We investigate the performance of funds that specialise in cryptocurrency markets. In doing so, we contribute to a growing literature that aims to understand the role of digital assets as an investment. Methodologically, we implement a novel bootstrap approach that samples jointly the cross-sectional distribution of alphas and controls for the nonnormality of fund returns and their within-strategy correlations. Empirically, we find that a sizable minority of managers are able to cover their costs and generate large alphas. However, there is weak statistical evidence of managers' skills once withinstrategy common variation in returns is taken into account.

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ISBN 978-80-7343-413-7 (Univerzita Karlova, Centrum pro ekonomický výzkum a doktorské studium) ISBN 978-80-7344-449-5 (Národohospodářský ústav AV ČR, v. v. i.) AbstractThis paper provides a generalized disappointment aversion (GDA) interpretation of the variance and skew risk premia in equity returns and the volatility skew in equity index options. The key ingredients are Bayesian learning about a hidden consumption growth rate and the investor's tail aversion induced by GDA preferences which amplify the impact of consumption shocks. This model with disappointment risk reproduces salient properties of the variance and skew risk premia and generates a realistic volatility skew implied by index options, while simultaneously matching the mean and volatility of risk-free rate and equity returns, and the level of the price-dividend ratio. Additionally, the time-varying probability of disappointment events generates a wide range of dynamic asset pricing phenomena.

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