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Calculate mortgage pipeline exposure in layers: first measure the unpaid principal balance of active, unclosed locks; then multiply each segment by its forecast pull-through to estimate funded exposure; finally compare duration-weighted pipeline sensitivity with the duration-weighted hedge position and your approved target. The quick notional check is hedge position ÷ active pipeline volume, but it is not a sufficient hedge decision because fallout, servicing values, duration, basis, convexity and delivery obligations can make a target materially different from 100 percent.
What the calculation is intended to measure
A mortgage originator carries interest-rate risk between a borrower’s lock and the loan’s funding, sale or delivery. The pipeline calculation estimates how much of that risk remains and whether the positions used to offset it are sized for the loans that are actually expected to fund. It is a risk measurement process, not a rule that every locked dollar must be matched with one dollar of securities.
Pipeline exposure and hedge position are different quantities
Pipeline volume is the current dollar amount of active loans in the hedge pipeline. In most implementations this means locked or committed loans that have not yet closed and been delivered. The amount is usually unpaid principal balance, although an institution may use another documented notional basis.
Hedge position is the active coverage attributed to the same population and risk bucket. Mortgage teams commonly express it in to-be-announced mortgage-backed securities (TBAs), but the instrument can vary by product and policy. A TBA notional is not automatically equivalent to a loan notional: the two can have different price sensitivity, timing, basis behavior and convexity.
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Why expected funded volume matters
Locks do not all become funded loans. Fallout can result from a borrower withdrawing, a failed condition, a refinance, a rate renegotiation or a delayed closing. Pull-through converts committed volume into an expected funded amount. Fannie Mae’s glossary defines realized pull-through as “the volume of loans closed and funded divided by the volume of loans committed over a period of time expressed as a percentage.” A hedge model can forecast pull-through loan by loan or by cohort instead of applying one trailing percentage to every lock.
Inputs to assemble before calculating
Use one consistent as-of time. Every balance, hedge, forecast and duration should describe the same cut-off, so a position cannot appear balanced merely because one report is newer than another.
| Input | What to record | Why it affects the result |
|---|---|---|
| Active pipeline balance | Unpaid principal balance of eligible, unclosed locks or commitments | Sets the starting notional exposure |
| Hedge position | Open TBA or other approved hedge notional assigned to the same segment | Provides the offset being tested |
| Forecast pull-through | Expected funded percentage, with vintage, method and overrides | Reduces locked volume to expected funding |
| Pipeline duration or price sensitivity | Effective duration, DV01, or another approved sensitivity measure | Shows how the loans respond to a rate move |
| Hedge duration or sensitivity | Equivalent measure for each hedge instrument and coupon | Prevents unlike notionals from being treated as equal risk |
| Servicing and MSA effects | Value and sensitivity of servicing rights or mortgage servicing assets where applicable | Falling rates can increase prepayments and reduce servicing values |
| Basis and execution data | Product-to-TBA basis, liquidity, transaction costs and delivery terms | A nominal offset can still leave market and execution risk |
| Segmentation keys | Program, coupon, expected close date, lock status and commitment or hedge bucket | Improves pull-through and sensitivity estimates |
Step-by-step calculation
1. Define the exposure population
Write the inclusion rule before loading balances. A common rule is “active locks or commitments that have not closed and delivered as of the reporting timestamp.” Keep funded loans that have already been committed or sold out of this unclosed-pipeline population unless your approved framework explicitly retains a residual risk.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Segment the population where behavior or price sensitivity differs materially. At minimum, consider loan product or program, coupon, expected closing date and the commitment or hedge bucket. A 30-day conventional lock and a longer-dated government lock should not be forced into one fallout assumption merely because both are unpaid principal balance.
Regulatory guidance treats pipeline and warehouse administration as related but distinct activities. Maintain a separate population and reconciliation for loans already funded and held in a warehouse, and document any overlap or transfer between reports.
