Effects of COVID-19 on Cryptocurrency and Emerging Market Connectedness : Empirical Evidence from Quantile, Frequency, and Lasso Networks

We use time and frequency connectedness approaches based on network analysis to investigate the volatility connectedness among 27 emerging equity markets and seven high-capitalized cryptocurrencies. We estimate the network connectedness using the standard, quantile, frequency, and lasso VAR models for the pre- and post-COVID-19 pandemic periods and daily data over the period from June 4, 2018 to April 1, 2021. The network connectedness estimates based on the several models used in this study indicate a growing risk spillover among and within the emerging market equities and the cryptocurrencies after the COVID-19 pandemic hit the world. The frequency connectedness analysis shows that almost all the cryptocurrencies can be used as diversifiers for emerging stock markets in the long run. However, their short- run diversification role only exists during the COVID-19 outbreak. The empirical findings from the quantile VAR model reveal that the volatility connectedness in the tails is much stronger compared to the center of the distribution. It is also evident that all the system risks flow towards a few hub points at the 0.95-th quantile. Our study also shows that the spread of risk among these financial markets is global rather than regional, supporting cross-border structure and worldwide financial market integration