Abstract
A non-parametric technique called generalized additive model (GAM) estimation is particularly useful in high-dimension non-parametric estimations and in situations that involved mixed parametric and non-parametric specifications. The relationship between prepayment rates, and variables such as the age of the mortgage, the ratio of the mortgage coupon rate and prevailing interest rates, and expected and unexpected burnouts is highly non-linear, and it is difficult to capture these relations with parametric functions. Decomposition of pool burnouts into expected and unexpected components improves the model fit and has important pricing implications. The prepayment model estimated here fits the data significantly better than other models in use, and illustrates the factors that affect prepayments and the prices of mortgage-backed securities.
- © 2000 Pageant Media Ltd
Don’t have access? Click here to request a demo
Alternatively, Call a member of the team to discuss membership options
US and Overseas: +1 646-931-9045
UK: 0207 139 1600