Why Reverse Underwriting Wins
Most investors underwrite forward: take the asking price, plug in revenue and expenses, and see what the return looks like. That approach anchors you to the seller's number and quietly encourages you to nudge assumptions until the deal "works".
Reverse underwriting flips the question. You fix the return you require, hold the property's income constant, and solve for the only variable you control: the price you pay. The output is a maximum offer — a hard number you can walk into a negotiation with.
This assumes you already have a defensible income model. If not, build it first using the STR deal underwriting framework.
Step 1: Pick One Binding Target
You can solve for price against several targets, but only one can bind. Run each and take the lowest resulting price.
- Cash-on-cash target: the return you need on the cash you put in — typically 8–12% for an STR.
- DSCR target: the coverage your lender requires, usually 1.20x–1.25x.
- Cap rate target: NOI ÷ price, useful for comparing across unlevered deals and markets.
In a high-rate environment the DSCR target is usually the binding constraint, because debt service rises faster than income does.
Step 2: Hold NOI Fixed
The whole method depends on NOI being independent of price. Most of it is: ADR, occupancy, cleaning, management, utilities, and insurance do not change because you paid less. Two lines do move with price, so handle them explicitly.
- Property taxes are usually reassessed off the sale price. Recompute them at the price you are solving for, or run one iteration after the first solve.
- Lodging tax and management scale with revenue, not price — leave them alone.
Use the conservative case NOI, not the base case, when the deal is competitive. Paying your maximum price on optimistic income is how a good model produces a bad purchase.
Step 3: Solve for the Purchase Price
The three solves, in the form you can put in a spreadsheet:
Cap rate solve: Price = NOI ÷ Target Cap Rate
DSCR solve: Max Annual Debt Service = NOI ÷ Target DSCR
Max Loan = Max Annual Debt Service ÷ Annual Constant
Price = Max Loan ÷ (1 − Down Payment %)
Cash-on-cash solve: Required Cash Flow = Target CoC × Total Cash Invested
Allowed Debt Service = NOI − Required Cash Flow
Price = (Allowed Debt Service ÷ Annual Constant) ÷ (1 − Down Payment %)
The annual constant is annual debt service divided by loan amount. At 6.5% over 30 years it is roughly 0.0758 — that is, about $7,580 of yearly payments per $100,000 borrowed.
Because total cash invested depends on price, the cash-on-cash solve is circular. Solve once with an estimated price, recompute cash invested at that answer, and solve again. Two passes are enough for practical accuracy.
A Worked Example
A three-bedroom listed at $475,000. Comps support an ADR of $245 and 62% occupancy, giving gross revenue of about $55,400. After management, cleaning across roughly 45 turnovers, lodging tax, utilities, insurance, taxes, and reserves, conservative NOI lands at $27,000.
- DSCR solve at 1.25x: maximum debt service = $27,000 ÷ 1.25 = $21,600. Maximum loan = $21,600 ÷ 0.0758 ≈ $285,000. At 25% down, maximum price ≈ $380,000.
- Cash-on-cash solve at 10%: at roughly $135,000 of cash in, required cash flow is $13,500, so allowed debt service is $13,500. Maximum loan ≈ $178,000, implying a price near $237,000 — far more restrictive.
- Cap rate solve at 6.5%: $27,000 ÷ 0.065 ≈ $415,000.
The binding constraint here is the 10% cash-on-cash target. Either the offer needs to be well under ask, the return target needs to drop toward 6–7%, or the revenue case needs a genuine improvement — a hot tub, better photography, a higher guest count — that you can fund and justify.
Let the model solve for your offer
Revaluno's STR Analysis Tool builds NOI from live comps and reverse-solves the purchase price that hits your target return and DSCR.
Try the STR Analysis ToolSanity-Check Against the Comps
An income-derived price is only half the picture. Before you send it, check it against value:
- Compare your maximum offer to recent sold comparables in the same submarket. A price 30% below every sale in the neighborhood will not get accepted, no matter how clean the math is.
- Check price per square foot against the range for similar homes — see how to run real estate comps.
- Verify the exit. If you had to sell in year three, would a conventional buyer pay near your basis? Run an ARV estimate as a floor test.
- Confirm the regulatory picture: permit caps, HOA rules, and occupancy limits can invalidate the income assumption entirely.
Turning the Number Into an Offer
Lead with the constraint, not the opinion. "At the asking price, coverage is 0.95x and my lender needs 1.25x — here is the price that clears it" is a conversation. "Your price is too high" is not.
Also underwrite the terms, not just the price. A seller-paid rate buydown, an assumable low-rate loan, or furniture included in the sale each move your model. Furniture alone can be $20,000–$40,000 of startup capital you no longer have to spend, which lifts cash-on-cash without the seller lowering price.
Finally, write the number down before you tour the property. The maximum offer you compute on a spreadsheet is the one you should honor after you have fallen in love with the view.
Frequently Asked Questions
What return should I solve for on a short-term rental?
Most STR investors solve for an 8–12% cash-on-cash return or a DSCR of 1.25x, whichever produces the lower purchase price. Using the more restrictive of the two keeps the deal financeable and profitable.
Should startup and furnishing costs be part of the offer calculation?
They belong in total cash invested when you measure your return, but the reverse solve for a maximum purchase price is cleaner when it works off NOI and debt service. Add furnishing back when you check the final cash-on-cash.
What if my maximum offer is far below the asking price?
That is useful information, not a failure. Either the revenue assumptions need to rise for a defensible reason, the expense stack has room, or the property is priced for a buyer with a different objective. Walk or wait.