Covid-19 Pandemic and Tail-Dependency Networks of Financial Assets

Le, Trung H.; Do, Hung Xuan; Nguyen, Duc Khuong; Sensoy, Ahmet

This study provides evidence on the frequency-based dependency networks of various financial assets in the tails of return distributions given the extreme price movements under the exceptional circumstance of the Covid-19 pandemic, qualified by the IMF as the Great Lockdown. Our results from the quantile cross-spectral analysis and tail-dependency networks show increases in the network density in both lower and upper joint distributions of asset returns. Particularly, we observe an asymmetric impact of the Covid-19 because the left-tail dependencies become stronger and more prevalent than the right-tail dependencies. The cross-asset tail-dependency of equity, currency and commodity also increases considerably, especially in the left-tail, implying a higher degree of tail contagion effects. Meanwhile, Bitcoin and US Treasury bonds are disconnected from both tail-dependency networks, which suggests their safe-haven characteristics.