Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms
用高频数据识别个股的跳跃，发现波动率风险能解释50%的CDS利差变化，跳跃风险能解释19%，加入控制变量后解释力达77%，且对高收益债券影响更大。
A structural model with stochastic volatility and jumps implies particular relationships between observed equity returns and credit spreads. This paper explores such effects in the credit default swap (CDS) market. We use a novel approach to identify the realized jumps of individual equity from high frequency data. Our empirical results suggest that volatility risk alone predicts 50% of CDS spread variation, while jump risk alone forecasts 19%. After controlling for credit ratings, macroeconomic conditions, and firms' balance sheet information, we can explain 77% of the total variation. Moreover, the marginal impacts of volatility and jump measures increase dramatically from investment grade to high-yield entities. The estimated nonlinear effects of volatility and jumps are in line with the model implied relationships between equity returns and credit spreads.