Measuring Systemic Risk: Common Factor Exposures and Tail Dependence Effects
构建了一个包含共同因子和尾部依赖因子的模型来测量系统性风险，发现忽略尾部依赖因子会导致风险低估，且加入该因子的指标能更好预测金融压力。
Abstract We model systemic risk using a common factor that accounts for market‐wide shocks and a tail dependence factor that accounts for linkages among extreme stock returns. Specifically, our theoretical model allows for firm‐specific impacts of infrequent and extreme events. Using data on the four sectors of the US financial industry from 1996 to 2011, we uncover two key empirical findings. First, disregarding the effect of the tail dependence factor leads to a downward bias in the measurement of systemic risk, especially during weak economic times. Second, when these measures serve as leading indicators of the St. Louis Fed Financial Stress Index, measures that include a tail dependence factor offer better forecasting ability than measures based on a common factor only.