Dynamic Factor Models With Macro, Frailty, and Industry Effects for U.S. Default Counts: The Credit Crisis of 2008
构建了一个高维非线性动态因子模型，将系统性违约风险分解为宏观经济、脆弱性和行业效应三部分，发现约35%的违约率变动由系统性和行业因素解释，其中脆弱性效应在金融危机前后尤为显著。
We develop a high-dimensional, nonlinear, and non-Gaussian dynamic factor model for the decomposition of systematic default risk conditions into latent components for (1) macroeconomic/financial risk, (2) autonomous default dynamics (frailty), and (3) industry-specific effects. We analyze discrete U.S. corporate default counts together with macroeconomic and financial variables in one unifying framework. We find that approximately 35% of default rate variation is due to systematic and industry factors. Approximately one-third of this systematic variation is captured by the macroeconomic and financial factors. The remainder is captured by frailty (40%) and industry (25%) effects. The default-specific effects are particularly relevant before and during times of financial turbulence. We detect a build-up of systematic risk over the period preceding the 2008 credit crisis. This article has online supplementary material. © 2012 American Statistical Association.