Sharpe Ratio Calculator
The formula
What the sharpe ratio tells you
The Sharpe ratio compresses a fund's entire return history into one number: how much you were paid for each unit of total risk taken. William Sharpe introduced it in 1966 to compare mutual funds fairly — a manager with higher returns but twice the volatility may actually be worse.
Calculation: Sharpe = (Rp − Rf) ÷ σp. Enter your inputs and every substitution is shown below the result.
Reading the result
A negative Sharpe means the risk-free asset beat you. Ratios between 0 and 1 describe most real portfolios; above 1 is strong, and figures above 2 are rare over full market cycles and usually signal a short sample, low rates or smoothing.
Rules of thumb: < 0 worse than cash · 0–1 typical · 1–2 good · ≥ 2 excellent (often a red flag for backtest overfitting)
Limitations and best practice
Sharpe assumes returns are roughly normal and treats all volatility as bad, penalizing upside surprises the way a value investor would not. Compare it only across similar horizons and frequencies — monthly data flatters ratios versus annual data.
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
Is a Sharpe ratio of 1 good?
Why does my fund's Sharpe change with the risk-free rate?
Can Sharpe be negative?
Sharpe vs Sortino — which matters more?
Source & methodology
Sharpe, W. F. (1966) "Mutual Fund Performance"; Sharpe (1994) "The Sharpe Ratio", Financial Analysts Journal.
Sharpe Ratio: what this tool answers
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. Sharpe Ratio is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get Sharpe ratio in real time, and see every substitution printed below.
In plain terms, Sharpe Ratio answers the question "Sharpe ratio?". The measurement matters because it converts a situation that feels complicated — several inputs pulling in different directions — into a single number you can act on. Within Investing & Markets, Portfolio Management is the context where this figure is quoted most often, and professionals treat it as a first-pass screen rather than a verdict.
The number itself is the easy part. What takes judgement is knowing which inputs are facts in your situation and which are guesses wearing a decimal point — a distinction this page makes explicit for every field above.
Every figure in the prose is generated by the engine rather than written beside it — the worked example resolves to sharpe ratio = 0.33 on the default inputs, and the sensitivity section ranks the inputs that move the result — Expected portfolio return first, at ≈20.0 % of the headline for a ten-percent error either way in that input. Read the sections in order and you will be able to reproduce every figure by hand.
Inside the Sharpe Ratio calculation: formula and every input
Here is the complete model this tool runs — Sharpe = (Rp − Rf) ÷ σp — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
Expected portfolio return (%) (example value 10) is a quantity rather than a category — precision here is cheap and worth having. Enter it exactly as your document states it — quoted annual, monthly and effective rates are three different numbers.
Risk-free rate (%) (example value 5) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Rates are the most mis-transcribed input on any page like this; copy it from the document rather than retyping from memory.
Portfolio volatility (%) (example value 15) is a measured number in the unit named by the label; the formula does not convert for you. Rates are the most mis-transcribed input on any page like this; copy it from the document rather than retyping from memory.
Sharpe Ratio on the example inputs: the complete substitution
The tool prints its own working; this is the same arithmetic on the example values, reproduced so you can follow it by hand. Starting figures: Expected portfolio return (%), Risk-free rate (%), Portfolio volatility (%). The endpoint of that chain is 0.33 of sharpe ratio, sitting in the “Acceptable” band.
- Excess return = 10% − 5% = 5.00%
- Sharpe = 5.00 ÷ 15 = 0.33
- Interpretation: each unit of volatility earns 0.33 units of excess return
Excess return over cash — 5.00 %. Compare it against the main result of 0.33 before drawing conclusions.
Volatility that would still give Sharpe 1 — 5.00 %. Read next to the headline, this is the figure that shows the shape of the trade-off.
Sharpe if volatility were halved — 0.67. If your inputs change, this is usually the first companion figure to move.
