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Analysis of cryptocurrency connectedness based on network to transaction volume ratios


Network to Transaction (NVT) ratio is a measure that describes the relationship between transaction volume and market capitalization, and that may serve as an indicator for the valuation of a cryptocurrency. We build a connectedness network connecting 39 cryptocurrencies based on mutual contributions to the variances of forecast errors for NVT ratios. We find that NVT connectedness is not related to market capitalization, as we have large and small cryptocurrencies by market cap that propagate large NVT shocks (e.g. Litecoin, Dogecoin, Bitcoin Cash(bch), OMG Network and Decentraland). The largest transmitter of NVT shocks is OMG Network, which receives little public attention. Cryptocurrencies relying on proof of stake as a consensus mechanism are the smallest receivers of NVT spillovers from other cryptocurrencies. These assets are also the least interconnected, which makes them attractive from a risk diversification point of view. This complements the energy efficiency of PoS compared with proof of work.

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Correspondence to Christian M. Hafner.

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See Tables 3 and 4.

Table 3 The 39 cryptocurrencies with their symbols, market capitalizations (MCs) and rankings by MCs
Table 4 NVT descriptive statistics during the period from 15 November 2018 to 16 February 2021

See Figs. 9, 10, 11, 12, 13 and Tables 5 and 6.

Fig. 9
figure 9

ACF plots for 9 NVT series

Fig. 10
figure 10

ACF plots of 9 NVT series after removing seasonality

Fig. 11
figure 11

Correlation between different NVT ratios of cryptocurrencies

Fig. 12
figure 12

Estimated coefficients of the VAR(3)-LASSO model

Fig. 13
figure 13

Correlation in the residuals of the estimated VAR-LASSO model

Table 5 Results of the ADF stationarity test, where the critical value 5% is − 2.865
Table 6 P_values for the Ljung-Box test on the residuals of the VAR-LASSO model

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Hafner, C.M., Majeri, S. Analysis of cryptocurrency connectedness based on network to transaction volume ratios. Digit Finance (2022).

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  • Vector autoregressions
  • ICA
  • Networks
  • Cryptocurrencies

JEL Classification

  • C14
  • C43
  • Z11