1. Smith Barney Prepayment Model Nadine Kwiatkowski Mladen Mrkaic

2. Model Overview and Assumptions Technical Analysis – Past to Future Predictions Two Characteristics: - Fundamental relationships persist over time - Understandable and highly correlated assumptions

3. Model Structure Components are well-known prepayment causes Applies to all mortgage types Component is well formulated and depends in a logical variables Component’s relationships can be easily modified

4. Pre-payment Causes Home sales Refinancing Defaults Partial Prepayments (Curtailments) Full payoffs

5. Smith Barney Model “Demonstrates comprehensive approach in incorporating the different reasons for prepayments and uses fundamental and hence long-lasting relationships between variables and prepayments rates shows to be reliable over time.”

6. Sub-Models Variables Home Turnover and Refinancing Sales of Existing Homes (leads to a prepayment) - 5% and 7% in past – factors: mortgage rates and economic expansion Projected Housing Turnover – based on mortgage rates (15 yrs) Seasonal Variation in Home Sales (winter vs summer) Refinance Incentive – C/M*1-((1+M) -(term-age) )/(1-(1+C) -term) -1 Statistically explained by: - Diverse pool of mortgagors - Evolution of the pool over time - The media effect and the migration of borrowers

7. Housing Turnover Specific loan/borrower characteristics affect prepayment speeds The Seasoning Process Percentage of refinanced loans in the pool Greater % of refinancing = faster seasoning process

8. Housing Turnover The “points” effect Low-points and No-points Higher rate, lower down payment, fast refinancers High-points Put down points, borrower intention to stay. Putting down “roots”

9. Housing Turnover The “Lock-in” Effect Disincentive to move Dependant on factors other than age Function of two quantities: 1-C/M*1-(1+M_-(term-age) 1-(1+C)-term (1+C)^term – (1+C)^age INF*[(1+C)^term-1] Function of coupon differential between loan rate and current rates, diminishes over time

10. Housing Turnover Housing Inflation affects a homeowner’s ability to move. Rapid price appreciation leads to “trade up” moves. Price depreciation dampens ability Geographical factors Regional economic conditions on prepayment Loan Type Adjustable Rates vs. Fixed Rates

11. Refinancing Behavior High prepayment speeds are primarily due to refinancing Burnout-refinancing rates decline over time Effect of Relative Loan Size Slower response to refinancing incentive of very seasoned loans Fixed costs of refinancing, paperwork/hassle Results in smaller incentive to refinance a low- balance loan

12. Refinancing Behavior Seasoning Patterns for Newer Loans Newer loans taken out more recently also “dampen” refinancing rates Sufficient incentives can still result in accelerate prepayment speeds.

13. Refinancing Behavior Points effect and Refinancing Higher speeds on newer premiums that are “no-point” or “low- point” Higher coupons are paid to reduce or eliminate refinance costs Minor interest rate drops can trigger incentive to refinance again among “opportunistic” refinancers resulting in elevated prepayments during early years of loans Potential for Misidentification Credit problems resulting in above market rate mortgages Borrowers could not get market rates show slower refinancing rates High points paid to secure below-market rates: Slow seasoning period in housing turnover as well as refinancing

14. Basic Properties of Model Projections Projections are for a specified path of interest rates Variety of interest rate scenarios need to be considered Long Term Projections need to be used with care Long term average speeds can be misleading Noise: Random Component of Speeds Actual speeds will differ from projections Prepayment Risk Partial Prepayment Duration Variables Housing Turnover Rate Refinancing Rate

15. Two Main Factors Affordability - ability to make a monthly mortgage payment Desirability - socioeconomic factor perception of the economic return

16. Conclusion Model is modular (additive for different types of factors), universal (all mortgage types), and transparent (relationships of components are visible to and alterable by the user) and shows relatively stable results over time