In recent years a new type of tradable assets appeared, generically known as
cryptocurrencies. Among them, the most widespread is Bitcoin. Given its
novelty, this paper investigates some statistical properties of the Bitcoin
market. This study compares Bitcoin and standard currencies dynamics and
focuses on the analysis of returns at different time scales. We test the
presence of long memory in return time series from 2011 to 2017, using
transaction data from one Bitcoin platform. We compute the Hurst exponent by
means of the Detrended Fluctuation Analysis method, using a sliding window in
order to measure long range dependence. We detect that Hurst exponents changes
significantly during the first years of existence of Bitcoin, tending to
stabilize in recent times. Additionally, multiscale analysis shows a similar
behavior of the Hurst exponent, implying a self-similar process.Comment: 17 pages, 6 figures. arXiv admin note: text overlap with
arXiv:1605.0670