Most conversations about prepayment risk start too late

Someone says "mortgages," someone else says "negative convexity," and the room moves on as if the strategy has been defined.

It has not.

A prepayment-risk strategy is not simply a rates trade with mortgage jargon around it. It is a trade on borrower behavior, security design, market structure, and hedging flows. Rates matter, but they are only the first layer. The real question is who has the option, when they are likely to exercise it, how the market prices that option, and what happens when reality diverges from the model.

That matters because the mortgage market is large, technical, and still heavily intermediated. U.S. mortgage balances stood at $13.17 trillion at the end of 2025, and the Federal Reserve still held approximately $1.98 trillion of mortgage-backed securities as of May 6, 2026 — down from a peak of $2.74 trillion, but still large enough to shape the balance between supply and private-sector absorption. Agency MBS issuance reached $727.4 billion year-to-date through April, with daily trading averaging $395.8 billion. This is not a side pocket of fixed income. It is one of the largest optionality markets in the world.

 30-year fixed mortgage rate — weekly average (%) 

Source: Freddie Mac Primary Mortgage Market Survey (PMMS) via FRED · As of May 7, 2026: 6.37% · Peak: 7.79% (Oct 2023) 

What the strategy actually is

Prepayment risk is the risk that a borrower repays principal sooner or later than expected. In mortgages, that usually means a homeowner refinances, sells the house, moves, prepays out of cash flow, or does nothing when the market expected them to act.

That changes the security's cash flows — and with it duration, convexity, carry, hedge ratios, and realised P&L.

The clean way to think about it: the borrower owns an option, and the investor is short it. In plain-vanilla agency MBS, that option is mostly the right to refinance without compensating the investor for the upside they lose when the bond prepays at par. When mortgage rates fall, borrowers are more likely to refinance and the investor's higher-coupon bond disappears faster. When rates rise, prepayments slow and the investor is left owning longer duration than they expected. That is the classic negative convexity problem.

This shows up across a range of instruments: agency MBS, TBAs, specified pools, CMOs, IOs and POs, and mortgage servicing rights. Related expressions appear in non-agency mortgages and certain consumer ABS sectors where call or refinance behavior matters. The strategy label sounds narrow. The implementation range is not.

Why this is not just a rates strategy 

A lot of people stop at "lower rates equal faster prepays." That is directionally true and still incomplete.

The mortgage market has learned, over several cycles, that refinancing incentive is not enough. Two borrowers can face the same rate drop and behave very differently. One refinances immediately. One does nothing. One moves instead. One cannot qualify. One is rate-insensitive because they already missed prior refinance windows and are effectively burned out.

The variables that matter are familiar once you know where to look: coupon, loan size, FICO, loan age, geography, servicer mix, burnout, turnover, housing supply, cash-out demand, and regulation. Fannie Mae's Benchmark CPR framework exists precisely because prepayment behavior needs to be monitored consistently across sellers and servicers. Freddie Mac's weekly Refinance Prepayment Index serves as an early indicator of prepayments for exactly the same reason.

 Federal Reserve agency MBS holdings (US$tn) 

Source: Federal Reserve H.4.1 / FRED (WSHOMCB) · QT ended December 2025 · Holdings ~$1.98tn as of May 2026, down from $2.74tn peak 

The core edge in this space is rarely a strong rates view. It is usually a specific understanding of which loans will behave differently from the cohort — and how that difference is priced.

Where the alpha comes from

The recurring alpha buckets are worth mapping clearly, because managers who claim all of them usually own none.

Security selection is the oldest and still the most important. Some mortgage pools are structurally better or worse than the generic market assumption. The classic examples involve low loan balance, geography, coupon dispersion, servicer behavior, and borrower characteristics. A strong manager is not buying "mortgages." They are buying a very specific kind of borrower behavior at a price they believe is wrong.

Model dispersion is different. Prepayment models are not accounting statements — they are estimates. Different dealers, REITs, banks, and hedge funds can look at the same pool and arrive at different speed projections. That gap creates opportunity. In good times it looks like quiet relative value. In stressed markets it turns into a flow event, because everyone realizes at once that the same apparently hedged book was built on different assumptions.

Optionality mispricing is subtler still. Mortgage optionality is path dependent. A market that prices only the endpoint of rates often misses the path borrowers need to see before they refinance, the operational frictions in doing so, and the fact that the same nominal rate move can produce different behavior depending on housing turnover, credit availability, and prior refinance history. Prepayment specialists do not just ask where rates go. They ask what borrowers do on the way there.

