Modeling the Dynamics of Credit Spreads with Stochastic Volatility
构建了一个双因子仿射模型，将信用利差的水平和波动率作为两个随机因子，结合无风险利率的双因子模型，用扩展卡尔曼滤波估计108家公司债券价格，发现该模型拟合和预测误差均低于标准模型，并能捕捉信用利差的随机波动和正偏态特征。
This paper investigates a two-factor affine model for the credit spreads on corporate bonds. The first factor can be interpreted as the level of the spread and the second factor is the volatility of the spread. The riskless interest rate is modeled using a standard two-factor affine model, thus leading to a four-factor model for corporate yields. This approach allows us to model the volatility of corporate credit spreads as stochastic, and also allows us to capture higher moments of credit spreads. We use an extended Kalman filter approach to estimate our model on corporate bond prices for 108 firms. The model is found to be successful at fitting actual corporate bond credit spreads, resulting in a significantly lower root mean square error than a standard alternative model both in sample and out of sample. In addition, key properties of actual credit spreads such as the stochastic volatility of the credit spreads and the positive skewness of the credit spread distribution are better captured by the model.