Article ID: | iaor19932125 |
Country: | United States |
Volume: | 38 |
Issue: | 11 |
Start Page Number: | 1665 |
End Page Number: | 1685 |
Publication Date: | Nov 1992 |
Journal: | Management Science |
Authors: | Zenios Stavros A., Kang Pan |
Keywords: | financial, statistics: regression |
The estimation of prepayment rates for pools of mortgages is a critical component in determining the value of mortgage-backed securities-MBS for short-and derivative products. This paper discusses the development of prepayment models for pools of fixed-rate mortgages. The models are complete: calibrated functional forms are given for all the factors that determine prepayment rates. Hence, the models can be used as benchmarks against the simple models of the Public Securities Association, the Federal Housing Administration experience, or the variety of projected prepayment rates generated by proprietary industry models. The key factors that determine prepayment rates are: (1) refinancing incentive, (2) seasonal variations, (3) seasoning of the mortgage pool, and (4) burnout effect. Each factor is modeled separately and is calibrated using historical data. A multiplicative relationship determines the prepayment rate of the mortgage pool. A novel feature of the present model is the use of