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• W3183439181 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." @default.
• W3183439181 created "2021-08-02" @default.
• W3183439181 creator A5024731494 @default.
• W3183439181 creator A5053742635 @default.
• W3183439181 creator A5088979876 @default.
• W3183439181 date "2018-02-11" @default.
• W3183439181 modified "2023-10-18" @default.
• W3183439181 title "A Time-Varying Network for Cryptocurrencies" @default.
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• W3183439181 doi "https://doi.org/10.48550/arxiv.1802.03708" @default.
• W3183439181 hasPublicationYear "2018" @default.
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