Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions
提出一个基于市场的框架，利用时变参数向量自回归模型估计金融溢出效应的动态网络，并应用于标普500指数中的金融公司，在行业和机构层面衡量关联性。
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.