Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks
Huseyin Ozdemir and
Physica A: Statistical Mechanics and its Applications, 2022, vol. 604, issue C
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 October 2, 2017 to May 20, 2022. 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 cryptocurrencies cannot be used as diversifiers for emerging stock markets in both the short and long-run. 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 Saudi Arabia, Thailand’s stock markets, and USDT are the main risk transmitters at the 0.95-th quantile during the post-COVID period. Time-varying connectedness estimates confirm the substantial effect of COVID-19. 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. The findings suggest cryptocurrency and emerging market equity portfolios should be closely monitored during financial turmoil.
Keywords: Volatility connectedness; Network analysis; Emerging equity markets; Cryptocurrency; COVID-19 outbreak (search for similar items in EconPapers)
JEL-codes: C32 F42 G15 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122005696
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