Measuring systemic risk with a dynamic copula-based approach

This study examines the extent of systemic risk embedded in the credit and equity markets using a conditional value-at-risk (CoVaR) measure. We implement a copula-based CoVaR approach with different perspectives of a dependence structure based on a generalized autoregressive score model. In parallel, we select the credit default swap spread and stock price data of five companies in the financial sector ??? American Express, BBVA, Goldman Sachs, Morgan Stanley, and Wells Fargo ??? from 2001 to 2013, and include data on the global financial crisis of 2007???2008. We then divide the data into three time periods: pre-crisis, during the crisis, and post-crisis. We conduct time-varying marginal modelling, and copula parameter estimation, and then compute CoVaR values with the best-fit copula model. Comparative empirical tests provide financial implications for systemic risk management