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

Marco Valerio Geraci () and Jean-Yves Gnabo ()

Journal of Financial and Quantitative Analysis, 2018, vol. 53, issue 3, 1371-1390

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 sectoral and institutional levels. At the sectoral 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 institutional level, our framework delivers more stable interconnectedness rankings than other comparable market-based measures.

Date: 2018
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Working Paper: Measuring interconnectedness between financial institutions with Bayesian time-varying vector autoregressions (2015) Downloads
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