Interest-rate sensitivity for property portfolios: a simple framework for decision-making

When interest rates move, property portfolios often feel it in three places-fast:

• Cash flow (higher debt service reduces distributions and liquidity buffers)
• Covenants (DSCR/ICR headroom can tighten quickly at an SPV level)
• Decision speed (you need a clear "so what?" before the next refinancing, capex decision, or investor call)

The good news: you do not need a complex treasury model to make better decisions. You need a repeatable sensitivity framework that turns "rates up 50 bps" into clear actions-and works across multiple SPVs/entities. (This is exactly the kind of "what-if" scenario planning that becomes powerful once your portfolio data rolls up cleanly across SPVs.)

Below is a simple approach you can run monthly, and tighten up quarterly.

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Definition: what "interest-rate sensitivity" actually means

Interest-rate sensitivity is the change in your portfolio's financial outcomes when interest rates move.

In practice, it is not just "interest expense goes up." A good sensitivity framework shows the knock-on impacts on:

• Cash available (after debt service, before/after reserves)
• Distribution capacity (what can be paid vs what should be retained)
• Covenant headroom (DSCR/ICR, and sometimes cash trap thresholds)
• Refinancing risk (maturities, hedges expiring, margin resets)
• Portfolio resilience (how long you can withstand stress without reactive decisions)

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The core principle: model rates at SPV level, decide at portfolio level

Rates hit facilities, and facilities sit inside SPVs. So the mechanics must start at SPV level.

But decisions (hedging policy, distribution guidance, capex pacing, refinancing plan) are usually made at portfolio level.

So your framework should do both:

1. SPV-level accuracy (because cash, covenants, and debt are legal-entity realities)
2. Portfolio-level clarity (because the board and investors need one coherent story)

If you are consolidating multiple entities (often across separate accounting files) into a standardised portfolio view, this becomes much easier to run consistently month after month.

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The simple 5-step framework

Step 1: Build a "debt exposure map" (one row per facility)

You cannot stress test what you have not described.

Create a debt register with (at minimum):

• SPV / entity
• Facility name and lender
• Outstanding balance
• Rate type: fixed / floating / floating hedged
• Base index: SONIA / SOFR / Euribor (etc.)
• Margin and any step-ups
• Reset frequency (monthly, quarterly)
• Maturity date and extension options
• Amortisation (interest-only vs amortising schedule)
• Hedge details: swaps/caps, notional, strike, expiry, amortising/not
• Key covenants: DSCR/ICR thresholds, cash trap rules, LTV triggers
• Restricted cash / reserves tied to the facility

Outcome: you know exactly which SPVs are exposed, how, and when.

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Step 2: Choose 3-5 rate scenarios that match real decisions

Keep this pragmatic. The best scenarios are the ones that change what you do next.

A solid baseline set:

1. Base case: current forward view / your house view
2. +50 bps parallel shock (quick stress)
3. +100 bps parallel shock (meaningful stress)
4. +200 bps shock (tail risk / covenant stress)
5. Refinance shock: "at maturity, margin + X bps and base rate at Y%"

Optional but useful if you are more advanced:

• Delayed cuts / higher-for-longer (timing matters)
• Hedge expiry scenario ("swap ends in 9 months-what then?")

Tip: do not over-model the yield curve. For decision-making, simple shocks beat complicated assumptions that no one trusts.

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Step 3: Translate rate moves into interest cost-facility by facility

This is the mechanical heart of the model.

For each floating facility (unhedged portion):

• Incremental annual interest cost = Loan balance - Rate shock
• Incremental monthly cost = Incremental annual cost - 12

Then adjust for:

• Interest rate floors
• Caps (strike rate)
• Swap fixed legs
• Hedge amortisation (notional may reduce over time)

Outcome: a clear "rate up 100 bps = +-X/month" by SPV and for the portfolio.

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Step 4: Convert interest changes into decision metrics

Interest cost is not the decision. The decision is whether you still have:

• enough cash headroom, and
• enough covenant headroom,
• at the specific SPVs that matter.

The most useful decision metrics:

A) Cash available after debt service

A simple bridge per SPV:

NOI

• Interest
• Principal (if amortising)
• Committed capex
• Required reserves
  = Cash available / (cash burn)

(You can do this monthly or quarterly, depending on how tight liquidity is.)

B) DSCR / ICR headroom

Common simplified forms:

• Interest cover = NOI - Interest
• DSCR (varies by lender definition) often compares net operating cash flow to total debt service.

You do not need perfect covenant replication to make good decisions, but you do need:

• consistency,
• and a clear warning system for SPVs nearing thresholds.

C) "Runway" under stress

If a scenario produces a cash burn, compute:

Runway (months) = Available cash - Monthly cash burn

This is the kind of number boards understand instantly.

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Step 5: Define action triggers (what you will do when thresholds are hit)

This is where sensitivity becomes a decision tool, not an academic exercise.