2. Forecast pull-through for each segment
For a simple cohort, calculate:
Expected funded volume = active pipeline volume × forecast pull-through
For example, a $2 million lock cohort with a 75% forecast produces $1.5 million of expected funded principal. The 75% is an assumption for that cohort, not a permanent characteristic of every loan.
A forecast can use recent realized performance, but a robust model also considers current loan status, borrower and underwriting conditions, product, time to close and the age of the lock. Record overrides and the reason for each override. Compare actual closed-and-funded results with the forecast by vintage and segment; supervisory guidance expects mortgage-banking models to be checked against predicted performance and recalibrated when they drift.
3. Calculate nominal coverage as a first check
The quick notional ratio is:
Nominal coverage = active hedge position ÷ active pipeline volume
If the pipeline is $10 million and the hedge is $8 million, nominal coverage is 80%. This ratio answers only whether the two notionals are similar. It does not say that 80% is right, because expected fallout may reduce funding below the locked balance and the hedge may have different duration or basis exposure.
You can also show a simple expected-funded ratio for operational monitoring:
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Hedge-to-expected-funding ratio = active hedge position ÷ expected funded volume
Do not substitute this ratio for a sensitivity-weighted test. It is useful for spotting a large change in fallout assumptions before the formal hedge model is rerun.
4. Convert both sides to a common sensitivity measure
Notional dollars in loans and TBAs can gain or lose different amounts when rates move. Translate each side into the measure specified by your model, such as effective duration, price value of a basis point (PV01) or a duration-weighted notional.
Conceptually:
Duration-weighted pipeline exposure = expected funded exposure × pipeline duration factor
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Use the same sign convention, rate shock, price scale and timing assumptions on both sides. If your model uses DV01, sum the signed dollar change for the defined rate move rather than multiplying incompatible duration percentages. Mortgage cash flows can change as rates move because prepayment behavior changes, so effective duration is generally more informative than a static contractual maturity.
5. Compare with the model-defined optimal coverage
Calculate current coverage on the same sensitivity-weighted basis as the target:
Current weighted coverage = duration-weighted hedge exposure ÷ duration-weighted pipeline exposure
The gap can be expressed as a percentage or dollars:
Coverage gap = current weighted coverage − optimal weighted coverage
Some Mortgage Capital Trading examples describe optimal coverage as forecast pull-through less a servicing-related adjustment called theta. That relationship is specific to the example’s assumptions. Theta, duration factors and scaling are not universal industry constants; use the values validated in your institution’s approved model.
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6. Interpret the sign and size of the gap
In the simplified convention used by the cited MCT examples, coverage below the modeled target is described as under-covered or “long,” and the illustration responds by selling additional TBA coverage. Coverage above target is over-covered, and the illustration pairs out part of the position. Your policy may use the opposite sign convention, so label reports in plain language as well as with plus or minus signs.
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Worked illustrations and how to read them
The $10 million rate-shock illustration
Mortgage Capital Trading’s 2022 Hedging 101 white paper uses a simplified scenario with a $10 million pipeline, assumed 100% pull-through and a 25-basis-point rate increase. Using a 4-to-1 price-to-rate multiple, the example illustrates a 100-basis-point price loss on the pipeline. It then shorts $10 million of TBAs at an assumed price of 101; a one-point gain on the hedge is shown offsetting the one-point pipeline loss.
The arithmetic demonstrates the direction of an offset, not a live market quote or a guaranteed hedge result. Real pipelines have fallout, different coupons and durations, and servicing or basis effects. A model would therefore estimate loan-level pull-through and derive an optimal hedge rather than mechanically hedge 100% of lock notional.
The $2 million new-lock and recycling illustration
The same white paper describes $2 million of new locks with 75% expected pull-through. The expected funded amount is $1.5 million. It then describes $1.5 million of funded loans being committed to investors and the associated coverage being retained to offset new lock needs instead of immediately being paired out. This operating practice is called trade recycling.
