  The objective of this paper is the construction of new indicators that can be
useful to operate in the cryptocurrency market. These indicators are based on
public data obtained from the blockchain network, specifically from the nodes
that make up Bitcoin mining. Therefore, our analysis is unique to that network.
The results obtained with numerical simulations of algorithmic trading and
prediction via statistical models and Machine Learning demonstrate the
importance of variables such as the hash rate, the difficulty of mining or the
cost per transaction when it comes to trade Bitcoin assets or predict the
direction of price. Variables obtained from the blockchain network will be
called here blockchain metrics. The corresponding indicators (inspired by the
"Hash Ribbon") perform well in locating buy signals. From our results, we
conclude that such blockchain indicators allow obtaining information with a
statistical advantage in the highly volatile cryptocurrency market.
