Salon 2
Varying-Coefficient Regression Models with Application to Stress Test (303189)
Jie Chen, Wells Fargo*Qiyi Lu, Wells Fargo
Agus Sudjianto, Wells Fargo
Hanyu Yang, Wells Fargo
Keywords: stress test, credit risk modeling, varying-coefficient model, nonparametric estimation, smoothing spline
In financial institutions, stress test models are built to translate different economic scenarios into losses, expenses, or revenues, and then used to determine capital requirements under baseline and stressed economic conditions. In some stress test models, the dynamics being modeled could vary over multiple dimensions of time such as vintage, calendar time, and account age (month on book). It is of interest to account for these time dimensions simultaneously to produce a better model than traditional techniques that consider only one dimension. We propose a general framework of varying-coefficient model for pool-level credit data. The proposed model framework allows coefficients to change smoothly over a time dimension such as loan age for each loan vintage, thus providing better interpretation of the maturation effect and macroeconomic conditions. It is a nonparametric framework, and existing nonparametric smoothing techniques can be used to construct an estimation procedure. Empirical analyses on indirect auto stress test are used to illustrate the proposed method and show the usefulness and advantage of the approach.