Abstract
This paper explores whether asset market equilibria in cryptocurrency markets do exist. In doing so, it distinguishes between privacy and non-privacy coins. Most recently, privacy coins have attracted increasing attention in the public debate as non-privacy cryptocurrencies, such as Bitcoin, do not satisfy some users’ demands for anonymity. Analyzing ten cryptocurrencies with the highest market capitalization in each submarket in the 2016–2018 periods, we find that privacy coins exhibit a distinct market equilibrium. Contributing to the current debate on the market efficiency of cryptocurrency markets, our findings provide evidence of market inefficiency. Moreover, the asset market equilibrium of privacy coins appears to originate from non-privacy coins with highest market capitalizations. We argue that the reason for this finding could be that non-privacy coins may be the first choice for criminals who might prefer cryptocurrencies exhibiting both a high level of anonymity and liquidity.
Highlights
Empirical investigations of cryptocurrency markets have attracted considerable attention in the academic literature
We explore whether market equilibria in cryptocurrency markets exist which, in turn, would imply the existence of submarkets
Our results provide some new evidence on market heterogeneity: Privacy coins with high market capitalizations appear to build a submarket of cryptocurrencies as they form their own market equilibrium that is unrelated to the remaining cointegration equilibria in the cryptocurrency market
Summary
Empirical investigations of cryptocurrency markets have attracted considerable attention in the academic literature. Alexander and Dimitriu (2005) investigate the performance of a cointegration-based index tracking strategy and, by this, test the Efficient Market Hypothesis (EMH), as according to Jensen’s (1978) definition of efficient markets, a trading strategy producing significant risk-adjusted payoffs is evidence against the EMH. Our paper contributes to the literature on testing the market efficiency of cryptocurrency markets using cointegration theory (Engle and Granger’s, 1987)
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