Yubo Tao, Assistant Professor in the Department of Economics in the Faculty of Social Sciences at University of Macau, has published his latest article “A Time-Varying Network for Cryptocurrencies” (team includes Li Guo and Wolfgang Karl Härdle) in the top international journal ‘Journal of Business & Economic Statistics’. Based on the evolution of return cross-predictability and technological similarities, they build a time-varying network for cryptocurrencies.
The team developed a dynamic covariate-assisted spectral clustering method to consistently estimate the latent community structure of cryptocurrencies network that accounts for both sets of information. They 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, the team confirms that their results are not driven by behavioral mechanisms.
For more information: https://www.tandfonline.com/doi/abs/10.1080/07350015.2022.2146695?journalCode=ubes20