PD modelling:

a. Estimate a basic credit risk model for mortgage default probabilities (PD) (you may choose a logit or a probit model). Include the feature set. Compute the estimated PD for all mortgage loans and periods. Plot and compare the average probability of default and default rate over time and over each feature (four charts). Provide your code, output for the model and interpret the output.

b. Estimate the PD model again by including a transformation for every variable of the feature set that results in a better model accuracy. You may use splines, polynomial terms or other transformations (chapter 6 of textbook may help). Compute the estimated PD for all mortgage loans and periods. Plot and compare the average probability of default and default rate over time and over each feature (four charts). Provide your code, an output for the model, the plots and interpret the output. Explain the reason for your transformation

b. Compare the accuracy of two models from sub-questions 2A and 2B. Present and explain your findings with regard to model accuracy?