Cryptocurrency Networks for Diversification and Cross-Sectional Momentum

Summary

The study builds a changing cryptocurrency network using two kinds of links: return cross-predictability and technological similarity. It applies a dynamic covariate-assisted spectral clustering method to estimate communities while accounting for both sources of information. The network is intended to reveal how risk may propagate and where the market is segmented.

The document reports that diversification across different estimated communities can improve risk diversification. It also describes a cross-sectional crypto momentum portfolio with a reported daily return of 1.08%, and says behavioral-factor analysis did not explain the portfolio returns. The excerpt does not specify the sample, costs, implementation details, or robustness checks, so the stated return alone is insufficient to assess real-world performance.

Key ideas

• Cryptocurrency links are estimated from return predictability and technological similarity.
• Dynamic covariate-assisted spectral clustering is used to infer changing network communities.
• The communities are presented as useful for understanding risk propagation and segmentation.
• The study reports diversification benefits from holding assets in different communities.
• A cross-sectional inter-crypto momentum portfolio is reported to return 1.08% daily, with behavioral factors not explaining its returns.

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.