This paper analyses the volume-return relationships across the top 30 most traded cryptocurrencies from April 2013 to June 2019 using high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as...

The main aim of the paper is to study and determine the optimal sampling frequency for modelling cryptoasset volatility. For that purpose, the noise-to-signal ratio is estimated for six selected cryptoassets, separately for each month of existance on Kraken exchange. The minimal noise-to-signal...

In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-tradable crypto assets using high-frequency data for the period from January 2019 to December 2020. We apply the Diagonal-BEKK model to data from the pre-COVID and COVID-19 periods, and identify...