Cryptocurrency markets have much larger tail risk than traditional financial markets, and
constructing portfolios with such large tail risk assets would be challenging. Therefore …

We document characteristics-based return anomalies in a large cross-section (> 4,000) of
crypto assets. Cryptocurrency returns exhibit momentum in the largest-cap group, reversals …

Investor sentiment is widely recognized as the major determinant of cryptocurrency prices.
Although earlier research has revealed the influence of investor sentiment on cryptocurrency …

This paper examines the role of the information disclosed on blockchains in the
cryptocurrency market. We find that blockchain disclosure on user adoption, measured as …

The valuation of cryptocurrencies is important given the increasing significance of this
potential asset class. However, most state-of-the-art cryptocurrency valuation methods only …

The asset pricing literature documents a growing list of predictable patterns in the cross-
section of cryptocurrency returns. But can they be forged into viable trading profits? We …

We employ a repertoire of machine learning models to investigate the cross-sectional return
predictability in cryptocurrency markets. While all methods generate substantial economic …

Motivated by recent findings from the equity market, we investigate non-standard errors in
cryptocurrency research. We examine ten prevalent decisions related to data sources …

We investigate the dynamics of returns in cryptocurrency markets through the lens of a small-
scale latent factor model with time-varying factor loadings instrumented by individual …

We investigate interaction effects in cryptocurrency markets by constructing and evaluating
double-sorted portfolios based on 40 different characteristics. Using a dataset of over 500 …