Beta (Unlevered) Calculator
The formula
What the unlevered beta tells you
The observed equity beta with financial leverage removed — the pure operating/market risk of the business assets.
Calculation: Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E]. Enter your inputs and every substitution is shown below the result.
Reading the result
Unlever a set of industry comps, take the median, then relever at your own structure: that is how private-company and project betas get built from scratch.
Rules of thumb: Asset betas: staples ~0.5, industrials ~0.9, tech ~1.2, semis ~1.4
Limitations and best practice
Net debt, leases and minority stakes muddy the D/E input; consistency beats precision here — use the same debt definition across the whole comp set.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Why median instead of average unlevered beta?
Does unlevering work for banks?
Source & methodology
Standard comp-unlevering methodology (Damodaran, McKinsey Valuation).
Beta (Unlevered) explained: formula, worked example and honest limits
Every bet is a price, and this page computes whether the price is fair. There are plenty of pages about Beta (Unlevered); almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
People rarely disagree about arithmetic; they disagree about assumptions that were never written down. Printing the substitution and the sensitivity ranking removes that category of disagreement for Beta (Unlevered).
Business runs on numbers that are cheap to compute and expensive to ignore. Beta (Unlevered) in Business & Entrepreneurship is one of those: Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E], and the gap between founders who check and founders who hope shows up exactly here.
Nothing below is stock text pasted around a number: the worked example computes unlevered (asset) beta = 0.92 from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — Observed equity beta first, at ≈10.0 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
Every input in Beta (Unlevered), and what it does to the answer
One formula, published in full: Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E]. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Observed equity beta (example value 1) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Debt ($) (example value 3,598,238) is a quantity rather than a category — precision here is cheap and worth having. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
Equity ($) (example value 5,179,587) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Tax rate (%) (example value 22) is a measured number in the unit named by the label; the formula does not convert for you. Check the convention first: if the source says “6.5 % per year”, type 6.5 and let the formula do the rest.
The default Beta (Unlevered) calculation, written out in full
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Observed equity beta, Debt ($), Equity ($), Tax rate (%). The endpoint of that chain is 0.92 of unlevered (asset) beta, sitting in the “Strip the financing out and the business itself carries beta 0.92 — the industry risk, honestly” band.
- Bu = 1.42 ÷ [1 + (1 − 22%) × 0.69] = 0.92
- Unlevering is how you compare operating risk across differently financed competitors
D/E used — 0.69. This is the number experienced users quote when the headline alone would mislead.
Share of observed beta due to leverage — 0.50 beta. If your inputs change, this is usually the first companion figure to move.
Median-style relever for a 0.3 D∕E peer — 1.14. If your inputs change, this is usually the first companion figure to move.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Beta (Unlevered) corridor: your result across a realistic band
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of Beta (Unlevered), not an interpolation.
| Observed equity beta setting | Unlevered (asset) beta |
|---|---|
| 80 % of the example value | 0.74 |
| 90 % of the example value | 0.83 |
| example inputs | 0.92 |
| 110 % of the example value | 1.01 |
| 120 % of the example value | 1.11 |
Across 5 settings of Observed equity beta, the result spans 0.74 to 1.11. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing Observed equity beta alone; the substitution steps will follow your figures exactly.
What actually moves your Beta (Unlevered)
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the unlevered (asset) beta recomputed, so the ranking below is measured rather than asserted. It is the fastest honest answer to “what matters most in Beta (Unlevered)?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Observed equity beta: ten percent up gives 1.01, ten percent down gives 0.83 — ≈10.0 % of the unlevered (asset) beta either way
- Nudge Equity by ±10 % and Beta (Unlevered) lands between 0.89 and 0.95 (sensitivity ≈3.8 %)
- Nudge Debt by ±10 % and Beta (Unlevered) lands between 0.89 and 0.95 (sensitivity ≈3.6 %)
- Nudge Tax rate by ±10 % and Beta (Unlevered) lands between 0.91 and 0.93 (sensitivity ≈1.0 %)
Observed equity beta is the dominant lever here: ten percent either way moves the result by about 10.0 %, from 0.83 to 1.01. Measure that input from a document rather than from memory, and treat Equity as the second priority (≈3.8 % per ten percent). The remaining fields can sit at safe defaults without materially changing the answer — knowing which is which is what separates a careful calculation from an anxious one.
Is your Beta (Unlevered) good — reading the result bands
Nobody acts on a bare figure — they act on a figure with a comparison attached. On the example inputs the band reads “Strip the financing out and the business itself carries beta 0.92 — the industry risk, honestly”; your own figures place you on a different rung of the same ladder. The sensitivity list shows how far a modest input error moves you along that ladder: for Observed equity beta, ±10 % covers 0.83 to 1.01. The practical reading rules: read the band as a starting hypothesis, then test it: change the two dominant inputs by ten percent and see whether the verdict survives. Verdicts that survive stress are the ones worth acting on.
Placing this figure in context: calculators of this kind differ less in arithmetic than in what they choose to ignore. This one keeps Observed equity beta explicit so that the omissions are visible rather than hidden in a preset.
Why Beta (Unlevered) results go wrong — and how to prevent it
Net debt, leases and minority stakes muddy the D/E input; consistency beats precision here — use the same debt definition across the whole comp set. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Stopping at the first plausible answer. If the result surprises you, the productive question is which input would have to be wrong for the surprise to disappear — then go check that input.
This model has its own particular trap: Observed equity beta carries ≈10.0 % of the response per ten percent of error, so effort spent elsewhere is largely decorative.
