A time-varying copula approach for constructing a daily financial systemic stress index

This paper develops a financial systemic stress index (FSSI) for the US financial market. We propose a time-varying copula method to model the dependence structure among financial sectors in order to build a correlated financial stress model that can signal systemic financial risks. The copula method is preferable to the traditional approach, enabling the modeling of non-linear correlations. Our analyses show that the dependencies across banking, security, and forex markets are best modeled by Archimedian copulas. Finally, we conduct a Markov Switching Autoregressive (MS-AR) model for FSSI and identify high financial stress episodes taking place in 2008-2009, 2011 and 2020.