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

被引:52
作者
Geraci, Marco Valerio [1 ,2 ]
Gnabo, Jean-Yves [3 ,4 ]
机构
[1] Univ Cambridge, INET Inst, Cambridge, England
[2] Univ Libre Bruxelles ECARES, Brussels, Belgium
[3] Univ Namur CeReHM, Namur, Belgium
[4] Univ Paris Nanterre EconomiX, CNRS, Paris, France
关键词
SYSTEMIC RISK; MONETARY-POLICY; CONNECTEDNESS; REGRESSION; MODELS;
D O I
10.1017/S0022109018000108
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:1371 / 1390
页数:20
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