Analysis of Financial Contagion among Economic Sectors through Dynamic Bayesian Networks

Crises severely impact various economies and may spread across regions or sectors in a process called contagion. Understanding this process allows foreseeing crises’ impacts and anticipating actions that reduce their effects. Specific economic sectors may be major crisis propagators: banking and insurance are often considered decisive in this context. In this paper, we aim to model the U.S. economy’s sectorial interdependence using Dynamic Bayesian Networks on nine industrial Dow Jones’ indices, daily between 2000 and 2020. As a secondary objective, we evaluate whether the insurance industry plays a central role in spreading crises. Several crisis periods are analyzed, from dot-com bubble to current Covid-19 pandemic. The results reveal the subprime crisis, European debt crisis and the 2016 presidential election as the main contagious periods. The last analyzed period – Covid-19 pandemic – was divided in two phases, showing, on phase 1, an interconnected economic system with three main spreaders (Oil & Gas, Real Estate and Pharmaceutical) and, on phase 2, the same configuration of the post-subprime. Finally, despite being somehow relevant during the subprime crisis, the premise of the insurance sector’s centrality relative to other economic sectors was proven false, as this sector reveals to be one of the main contagion receptors.

Find the Q&A here: Q&A on 'Macro Issues Affecting Financial Markets'