  This paper is the first of a series of short articles that explore the
efficiency of major cryptocurrency markets. A number of statistical tests and
properties of statistical distributions will be used to assess if
cryptocurrency markets are efficient, and how their efficiency changes over
time. In this paper, we analyze autocorrelation of returns in major
cryptocurrency markets using the following methods: Pearson's autocorrelation
coefficient of different orders, Ljung-Box test, and first-order Pearson's
autocorrelation coefficient in a rolling window. All experiments are conducted
on the BTC/USD, ETH/USD, ETH/BTC markets on Bitfinex exchange, and the XBT/USD
market on Bitmex exchange, each on 5-minute, 1-hour, 1-day, and 1-week time
frames. The results are represented visually on charts. Statistically
significant autocorrelation is persistently present on the 5m and 1H time
frames on all markets. The tests disagree on the 1D and 1W time frames. The
results of this article are fully reproducible. Used datasets, source code, and
a runnable Jupyter Notebook are available on GitHub.
