Stochastic actor-oriented modelling of the impact of COVID-19 on financial network evolution.

Abstract

The coronavirus disease 2019 (COVID‐19) pandemic has led to tremendous loss of human life and has severe social and economic impacts worldwide. The spread of the disease has also caused dramatic uncertainty in financial markets, especially in the early stages of the pandemic. In this paper, we adopt the stochastic actor‐oriented model (SAOM) to model dynamic/longitudinal financial networks with the covariates constructed from the network statistics of COVID‐19 dynamic pandemic networks. Our findings provide evidence that the transmission risk of the COVID‐19, measured in the transformed pandemic risk scores, is a main explanatory factor of financial network connectedness from March to May 2020. The pandemic statistics and transformed pandemic risk scores can give early signs of the intense connectedness of the financial markets in mid‐March 2020. We can make use of the SAOM approach to predict possible financial contagion using pandemic network statistics and transformed pandemic risk scores of the COVID‐19 and other pandemics.