Prof. Yubo Tao and his co-authors published their article “A Time-Varying Network for Cryptocurrencies” in Journal of Business & Economic Statistics. Journal of Business & Economics Statistics was found in 1983. It is a reputable academic journal (ABS4 and ABDC [A*]) managed by the American Statistical Association. The journal publishes approximately 60 articles a year.
A Time-Varying Network for Cryptocurrencies (By Li Gu, Wolfgang Karl Härdle & Yubo Tao)
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.