Sharpe if returns were 2% higher — 0.47. This is the number experienced users quote when the headline alone would mislead.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
Scenario table: Sharpe Ratio at ±10 % and ±20 % of the key input
The honest version of any estimate is a corridor, and this one is cheap to produce: Sharpe Ratio was recomputed at 5 points along the dominant input, with every other field left untouched.
| Expected portfolio return setting | Sharpe ratio |
|---|---|
| 80 % of the example value | 0.20 |
| 90 % of the example value | 0.27 |
| example inputs | 0.33 |
| 110 % of the example value | 0.40 |
| 120 % of the example value | 0.47 |
The corridor runs from 0.20 to 0.47 across that band — which is the range worth planning inside rather than the single 0.33 point estimate. Reproduce it in the form above by editing Expected portfolio return alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Sharpe Ratio the most
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the sharpe ratio. Read it as a map of where Sharpe Ratio is fragile — drawn for the example inputs, which is the map you want when deciding what to measure carefully.
- Nudge Expected portfolio return by ±10 % and Sharpe Ratio lands between 0.27 and 0.40 (sensitivity ≈20.0 %)
- Portfolio volatility: ten percent up gives 0.30, ten percent down gives 0.37 — ≈11.1 % of the sharpe ratio either way
- Nudge Risk-free rate by ±10 % and Sharpe Ratio lands between 0.30 and 0.37 (sensitivity ≈10.0 %)
Expected portfolio return is the dominant lever here: ten percent either way moves the result by about 20.0 %, from 0.27 to 0.40. That is where a careless figure does the most damage, so check it against a source, and treat Portfolio volatility as the second priority (≈11.1 % 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.
Is your Sharpe Ratio good — reading the result bands
A number on its own is trivia; a number against a range is intelligence. The verdict attached to the default calculation — “Acceptable” — is one band on a ladder your own figure may sit somewhere else on. The sensitivity list shows how far a modest input error moves you along that ladder: for Expected portfolio return, ±10 % covers 0.27 to 0.40. 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.
In Investing & Markets, Sharpe Ratio is one instrument in an orchestra: on its own it is a number, next to Excess return over cash and Volatility that would still give Sharpe 1 it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
How people get Sharpe Ratio wrong
Sharpe assumes returns are roughly normal and treats all volatility as bad, penalizing upside surprises the way a value investor would not. Compare it only across similar horizons and frequencies — monthly data flatters ratios versus annual data. 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.
Reporting the headline and quietly discarding Excess return over cash. The companions are where the shape of the trade-off survives the rounding.
This model has its own particular trap: Expected portfolio return carries ≈20.0 % of the response per ten percent of error, so effort spent elsewhere is largely decorative.
The subtlest error is answering the wrong question precisely. Confirm that sharpe ratio is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
Sharpe Ratio verification checklist
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Re-run the calculation with a ±10 % stress on the two most sensitive inputs.
- Check Expected portfolio return before anything else: it is the measured dominant input, ≈20.0 % of Sharpe Ratio per ten percent.
- Note the date and the inputs beside the number so the figure can be audited later.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
How to use the Sharpe Ratio tool properly
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 — gather before you type. Sharpe Ratio depends on expected portfolio return (%), risk-free rate (%), portfolio volatility (%). 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. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Step 2 — baseline before exploration. Get one defensible Sharpe ratio on screen before you start nudging numbers. Without a baseline, every variation looks interesting and none of them means anything. A calculation you cannot explain to somebody else is a calculation you cannot defend.
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. Re-running a number costs seconds; retracting a decision costs considerably more.
Step 4 — stress before you commit. A decision that survives a ten-percent squeeze on its two biggest inputs needs no luck to be sound. One that does not survive is a decision about hope, not about arithmetic. When in doubt, prefer the boring input: the interesting one is usually the one you misread.
Step 5 — schedule the next run. In Investing & Markets the inputs drift quietly. Put a reminder a quarter out, re-enter the same fields, and read the change rather than the level. Most surprises in numbers are surprises about inputs, not about formulas.