Flow and hedge dislocations are the fourth bucket. The mortgage market is still shaped by large balance-sheet players, benchmark constraints, and hedging conventions. When duration extends or shortens abruptly, convexity hedging can overwhelm valuation for a time. Those episodes are where experienced specialists often make their best returns — not because they forecast every rate move, but because they know when hedging pressure is technical rather than fundamental.

Servicing and operational complexity rounds out the list. Mortgage servicing rights sit on the other side of some of these dynamics. If prepays slow, the servicing cash flow lasts longer and the asset becomes more valuable. If prepays accelerate, the reverse happens. MSR-heavy strategies can therefore be attractive diversifiers inside a broader mortgage allocation, but they bring their own operational, servicing, and regulatory complexity. CFPB mortgage servicing rules remain a live issue, and proposed additional changes from July 2024 are still working through the market.

How the strategy is actually run

This is where allocator diligence matters most, because the manager types are not interchangeable.

Pool pickers live in specified pools and care about relative prepayment protection. They usually talk in stories, cohorts, and pay-up discipline. Basis traders focus on TBA versus pool relationships, hedge costs, and flow-driven dislocations — their edge is often execution and balance-sheet awareness. Structured-product specialists express views through CMOs, IOs, and POs; the strategy can be highly effective, but it can also hide a great deal of embedded leverage. Servicing-oriented investors use MSRs or servicing-linked exposures to offset or monetize prepayment dynamics; these books can look stable until regulation, financing, or operational slippage intrudes.

Strong managers are clear about which of these businesses they are in. Weak ones talk as if they do all of it equally well.

What can go wrong 

Negative convexity is the obvious risk. When rates fall, the best assets prepay fastest. When rates rise, the book extends. The non-obvious risks matter at least as much.

Model risk is first. If prepayment assumptions are wrong, a book that looked like a tidy relative-value trade can turn into a directional one very quickly. Correlation risk is second: in stress, the distinctions between rate risk, spread risk, volatility risk, and financing risk can collapse, and mortgage books that looked diversified can suddenly trade as a single factor. Liquidity risk is third — the agency market is deep, but specific parts of it are less deep than people remember in quiet periods, and structured tranches are another matter entirely. Financing risk is fourth: a strategy can be right on the asset and still wrong on the carry path, margining path, or hedge monetization path.

 Prepayment-risk manager types — what each actually is and what can go wrong 

Source: Resonanz Capital

Anything with a meaningful servicing component deserves more work than most investors give it. Servicing transfers, borrower treatment rules, operational capability, and compliance discipline are not side details. They are part of the investment case. A lot of what gets labelled as prepayment alpha is really a mix of modelling edge, financing terms, and operational competence. Underwrite only the model, and you have underwritten half the strategy.

Why the opportunity set is still interesting now 

The current backdrop is genuinely useful for specialists — not because the trade is easy, but because the market is less homogeneous than it has been in simpler rate environments.

As of May 7, 2026, the average 30-year fixed mortgage rate stood at 6.37%. That leaves a large part of the mortgage universe out of the money for straightforward refinancing. Refinance activity is picking up at the margin as rates have eased, but this is not a simple one-factor refinance wave. It is a selective, borrower-by-borrower environment in which loan-level characteristics — the variables that matter to specialists — drive meaningful dispersion in outcomes.

In a low-rate refinancing boom, pools prepay quickly and dispersion compresses. Specialist judgment becomes a commodity. In a higher-rate, more selective refinance environment, the details matter more: which borrowers act, at what threshold, through which servicers, and at what pace. The same dynamic applies as the Fed continues to run down a still-large MBS portfolio, shifting the balance of supply and private-sector absorption over time.

This is the setting in which the analytical work of separating loan-level reality from generic assumptions earns its keep.

What to ask before committing capital

The right evaluation lens is specific. You need to know whether the manager's edge is data, modelling, structuring, execution, or financing — and whether they rely on dealer models or can genuinely challenge them. You need to understand how they think about borrower behavior versus simple refinance incentive, where the real leverage sits, and what stress episodes have actually cost them.

At Resonanz Capital, when we assess managers in this space, the most revealing question is also the simplest: what does the portfolio turn into when the model is wrong? A manager who can answer that clearly has thought about the strategy from the inside — they have done the work of stress-testing their own assumptions, not just presenting the base case. That discipline is exactly what distinguishes a genuine prepayment specialist from a rates manager with mortgage exposure.

A manager who deflects to the base case probably has not.

If they cannot explain their edge without saying "we like mortgages here," keep moving.