Glossary/Fixed income

Prepayment Risk

Also known as Early-repayment risk

Prepayment risk is the possibility that borrowers return principal earlier or at a different pace than expected, changing an investment’s cash-flow timing and realized return.

Editorially reviewed 2026-07-30

Why prepayment risk matters

It is central to mortgages and other amortizing assets because prepayments often accelerate when rates fall, forcing reinvestment at lower yields and limiting price appreciation.

How it is applied

Analysts model refinancing incentive, borrower characteristics, loan age, seasonality, housing turnover, burnout, penalties, rates, and economic scenarios, then estimate duration and cash flow by path. Mortgage and loan models project borrower prepayments as functions of rates, seasoning, housing turnover, credit, and incentives. Investors examine how faster and slower speeds change yield, average life, and reinvestment. Scenario ranges matter more than one forecast.

Portfolio example

Mortgage rates fall and homeowners refinance. An MBS investor receives principal sooner than expected and must reinvest it at lower rates. An investor buys a premium mortgage security at 105. If borrowers refinance quickly, principal returns near 100 sooner than expected, crystallizing the premium loss and forcing reinvestment at lower yields.

How to interpret it

Faster prepayment can be unfavorable for premium securities, while slower prepayment can extend duration when rates rise. The effect depends on price and portfolio objective. Falling rates often accelerate prepayments and limit upside, creating negative convexity. Rising rates can slow payments and extend duration. Discount securities may benefit from faster return of principal, unlike premium securities.

Limitations and common misconceptions

Borrower behavior is difficult to forecast and changes with underwriting, technology, regulation, home prices, and credit availability. Models calibrated to one cycle can fail in another. Borrower behavior, policy programs, servicing, housing mobility, burnout, and underwriting change over time. Models trained on one regime can fail. Prepayment and credit risks also interact because weaker borrowers may be unable to refinance. Analysts should report weighted average life and yield across several prepayment speeds, not only a base case. Pools with similar coupons can behave differently because borrower credit, geography, loan age, and refinancing friction differ. Hedging is challenging because duration extends as rates rise and contracts as rates fall. This changing sensitivity must be reflected in both valuation and liquidity planning. Model assumptions should be refreshed when borrower incentives or refinancing channels change.

Sources and further reading