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

Abstract

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.

Note: N.B. The full article appears in the Journal of Financial and Quantitative Analysis published by Cambridge University Press. © 1995-2018, Foster School of Business, University of Washington

Keywords: financial interconnectedness, time-varying parameter, systemic risk

JEL Classification: G01, G18, C32, C51, C58