Sensitivity analysis tests how an output — a valuation, a projected return, a coverage ratio — changes when its input assumptions move. Instead of one answer, it produces a map of answers across plausible conditions, which is why the sensitivity table is often the most honest exhibit in any set of projections.
The method and the two places advisors read it
The mechanics are simple: hold a model constant, vary one or two inputs across a range, and tabulate the results — classically a two-way grid (rent growth across the top, exit cap rate down the side, projected IRR in the cells). Richer variants — scenario analysis (coherent bundles of assumptions: base, upside, downside) and stress testing (deliberately severe cases) — extend the same idea. What the exercise reveals is which assumptions matter: in most real estate models, the exit cap and discount rate dominate everything else, a fact the sensitivity grid makes undeniable in a way the base case never does.
Reading spot #1 — NAV disclosures. Non-traded NAV REITs publish sensitivity tables with their valuations: how much NAV per share would move for a 25-basis-point change in the assumed discount rate or exit cap. The numbers are routinely striking — single small-sounding assumption shifts moving NAV by several percent — and they are the printed proof of how much judgment sits inside a published NAV. During the 2022–24 repricing, these tables were the reader’s tool for asking whether marks had moved as far as market evidence implied.
Reading spot #2 — deal projections. Sponsor pro formas that show only a base case have chosen not to show you the map. The advisor’s checklist for a projection’s sensitivity exhibit: does the downside row use genuinely adverse inputs (exit caps above entry — properties usually sell at wider caps than aggressive models assume — rent growth at or below inflation, realistic refinancing rates)? Does the deal survive the corner cells — and if the bottom-left corner shows a loss, is the client positioned to accept it? Is the input range honest, or does “sensitivity” run from optimistic to very optimistic? A projection whose worst tabulated case still shows a 12% IRR isn’t a sensitivity analysis; it’s marketing with rows.
FAQ
What is sensitivity analysis in simple terms?
Asking “what if we’re wrong?” systematically — recalculating a valuation or return across a range of assumptions to see how much the answer depends on each one.
Where do investors see sensitivity tables in alternatives?
NAV REIT valuation disclosures (NAV per share vs. discount-rate and exit-cap changes) and deal pro formas (projected returns across rent-growth and exit assumptions).
What makes a sensitivity analysis credible?
Honest ranges — downside cases that are actually adverse, including exit pricing worse than entry — and disclosure of which inputs the result is most hostage to.
Related terms
Discounted Cash Flow (DCF) · Exit Cap Rate · Discount Rate · NAV · Independent Valuation Advisor
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