Examples of clear triggers:

• DSCR falls below 1.30x in any SPV under +100 bps -> freeze discretionary distributions from that SPV
• "Runway under +100 bps" falls below 6 months -> accelerate refinance or restructure capex timing
• Hedge expiry within 9 months and unhedged exposure > X% -> hedge decision required by next IC meeting
• Refinancing within 12 months -> run refinance shock scenario monthly

Outcome: you can move quickly without re-debating policy every month.

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Worked example: one table that turns rates into decisions

Assume (simplified):

• Portfolio NOI: -4.5m / year

• Debt: -60m total

  • -40m floating (unhedged)
  • -20m fixed

• Current annual interest:

  • Floating all-in rate: 6% -> -40m - 6% = -2.4m
  • Fixed rate: 4% -> -20m - 4% = -0.8m
  • Total interest = -3.2m

• Baseline interest coverage (NOI - interest) = -4.5m - -3.2m - 1.41x

Now run simple shocks:

Scenario	Rate shock on floating	Incremental interest (annual)	Total interest (annual)	Interest cover (NOI - interest)	Cash after interest (NOI - interest)
Base	0 bps	-0	-3.2m	1.41x	-1.3m
+50 bps	+0.50%	-40m - 0.50% = -0.2m	-3.4m	4.5 - 3.4 - 1.32x	-1.1m
+100 bps	+1.00%	-40m - 1.00% = -0.4m	-3.6m	4.5 - 3.6 = 1.25x	-0.9m
+200 bps	+2.00%	-40m - 2.00% = -0.8m	-4.0m	4.5 - 4.0 = 1.13x	-0.5m

What this table enables:

• If your covenant trigger is around ~1.20-1.25x, you can see that +100 bps is a "board discussion" scenario.
• You can quickly translate "rates up" into "we lose ~-0.4m/year of distributable cash" in this simplified case.
• You can then segment by SPV to see which entities breach first.

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Common mistakes (that make sensitivity useless or misleading)

Mistake 1: Doing sensitivity only at portfolio level

A portfolio can look fine while one SPV is heading into a covenant breach.

Fix: calculate at SPV/facility level, then roll up.

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Mistake 2: Ignoring hedges (or modelling them incorrectly)

Swaps, caps, floors, amortising notionals-small details change outcomes.

Fix: treat hedges as first-class inputs in the debt register, and separate hedged vs unhedged exposure.

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Mistake 3: Stressing interest expense but not cash timing

Month-end P&L may look fine, while cash timing creates a crunch (quarterly interest, capex milestones, reserves).

Fix: pair the annual sensitivity with a simple 13-week / 6-month SPV cash view for exposed entities.

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Mistake 4: Missing refinancing and margin reset risk

The biggest "rate shock" sometimes happens at refinance:

• margin increases,
• fees are paid,
• hedges roll off,
• amortisation terms change.

Fix: always include a refinance shock scenario for any facility inside 12-18 months to maturity.

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Mistake 5: No action thresholds

If your sensitivity produces numbers but no decisions, it becomes a slide that no one uses.

Fix: pre-agree triggers tied to distributions, hedging, refinance timelines, and capex pacing.

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Best-practice reporting: what to include in the monthly pack

If you want this to build trust with investors and boards, keep it consistent and simple.

A strong one-page "Rate Sensitivity" section includes:

1. Exposure summary

   • Total debt, % floating, % hedged, next 12 months maturities

2. Scenario table

   • +50 / +100 / +200 bps -> incremental interest and coverage headroom

3. SPV exception list

   • which SPVs are closest to DSCR/ICR triggers under +100 bps

4. Actions / mitigations

   • hedge decisions, refinance plan, distribution posture, reserve posture

5. Assumptions (as of date)

   • base rates used, hedge coverage date, debt balances date

Once your underlying portfolio reporting is consistent across SPVs, you can also generate reliable narrative like: "Rates +100 bps reduce distributable cash by -X and bring SPV 03 within Y% of its covenant." That is where "what-if" scenario planning really pays off.

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A quick checklist you can implement this month

• Debt register updated (balances, maturities, hedges, covenants)
• Scenarios agreed (+50 / +100 / +200 bps + refinance shock)
• Incremental interest calculated per facility
• Cash and covenant headroom shown per SPV (exceptions highlighted)
• Action triggers agreed (distribution, hedging, refinance, capex)
• One-page pack output generated with "as of" dates

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Closing: make sensitivity repeatable, not heroic

Interest-rate sensitivity does not need to be complex to be valuable. The goal is a repeatable system that answers:

• What happens if rates move?
• Which SPVs break first?
• What do we do about it-now?

If your data is spread across many SPVs (and often many accounting entities), the real unlock is being able to run these scenarios on consistent, standardised portfolio reporting-so decisions are grounded and fast.