Trade recycling can reduce unnecessary transactions when the released coverage and new locks have a suitable risk match. It is not automatic: confirm that the populations, product, coupon, timing and sensitivity are compatible, and ensure the transfer is recorded in both the pipeline and hedge ledgers. If fallout subsequently declines or rises materially, the recycled position can become over- or under-covered and require adjustment.
The illustrative 85% optimal target
A separate MCT example uses a $10 million pipeline and an illustrative 85% optimal coverage recommendation, implying $8.5 million of TBA coverage on the example’s stated basis. The 85% is a scenario output, not a universal recommendation. Replacing it with 100% simply because the pipeline is $10 million would discard the fallout and servicing assumptions that produced the target.
Choosing a pull-through approach
| Approach | Strength | Weakness or control needed |
|---|---|---|
| Trailing realized rate | Simple and transparent; based on closed-and-funded history | Can lag a change in product mix, lock age, underwriting or market conditions |
| Cohort forecast | Separates program, coupon, lock age and expected close date | Requires enough history and disciplined segmentation |
| Loan-level forecast | Uses current status and borrower or underwriting information | More data, model governance and override controls are required |
| Manual overlay | Can reflect a known operational event quickly | Must have documented rationale, approval and post-period validation |
Whichever method you use, retain the forecast vintage, observation window, exclusions and overrides. A single percentage printed without those details cannot be audited or compared with realized outcomes.
Servicing, MSA and convexity effects
Mortgage cash flows are path-dependent. When rates fall, refinancing and prepayment can accelerate. That can shorten loan cash flows while also impairing the value of mortgage servicing assets or servicing rights. When rates rise, expected prepayments can slow, extending duration. These effects can make the hedge need differ from pull-through alone.
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The Federal Reserve, FDIC, OCC and OTS interagency advisory issued February 25, 2003 states that “Successful hedging systems will mitigate the impact of prepayments on MSA values and the effects of interest-rate risk in the mortgage pipeline and warehouse.” Treat this as a reason to include servicing and warehouse exposures in the risk view, not as a fixed hedge formula.
Use reasonable, supportable assumptions and validate the model. If servicing is retained, show the servicing sensitivity separately before combining it with pipeline sensitivity; otherwise a favorable pipeline number can conceal an adverse MSA movement.
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Basis, execution and delivery risks
Basis risk
A TBA hedge and a particular loan pool do not move in lockstep. Product, coupon, geography, seasoning, loan size and market liquidity can create basis changes. Monitor hedge effectiveness by bucket rather than relying only on the aggregate notional ratio.
Execution and transaction costs
Adding, reducing or rolling coverage incurs bid-offer spreads, commissions, financing or other execution costs. Include approved cost assumptions in scenario analysis and compare the cost of a correction with the risk of leaving the gap open. The cited examples do not establish a universal cost or instrument choice.
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Fannie Mae’s glossary describes a mandatory commitment as an obligation to deliver specified product volume by a date. If delivery fails, the commitment can require a pair-off, and pair-off fees may apply under the commitment terms. Track these obligations separately from the unclosed pipeline calculation so an apparent hedge surplus is not mistaken for freely available coverage.
Controls, reporting and stress testing
A calculation is useful only when the institution can explain where each number came from and what happens when assumptions fail. A practical control set includes:
- Reconcile active locks, funded loans, investor commitments and open hedges at every reporting cut-off.
- Assign each loan and hedge to one documented product, coupon, timing and risk bucket.
- Store pull-through forecasts, model versions, overrides, approvers and forecast vintages.
- Compare realized funding with predicted funding by cohort and investigate material variance.
- Monitor hedge effectiveness, basis movements and concentrations by instrument, counterparty and settlement date.
- Report hedged and unhedged positions, mark-to-market, rate-shock results, limits, breaches and exceptions to management.
- Stress both expected and adverse rate paths, including changes in fallout, prepayment speed, servicing values, basis and liquidity.
- Set independent limits for pipeline, warehouse, counterparty and concentration risk, with escalation procedures.
