Cryptocurrency Connectedness : Does Controlling for the Cross-Correlations Matter?

A growing literature has employed the existing generalized spillover measures of Diebold and Yilmaz (2012, 2014) to measure the connectedness—or market integration—of cryptocurrencies. This method, while useful, does not properly control for the cross-correlations of the cryptocurrencies when computing aggregate spillovers from all others to any given cryptocurrency, whereas the joint spillover method of Lastrapes and Wiesen (2021) does. This paper further describes the novel multivariate conditioning sets employed by the joint spillover method. By employing these two techniques and evaluating the differences in the results, we demonstrate that controlling for the cross-correlations of cryptocurrencies matters for measuring aggregate spillovers and the overall connectedness of the cryptocurrency market. Using data on nine of the most traded cryptocurrencies, we find that the generalized spillover index overestimates overall connectedness by about ten percentage points relative to the new joint spillover index. This difference varies across time and is not uniform across cryptocurrencies