We investigate the performance of funds that specialise in cryptocurrency markets and contribute to a growing literature that aims to understand the value of digital assets as investments. The main empirical results support the idea that cryptocurrency funds generate significantly alphas...

We provide empirical evidence within the context of cryptocurrency markets that the returns from liquidity provision, proxied by the returns of a short-term reversal strategy, are primarily concentrated in trading pairs with lower levels of market activity. Empirically, we focus on a moderately...

This paper proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. stocks and bonds. The model assumes that risk exposures and idiosynchratic volatility follow a break-point...

We use Bayesian methods to estimate a multi-factor linear asset pricing model characterized by structural instability in factor loadings, idiosyncratic variances, and factor risk premia. We use such a framework to investigate the key differences in the pricing mechanism that applies to...

We study the cross-sectional correlation between the returns on stablecoins and major cryptocurrency pairs. In doing so, we contribute to a growing literature that aims to understand the role of digital assets as an investment. Methodologically, we propose a large-scale Bayesian Vector...

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 panel bootstrap approach that samples jointly the...