Return Loss Calculator
The formula
What the return loss tells you
Exactly what return loss earned: total return, the annualised CAGR that makes it comparable, and the split between price gain and income.
Calculation: Total return = (sell + income − buy) ÷ buy; CAGR = ((sell + income) ÷ buy)^(1/years) − 1. Enter your inputs and every substitution is shown below the result.
Reading the result
Compare with the boring alternative over the same window — the verdict bands anchor to long-run market returns; income-heavy gains are usually steadier than price-only ones.
Rules of thumb: Long-run real equity return sits near 6–7 % nominal CAGR plus inflation; bonds run 2–4 points lower.
Limitations and best practice
Ignoring the timing of income (reinvested vs spent) can overstate a CAGR by a few tenths; dividends spent as cash belong outside the ending value.
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 does CAGR differ from average yearly return?
Are taxes included?
Source & methodology
Time-weighted return arithmetic per CFA Institute conventions.
Return Loss: the number, the method and the caveats
You are comparing options that arrive in different shapes, and Return Loss is the level playing field that makes them comparable. Searchers land on a Return Loss page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
What makes Return Loss worth calculating is not precision but position: it tells you which side of a threshold you are on, and by how much. A rough figure that settles the direction beats an elaborate one that never commits.
There is a habit that separates people who get useful answers from Physics Laboratory numbers: they decide what question the figure answers before they compute it. Return Loss answers “Total return?” — and nothing else, which is precisely why the result is trustworthy.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here total return = 46.19%, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Buy price / invested first, at ≈35.2 % of the headline for a ten-percent error either way in that input. Work down the page and by the end you could re-derive the result in a spreadsheet from memory.
Every input in Return Loss, and what it does to the answer
One formula, published in full: Total return = (sell + income − buy) ÷ buy; CAGR = ((sell + income) ÷ buy)^(1/years) − 1. 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.
Buy price / invested ($) (example value 15,500) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. If your source quotes a figure before and after some deduction, decide which one the formula wants and be consistent for every field.
Sell price / value now ($) (example value 22,250) is a measured number in the unit named by the label; the formula does not convert for you. Keep every money input in the same currency; mixing systems quietly corrupts the comparison.
Holding period (years) (example value 8) is a quantity rather than a category — precision here is cheap and worth having. Use the value as of today, not as of the last time you looked — time fields drift silently.
Income received over the hold ($) (example value 410) is a quantity rather than a category — precision here is cheap and worth having. If your source quotes a figure before and after some deduction, decide which one the formula wants and be consistent for every field.
Return Loss with real numbers, step by step
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Buy price / invested ($), Sell price / value now ($), Holding period (years), Income received over the hold ($). The computed total return comes out at 46.19%, which the interpretation band labels “Modest gain — check it after inflation and costs”.
- Ending value incl. income = $22,250.00 + $410.00 = $22,660.00
- Total return = (22,660.00 − 15,500.00) ÷ 15,500.00 = 46.19 %
- CAGR = (22,660.00 ÷ 15,500.00)^(1/8.0) − 1 = 4.86 % a year
Annualised (CAGR) — 4.86%. Read next to the headline, this is the figure that shows the shape of the trade-off.
Net profit — $7,160.00. This is the number experienced users quote when the headline alone would mislead.
Value multiple — 1.46 ×. Compare it against the main result of 46.19% before drawing conclusions.
Income share of gain — 5.7%. If your inputs change, this is usually the first companion figure to move.
Re-running with your own figures is instant; re-running by hand once is the best way to know the tool is telling you the truth.
The Return Loss 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 Return Loss, not an interpolation.
| Buy price / invested setting | Total return |
|---|---|
| 80 % of the example value | 82.74% |
| 90 % of the example value | 62.44% |
| example inputs | 46.19% |
| 110 % of the example value | 32.90% |
| 120 % of the example value | 21.83% |
The corridor runs from 21.83% to 82.74% across that band — which is the range worth planning inside rather than the single 46.19% point estimate. Reproduce it in the form above by editing Buy price / invested alone; the substitution steps will follow your figures exactly.
Where Return Loss is fragile — and where it is not
Generic advice says “it depends on your inputs”; this section says exactly how much. Each field was perturbed by ±10 % in isolation and the total return recomputed, so the ranking below is measured rather than asserted. It is the fastest honest answer to “what matters most in Return Loss?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Nudge Buy price / invested by ±10 % and Return Loss lands between 32.90% and 62.44% (sensitivity ≈35.2 %)
- Sell price / value now +10 % → Return Loss = 60.55% · −10 % → 31.84% (the total return shifts ≈31.1 %)
- Income received over the hold +10 % → Return Loss = 46.46% · −10 % → 45.93% (the total return shifts ≈0.6 %)
Buy price / invested is the dominant lever here: ten percent either way moves the result by about 35.2 %, from 32.90% to 62.44%. Spend your verification effort there first, and treat Sell price / value now as the second priority (≈31.1 % 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.
What a Return Loss of 46.19% means in practice
A number on its own is trivia; a number against a range is intelligence. The default case lands in the “Modest gain — check it after inflation and costs” band, and bands are deliberately wide because real situations overlap. How much of that band is luck? On Buy price / invested alone ten percent either way covers 32.90% to 62.44%. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
Set Return Loss beside its neighbours and it usually plays a specific role: this figure establishes the size of something, and the neighbouring tools establish whether that size is acceptable. Skipping the first step makes the second one arbitrary.
Common mistakes with Return Loss (and the fix)
Ignoring the timing of income (reinvested vs spent) can overstate a CAGR by a few tenths; dividends spent as cash belong outside the ending value. 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.
