A Time-Varying Network for Cryptocurrencies

Li Guo, Wolfgang Karl H\"ardle and Yubo Tao

Papers from arXiv.org

Abstract: 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.

Date: 2018-02, Revised 2022-11
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: A Time-Varying Network for Cryptocurrencies (2021)
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