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Using data from a prominent blockchain research firm, Coinmetrics.io, we explore the relationship between prices, computing power (measured by the hashrate), and network (measured by the number of unique active users). We focus on five major mineable cryptocurrencies (i.e. Bitcoin, Ethereum, Monero, Litecoin, and Dash). In some of our test, we expand our data to include an additional 33 cryptocurrencies. Our sample period spans from 7 August 2015 to 25 January 2019.

Crypto-marketing. A scheme in which promoters of securities tied to cryptocurrencies recruit investors to pitch the investments, often to friends and family and through social media and blogs. In return, these investors are promised a generous return plus the promise of commissions on their sales.
The strengthening of coherence in bubble regimes is much less prominent in the short and long term. In the short term, the effect of bubbles may be hidden by the effects of daily news items and intraday trading activity. It is also seen that in the short term the relationship between online factors and cryptocurrency prices are erratic and generally weak; there is little consistency as to whether the price or factors are leading, though slightly more negative relationships exist in this period band. The erratic relationships over the short term suggest online factors may not be best predictor in the shorter term.