- Validate models and review assumptions after major changes in products, channels, lock terms or market behavior.
Interagency supervisory guidance expects systems that measure and control interest-rate risk, monitor hedge effectiveness and concentrations, and provide management information on positions, mark-to-market and rate-shock exposures. Stress testing should address earnings and capital exposure under expected and stressed conditions, not only the daily point estimate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A repeatable daily workflow
- Freeze the timestamp. Record the reporting date, time zone and source-system extracts.
- Build the eligible pipeline. Exclude closed and delivered loans unless the approved framework retains a defined residual risk.
- Segment the loans. Group by program, coupon, expected close date, lock status and commitment or hedge bucket.
- Load hedge positions. Reconcile open TBA and other approved instruments to the same segments and settlement dates.
- Assign pull-through. Apply the documented cohort or loan-level forecast and record overrides.
- Calculate expected funding. Multiply each segment’s active balance by its forecast pull-through, then sum the results.
- Run the notional check. Divide hedge position by active pipeline volume and flag large day-over-day changes.
- Run the sensitivity check. Convert pipeline and hedges to the approved duration, DV01 or price-sensitivity basis and compare with the optimal target.
- Investigate the gap. Review fallout changes, servicing, basis, delivery obligations, limits and transaction costs before proposing a trade.
- Approve and document action. Record the decision, instrument, size, execution result, responsible person and any exception.
- Reconcile after execution. Confirm the trade settled into the intended bucket and that the next report reflects the change.
Common mistakes and fixes
Hedging 100% of locks by default
Problem: The rule ignores fallout and servicing adjustments.
Fix: Forecast funded volume and compare duration-weighted coverage with the approved optimal target.
Using one trailing pull-through percentage for every loan
Problem: Product mix and lock age can change faster than the historical average.
Fix: Segment by the characteristics that drive closing behavior and validate forecasts against subsequent funding.
Comparing unlike notionals
Problem: Loan and hedge dollars can have different duration, convexity and basis.
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Mixing funded loans into the unclosed pipeline
Problem: The balance is overstated or counted twice after investor commitment.
Fix: Define transfer rules between pipeline, warehouse and committed populations and reconcile them daily.
Ignoring servicing exposure
Problem: A pipeline hedge can look effective while an MSA or servicing value loses money in a falling-rate scenario.
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Fix: Model servicing sensitivity and report it alongside pipeline and warehouse exposure.
Treating a model output as a universal ratio
Problem: An illustrative 85% target or theta adjustment is copied into a different institution.
Fix: Use institution-specific, validated assumptions and label external examples as examples only.
Trading without checking delivery terms
Problem: A hedge reduction can leave a mandatory commitment short, creating pair-off exposure or fees.
Fix: Reconcile investor commitments, delivery dates and pair-off provisions before changing coverage.
What a complete management report should show
Present enough detail for a manager to distinguish a volume change from a risk change. At minimum, show:
- Active pipeline balance and change from the prior report.
- Expected funded balance and pull-through by segment.
- Hedge notional, settlement date and instrument bucket.
- Nominal coverage and duration- or DV01-weighted coverage.
- Approved optimal target and the dollar and percentage gap.
- Pipeline, hedge, servicing and warehouse mark-to-market.
- Rate-shock results, basis sensitivity and stressed fallout.
- Counterparty, concentration and limit utilization.
- Investor commitments, delivery obligations and potential pair-off exposure.
- Exceptions, overrides, approvals and planned corrective actions.
This format makes it possible to answer three different questions without conflating them: how many loans are locked, how many are expected to fund, and how much rate sensitivity remains after hedging.
Bottom line
Start with a clean, segmented active pipeline; forecast pull-through; calculate nominal coverage; then make the decision on a common duration or price-sensitivity basis. The correct hedge is the one supported by a validated model, documented servicing and basis assumptions, operational limits and stress testing—not a universal percentage of locked principal.
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