Impacts of COVID-19 on Various Financial Assets in Korea : A Bayesian Network Approach

This study conducts an empirical analysis of how the various financial assets in South Korea (stock, bond, exchange rates, Bitcoin, Koribor, gold, and oil) react during the COVID-19 pandemic period using the Bayesian network approach. We consider various asset types together, especially providing the results graphically. Our empirical results show that, first, the Bayesian Networks are useful for analyzing causal relationships among multiple assets. Second, COVID-19 directly or indirectly affects asset markets. In the post-COVID-19 period, network structures are more complex than the pre-COVID-19 period. Third, we apply the Bayesian network to the analysis of submarkets as a robustness check