By the Numbers
Improving returns with small loans from fast states
This document is intended for institutional investors and is not subject to all of the independence and disclosure standards applicable to debt research reports prepared for retail investors. This material does not constitute research.
MBS investors stand to boost returns by finding pools backed by smaller loans from states with high housing turnover. Smaller loans also tend to turnover more frequently than larger loans, and rates of housing turnover rates vary greatly from state to state. Investors in pools trading below par can combine the two factors—small loans from fast states. Prepayment speeds can vary by 2 CPR or more between fast and slow states in low-loan-balance collateral—a significant difference when the average speed is 5 CPR or 6 CPR. And these loans still the protection from refinancing afforded by smaller loan size.
Prepayment speeds over the last year have ranged from 6.0 CPR to 6.2 CPR in the median states for loans with balances between $100,000 and $200,000 (Exhibit 1). This range encompasses most of the lowest loan balance specified pool categories. I grouped the states into nine buckets based on prepayment speeds; the middle bucket (light yellow) includes the median state. States that are faster than median are colored red, and those that are slower than median are colored blue. There are sizeable differences across states. The fastest group of states ranged from 7.1 CPR to 7.4 CPR, and the slowest states from 3.9 CPR to 5.5 CPR.
Exhibit 1. Speeds over the last year for loans with $100,000-$200,000 balances
Source: Fannie Mae, Freddie Mac, Santander US Capital Markets
Since the market is trading almost entirely at a discount to par, these speeds are dominated by housing turnover. There is still a little cash-out refinance activity, probably from borrowers that still benefit from debt consolidation and cannot get approved for a second lien. The hottest states were in the Southeast and a few Upper Plains states, followed by several Midwestern and Southwestern states. The coolest areas were the Northeast, upper Midwest, California and Oregon.
Loans sized $200,000 to $300,000 generally prepaid slower than the smaller loans but showed similar variations across states (Exhibit 2). The median bucket of states prepaid 4.9 CPR to 5.1 CPR, about 1 CPR slower than the median speed of the lower balance loans. There was a similar swing between the fastest and slowest states as seen in the smaller balance loans—the fastest states prepaid about 1 CPR faster than the median states, and the slowest states about 1 CPR slower than the median states. The faster and slower states were similar between the smaller and larger loans.
Exhibit 2. Speeds over the last year for loans with $200,000-$300,000 balances
Source: Fannie Mae, Freddie Mac, Santander US Capital Markets
The geographic differences are comparable in size to the differences due to loan size. For example, the median state in the lower balance group prepaid roughly 6 CPR and the median state in the higher balance group prepaid roughly 5 CPR—a 1 CPR difference. That is the same difference seen between the median states and the fastest states in each of those groups. Selecting the right states can have as large an impact as moving down in loan size.
A major driver of housing turnover is home price appreciation (Exhibit 3). This shows home price appreciation by state for the 24 months preceding the past year. The states with higher HPA tend to also be the states that showed faster prepayments over the last year, and the lower HPA states tend to be the slower prepaying states.
Exhibit 3. State-level home price appreciation From Dec 2020 to Nov 2022.
Source: Core Logic, Santander US Capital Markets
Home prices increases can fuel housing turnover. Since borrowers have made a levered investment in their home, their home equity grows faster than home prices. That makes it possible for people to trade up to larger, more expensive, homes and keeps turnover higher than in weaker markets. Areas with net in-migration, like the Southeast, often benefit the most from this effect. And areas with net out-migration, like the Northeastern states and California, typically have cooler housing markets with less turnover and lower home price appreciation.
Investors can add extension protection to pools by concentrating on states that are projected to have greater home price appreciation. The prepayment data shows that this can work on existing specified pool categories, like low loan balance, that originators are already used to pooling separately. This article suggests an approach for selecting those states using recent home price appreciation measures, but it could also be done using a home price model or based on expected migration patterns.
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