The real-world conversations Sharpe Ratio settles
Numbers earn their keep in conversations, and Sharpe Ratio is no exception. In Investing & Markets discussions around Portfolio Management, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Most surprises in numbers are surprises about inputs, not about formulas.
Used properly this is a five-minute filter that saves weeks. Compute Sharpe Ratio, reject what fails, and only then bring in the expensive analysis for the survivors. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
Treat Sharpe Ratio like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. The inputs are the part of the work that nobody else can do for you.
Sharpe Ratio — frequently asked questions
What affects Sharpe Ratio the most?
Measured on this engine, Expected portfolio return is the dominant lever: moving it ±10 % shifts the sharpe ratio across 0.27 to 0.40 — about 20.0 % of the headline, with Portfolio volatility next at ≈11.1 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: portfolio volatility or expected portfolio return?
Expected portfolio return, by a factor of about 1.8. Concretely: ten percent on Expected portfolio return is worth ≈20.0 % of Sharpe Ratio, the same nudge on Portfolio volatility only ≈11.1 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Sharpe Ratio?
There is no honest universal average for Sharpe Ratio, but there is a reference point: the defaults on this page produce 0.33 (Acceptable). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Sharpe Ratio by hand?
Three steps: write the formula (Sharpe = (Rp − Rf) ÷ σp), 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 Sharpe Ratio than any number of calculator runs.
What happens to Sharpe Ratio if expected portfolio return changes by 10 %?
On these inputs a ±10 % change in expected portfolio return takes Sharpe Ratio to 0.40 against the 0.33 example — around 20.0 % of the headline. The same test on every other field is in the sensitivity section.
Is the Sharpe Ratio result of 0.33 good or bad?
The tool answers “what”, not “whether”: 0.33 carries the verdict “Acceptable” 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 do I calculate Sharpe Ratio manually?
Write down the inputs, then follow the printed steps in order — Sharpe = (Rp − Rf) ÷ σp. 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.
How often should I check Sharpe Ratio?
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. Sharpe Ratio is a snapshot, not a subscription; stale snapshots are the most common silent error in Investing & Markets planning.
Is a Sharpe ratio of 1 good?
Yes — historically a Sharpe near 1 is roughly what a well-run diversified equity portfolio delivers in normal markets; sustained figures above 2 are exceptional.
Why does my fund's Sharpe change with the risk-free rate?
Because the numerator is excess return. When T-bill yields jump from 1% to 5%, every fund's Sharpe drops even with identical performance — always check which rate was used.
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.
Key terms on this page
- Excess return over cash
- 5.00 % for the Sharpe Ratio worked case; it sits next to the main result because it carries context the headline leaves out.
- Volatility that would still give Sharpe 1
- 5.00 % in the default Sharpe Ratio calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Sharpe if volatility were halved
- 0.67 in the default Sharpe Ratio calculation — one of the secondary figures an experienced reader checks before trusting the primary number.
- Sharpe ratio
- The primary output of this tool: 0.33 for the default inputs, computed exactly from Sharpe = (Rp − Rf) ÷ σp.
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- A named zone on the range of plausible results; the example inputs land in “Acceptable”, and your inputs may not.
- Sensitivity (±10 %)
- How far the Sharpe Ratio moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
The model is published arithmetic implemented exactly as written: Sharpe = (Rp − Rf) ÷ σp. Source of record: Sharpe, W. F. (1966) "Mutual Fund Performance"; Sharpe (1994) "The Sharpe Ratio", Financial Analysts Journal. 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.
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. Nothing is smoothed, weighted or adjusted behind the scenes; where judgement enters, this page says so and names the input responsible.
What to do with your Sharpe Ratio next
Re-run the calculation with your own figures, stress the two most sensitive inputs by ±10 %, and only then act on the result.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Investing & Markets, a dated figure is a trend, and an undated one is a rumour.