More importantly, we find that the ACP and ANET factors can price cryptocurrency returns. In particular, all of our five cryptocurrencies have positive and significant exposures to the fundamental factors. The explanatory power of ACP and ANET is over and above any effects related to the Bitcoin and momentum factors. This finding is non-trivial given that the five cryptocurrencies in our sample have consistently accounted for between 80% to 95% of the total cryptocurrency market capitalisation. Furthermore, we extend our factor analysis to an out-of-sample set of 33 cryptocurrencies obtained from the Bittrex exchange. We find that the aggregate computing power and network factors also price cryptocurrencies in this large out-of-sample data set.
In particular, the activities of miners — cryptocurrency users who leverage vast amounts of computing power to record transactions, receiving newly created cryptocurrency units and transaction fees paid by other users in return — are critical to currencies’ stability and smooth function.

There is not one single location for Wikipedia views data over the historical data interval required. Wikipedia views data from the start of 2015 onwards can be retrieved using the official mwviews python library which connects to Wikipedia’s pageview API. Previous historical data can be retrieved in one month buckets from a separate website (http://stats.grok.de). Data was programmatically retrieved here from both sources, and then merged to produce a single time series.
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