Cryptocurrency Networks for Diversification and Cross-Asset Momentum

Summary

This study builds a time-varying network of cryptocurrencies using two types of information: cross-predictability in returns and technological similarity. It applies a dynamic covariate-assisted spectral clustering method to estimate groups, or communities, as the network evolves. The analysis frames these communities as useful for understanding how risk may spread and how the market may be segmented.

The authors report that portfolios holding cryptocurrencies from different communities can achieve better risk diversification. They also report a cross-sectional cryptocurrency momentum portfolio return of 1.08% per day and say behavioral-factor analysis does not explain the result. The description does not specify the sample period, assets, portfolio construction, trading costs, or uncertainty around the return estimate. Those omissions make it difficult to judge whether the reported performance would persist or be attainable after implementation costs.

Key ideas

• The network groups cryptocurrencies using return cross-predictability and technological similarity.
• A dynamic spectral clustering method estimates communities as the network changes.
• The authors suggest that diversifying across communities can improve risk diversification.
• A cross-sectional crypto momentum portfolio is reported to earn 1.08% daily.
• Behavioral-factor analysis is presented as evidence that the reported returns are not driven by those mechanisms.

Tags

# A Time-Varying Network for Cryptocurrencies


# A Time-Varying Network for Cryptocurrencies









Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based on the evolution of return cross-predictability and technological similarities. We develop a dynamic covariate-assisted spectral clustering method to consistently estimate the latent community structure of cryptocurrencies network that accounts for both sets of information. We demonstrate that investors can achieve better risk diversification by investing in cryptocurrencies from different communities. A cross-sectional portfolio that implements an inter-crypto momentum trading strategy earns a 1.08% daily return. By dissecting the portfolio returns on behavioral factors, we confirm that our results are not driven by behavioral mechanisms.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.