Confusing a large number with an important one. Return Loss can be dominated by one input whose absolute value looks unimpressive, which is why this page ranks influence separately from magnitude.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Buy price / invested first, everything else second.
A final trap is presentation: reporting Return Loss to more decimal places than the inputs support. The tool prints what the arithmetic gives; you should quote only what your least precise field justifies.
Six things to confirm before acting on Return Loss
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Note the date and the inputs beside the number so the figure can be audited later.
- Put Buy price / invested under a magnifier; the sensitivity table above is the reason why.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
Five steps from raw inputs to a figure you can defend
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — start from evidence. The inputs behind Return Loss are buy price / invested ($), sell price / value now ($), holding period (years), income received over the hold ($). Write them down with their source next to each one; if you cannot name where a figure came from, that is the input most likely to be wrong. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
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. When in doubt, prefer the boring input: the interesting one is usually the one you misread.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. A figure with a date beside it becomes evidence; without one it stays an anecdote.
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. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Step 5 — save the story with the figure. A number without its inputs and its date is unusable within a quarter. Record 46.19%, the assumptions behind it, and today’s date; your future self will be auditing a stranger’s arithmetic. Note the assumption you are least sure about; that is where the real risk lives.
The real-world conversations Return Loss settles
Science & Research arguments end at arithmetic or they do not end. Return Loss is the arithmetic: 46.19% on the example inputs, reproducible by anyone who types the same numbers. If a result feels obviously right, that is the moment to check the inputs hardest.
The audience for this page is investors and founders comparing opportunities on equal terms. In professional Physics Laboratory practice the pattern is always the same — screen with Return Loss, then invest slow analysis only in whatever survives the screen. Numbers are cheap to produce and expensive to retract; the extra minute is the cheapest insurance available.
Re-running this page costs nothing and catches the slow drifts that never announce themselves. In Science & Research the expensive mistakes are rarely sudden; they are small changes in Buy price / invested ($) that nobody recalculated for a year. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
People also ask about Return Loss
What affects Return Loss the most?
Measured on this engine, Buy price / invested is the dominant lever: moving it ±10 % shifts the total return across 32.90% to 62.44% — about 35.2 % of the headline, with Sell price / value now next at ≈31.1 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: sell price / value now or buy price / invested?
Buy price / invested, by a factor of about 1.1. Concretely: ten percent on Buy price / invested is worth ≈35.2 % of Return Loss, the same nudge on Sell price / value now only ≈31.1 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Return Loss?
On the worked example above Return Loss comes out at 46.19%. Treat that as one point on a distribution rather than a norm: the bands, the companion outputs and the sensitivity ranking tell you how wide the plausible range really is.
How do I calculate Return Loss by hand?
Use the stated model — Total return = (sell + income − buy) ÷ buy; CAGR = ((sell + income) ÷ buy)^(1/years) − 1 — and substitute in the order the tool prints (it starts from Ending value incl. income = $22,250.00 + $410.00 = $22,660.00). On the example inputs the hand route lands on 46.19%, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Return Loss if buy price / invested changes by 10 %?
On these inputs a ±10 % change in buy price / invested takes Return Loss to 32.90% against the 46.19% example — around 35.2 % of the headline. The same test on every other field is in the sensitivity section.
Is the Return Loss result of 46.19% good or bad?
The tool answers “what”, not “whether”: 46.19% carries the verdict “Modest gain — check it after inflation and costs” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
How many significant figures are reliable in Return Loss?
About as many as your least precise input. The tool computes at full precision and displays rounded output; report 46.19% to a decimal place your inputs can actually support.
How often should I check Return Loss?
Whenever an input changes by more than a few percent, and otherwise on the rhythm of your decisions — before a purchase, a review, a renewal. Return Loss is a snapshot, not a subscription; stale snapshots are the most common silent error in Science & Research planning.
Why does CAGR differ from average yearly return?
CAGR compounds — it is the single steady rate that turns the start into the end, while arithmetic averages flatter volatile paths.
Are taxes included?
No, this is the pre-tax picture; subtract tax drag on gains and income before comparing with a tax-sheltered alternative.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
What the labels on this page mean
- Annualised (CAGR)
- 4.86% for the Return Loss worked case; it sits next to the main result because it carries context the headline leaves out.
- Net profit
- $7,160.00 on the example inputs — a companion figure printed beside the headline of Return Loss so that no result is read in isolation.
- Value multiple
- 1.46 × in the default Return Loss calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Total return
- The primary output of this tool: 46.19% for the default inputs, computed exactly from Total return = (sell + income − buy) ÷ buy; CAGR = ((sell + income) ÷ buy)^(1/years) − 1.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The plain-language label — here “Modest gain — check it after inflation and costs” — mapping the computed figure onto experience-based ranges for Science & Research.
- Sensitivity (±10 %)
- How far the Return Loss 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
The model is published arithmetic implemented exactly as written: Total return = (sell + income − buy) ÷ buy; CAGR = ((sell + income) ÷ buy)^(1/years) − 1. Source of record: Time-weighted return arithmetic per CFA Institute conventions. Any other implementation of this model should return the same figure for the same inputs. If one does not, the difference is in its assumptions — which this page prints and that one probably does not.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The promise to the reader is narrow and testable: same inputs, same output, no silent rounding, and no figure presented without the formula that produced it.
Turning this Return Loss into a decision
Pair this figure with the companion outputs above — the headline sizes the prize, the companions describe the risk.
The audience here is investors and founders comparing opportunities on equal terms. Everything you need to defend the result — formula, substitution, sensitivity, source — is printed above, so the only remaining variable is the honesty of your inputs.