Purpose: Cryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market....

We use quantile regressions to demonstrate that volatility persistence and the asymmetric "leverage" effect are high volatility phenomena. More specifically, we find that (i) low volatility is not persistent, but high volatility all the more, even featuring properties of explosive processes;...

Trading of Bitcoin is spread about multiple venues where buying and selling is offered in various currencies. However, all exchanges trade one common good and by the law of one price, the different prices should not deviate in the long run. In this context we are interested in which platform is...

We propose a regression-based algorithm that allows to construct arbitrarily many comparable, multi-annual, consistent time series on monthly, weekly, daily, hourly and minute-by-minute search volume indices based on the scattered data obtained from Google Trends. The accuracy of the algorithm...

We study how retail investor attention influences the joint evolution of cryptocurrency prices. The co-movement is measured using realized correlation and a R-squared-based measure. We find that rising attention as proxied by Google search volume indices or Twitter tweet counts Granger-causes an...

The aim of this study is to provide a comprehensive description of the dependence pattern of stock returns by studying a range of quantiles of the conditional return distribution using quantile autoregression. This enables us in particular to study the behavior of extreme quantiles associated...