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.
Read more > https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3041977
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