Another is comparing across contexts: a Beta (Unlevered) computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
Beta (Unlevered) verification checklist
- Compare the result with one independent method or published benchmark.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Put Observed equity beta under a magnifier; the sensitivity table above is the reason why.
- Verify each input against its original source document, not memory.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Confirm the answer against one independent method or published benchmark for Beta (Unlevered).
Five steps from raw inputs to a figure you can defend
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for Beta (Unlevered) takes a minute to learn and applies to every input above.
Step 1 — gather before you type. Beta (Unlevered) depends on observed equity beta, debt ($), equity ($), tax rate (%). Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. Write the figure down before moving on; memory flatters whichever number you saw last.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. The input you reach for first is usually the one you measured longest ago.
Step 3 — isolate your variables. Change one field, observe, revert. The live sensitivity list does the ranking for the default inputs; verify it against your own, because dominance shifts when the starting point shifts. The input you reach for first is usually the one you measured longest ago.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. If a result feels obviously right, that is the moment to check the inputs hardest.
Step 5 — schedule the next run. In Business & Entrepreneurship the inputs drift quietly. Put a reminder a quarter out, re-enter the same fields, and read the change rather than the level. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Who actually uses Beta (Unlevered) — and when
Most Financial Analysis disagreements are arithmetic disagreements in disguise. When Unlevered (asset) beta of 0.92 sits on the table with its working shown, the conversation stops being about who sounds more confident and starts being about which input is wrong. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
The audience for this page is players deciding whether a wager is mathematically worth taking. In professional Financial Analysis practice the pattern is always the same — screen with Beta (Unlevered), then invest slow analysis only in whatever survives the screen. One decimal place more than your data supports is one decimal place of fiction.
Treat Beta (Unlevered) like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. Compare the calculation to the rough guess you arrived with, and ask why they differ.
The questions that come up most about Beta (Unlevered)
What affects Beta (Unlevered) the most?
Measured on this engine, Observed equity beta is the dominant lever: moving it ±10 % shifts the unlevered (asset) beta across 0.83 to 1.01 — about 10.0 % of the headline, with Equity next at ≈3.8 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: equity or observed equity beta?
Observed equity beta, by a factor of about 2.7. Concretely: ten percent on Observed equity beta is worth ≈10.0 % of Beta (Unlevered), the same nudge on Equity only ≈3.8 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Beta (Unlevered)?
There is no honest universal average for Beta (Unlevered), but there is a reference point: the defaults on this page produce 0.92 (Strip the financing out and the business itself carries beta 0.92 — the industry risk, honestly). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Beta (Unlevered) by hand?
Three steps: write the formula (Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E]), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Beta (Unlevered) than any number of calculator runs.
What happens to Beta (Unlevered) if observed equity beta changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the unlevered (asset) beta goes across 0.83 to 1.01, a swing of roughly 10.0 % around the 0.92 baseline. That ratio is the practical definition of how much this input matters.
Is the Beta (Unlevered) result of 0.92 good or bad?
Good and bad are comparisons, so the honest test is three questions: where does your own Beta (Unlevered) sit against the 0.92 reference above, how far would a plausible input error move it (≈10.0 % per ten percent on Observed equity beta), and what does the alternative option compute to?
What does 0.92 tell me about the business?
It answers the narrow question mechanically and the broad question only in context: Beta (Unlevered) is one dashboard light, and it pairs with unit economics and cash timing before any bet the business size.
How do I calculate Beta (Unlevered) manually?
Write down the inputs, then follow the printed steps in order — Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E]. A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
Why median instead of average unlevered beta?
One odd comp (mega-levered or micro-float) drags averages; medians survive single outliers in thin comp sets.
Does unlevering work for banks?
No — leverage is their product, not their financing. Analysts use adjusted P/B approaches for financials.
Do I need an account to use this Beta (Unlevered) calculator?
No, and no data leaves the tab. The engine runs in the page itself, which is why the worked example, the bands and the sensitivity ranking all respond instantly to your keystrokes.
What the labels on this page mean
- D/E used
- 0.69 for the Beta (Unlevered) worked case; it sits next to the main result because it carries context the headline leaves out.
- Share of observed beta due to leverage
- 0.50 beta in the default Beta (Unlevered) calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Median-style relever for a 0.3 D∕E peer
- 1.14 in the default Beta (Unlevered) calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Unlevered (asset) beta
- The primary output of this tool: 0.92 for the default inputs, computed exactly from Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E].
- Worked example
- Every substitution in order, from the example inputs to 0.92 — the audit trail for the headline figure.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “Strip the financing out and the business itself carries beta 0.92 — the industry risk, honestly”, and your inputs may not.
- Sensitivity (±10 %)
- How far the Beta (Unlevered) moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Methodology, sources and limits
Everything above runs on one stated formula, applied without hidden coefficients: Unlevered beta = levered beta ÷ [1 + (1 − tax) × D∕E]. Source of record: Standard comp-unlevering methodology (Damodaran, McKinsey Valuation). Where a professional version of this calculation differs, it differs in inputs and jurisdiction-specific coefficients, not in the algebra — which is why re-checking your inputs beats hunting for a second calculator.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. The design constraint was set by usefulness rather than by comfort: an estimate you can interrogate beats an answer you have to trust.
Turning this Beta (Unlevered) into a decision
Re-run at more conservative assumptions — if the wager only works on the optimistic numbers, it is not a wager, it is a hope.
Whoever you are (players deciding whether a wager is mathematically worth taking), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Business & Entrepreneurship, a dated figure is a trend, and an undated one is a rumour.