  This letter revisits the informational efficiency of the Bitcoin market. In
particular we analyze the time-varying behavior of long memory of returns on
Bitcoin and volatility 2011 until 2017, using the Hurst exponent. Our results
are twofold. First, R/S method is prone to detect long memory, whereas DFA
method can discriminate more precisely variations in informational efficiency
across time. Second, daily returns exhibit persistent behavior in the first
half of the period under study, whereas its behavior is more informational
efficient since 2014. Finally, price volatility, measured as the logarithmic
difference between intraday high and low prices exhibits long memory during all
the period. This reflects a different underlying dynamic process generating the
prices and volatility.
