Crypto Chase referred to the implications of sudden erratic price movements on exchanges, these serving to liquidate traders who should have retained their positions.
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.

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Identifying the determinants of asset prices is one of the most important questions in finance. Traditional asset pricing theories are founded on the idea that equity prices should be determined by fundamentals such as earnings (Gordon 1959, Campbell and Shiller 1988). In contrast, the behavioral finance literature posits that prices do not always follow fundamentals due to investor sentiment trading (Shiller 1981, Baker and Wurgler 2006, Stambaugh et al. 2012). Eventually however, equity prices seem to trace their fundamentals (Pa´stor and Veronesi, 2003, 2006, Bartram and Grinblatt 2018).