcoin market, Finance Res. Lett., 25, 280, 10.1016/j.frl.2017.12.009

Koenker, 1978, Regression quantiles, Econometrica, 33, 10.2307/1913643

Lee, 2014, Granger-causality in quantiles between financial markets: using copula approach, Int. Rev. Financial Anal, 33, 70, 10.1016/j.irfa.2013.08.008

Ning, 2009, Extreme return–volume dependence in East-Asian stock markets: a copula approach, Finance Res. Lett., 6, 202, 10.1016/j.frl.2009.09.002