Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions

We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor's 500 index and estimate interconnectedness at the sector and institution level. At the sector level, we uncover two main events in terms of interconnectedness: the Long Term Capital Management crisis and the 2008 financial crisis. After these crisis events, we find a gradual decrease in interconnectedness, not observable using the classical rolling window approach. At the institution level, our framework delivers more stable interconnectedness rankings over time than other market-based measures of systemic risk.