Introduction

Prepayment modeling plays a critical role in the analysis and valuation of mortgage-backed securities (MBS). It involves predicting the rate at which borrowers will pay off their mortgages ahead of schedule. This prediction is essential for investors and financial institutions to assess the cash flow dynamics of MBS investments. Prepayment modeling comprises four key components: refinancing, turnover, defaults, and curtailments. Understanding these components is crucial for accurately estimating the future cash flows associated with mortgage-backed securities.

Refinancing

Refinancing refers to the process where borrowers replace their existing mortgage loans with new loans that usually have more favorable terms. Borrowers often refinance when interest rates decrease, allowing them to secure lower monthly payments or reduce the overall interest expense. This leads to higher prepayment rates during periods of declining interest rates. A common measure used to quantify refinancing is the Refinance Rate (RR):

$$RR=\frac{\text { Number of Refinancing Mortgages }}{\text { Total Number of Mortgages }} \times 100$$

Example: If out of a pool of 1000 mortgages, 150 mortgages are refinanced within a year, the Refinance Rate would be

$$RR=\frac{150}{1000} \times 100=15 %$$

Turnover

Turnover refers to the rate at which homeowners sell their properties and pay off their mortgages. Economic conditions and individual circumstances significantly influence turnover rates. Higher turnover rates are observed in regions with a volatile real estate market or areas experiencing economic growth. Turnover rates tend to decrease during periods of economic uncertainty or when property values are stagnant.

Example: In a neighborhood with 200 homes, if 10 homes are sold within a year, the Turnover Rate would be:

$$\text{Turnover Rate = } \frac{10}{200} \times 100 = 5% $$

Defaults

Defaults occur when borrowers are unable to make their mortgage payments and subsequently default on their loans. Economic downturns, job loss, or personal financial crises can contribute to higher default rates. Default rates are influenced by factors such as borrower credit quality, loan-to-value ratios, and economic conditions.

Example: If 20 out of 500 mortgages in a pool result in defaults within a year, the Default Rate would be:

$$\text{Default Rate = } \frac{20}{500} \times 100 = 4% $$

Curtailments

Curtailments involve borrowers making extra principal payments, which effectively reduces the outstanding loan balance. This reduces the time it takes for the loan to be fully paid off. Curtailments can vary widely based on borrower behavior, economic conditions, and incentives provided by mortgage servicers.

Example: If borrowers in a pool make additional principal payments totaling USD 500,000 in a year,the Curtailment Amount would be USD 500,000.