Sharpe Ratio Calculator
Compute Sharpe ratio (risk-adjusted return) for any portfolio. Direct inputs or paste a return series. Benchmark table vs canonical asset classes.
Sharpe Ratio Calculator
How your portfolio compares
How to use the Sharpe Ratio Calculator
Pick a mode
Direct input: enter portfolio return, risk-free rate, and std dev directly. From series: paste a return series (monthly or annual) and the tool computes the mean + std dev for you.
Set the risk-free rate
The risk-free rate represents what you'd earn on a "safe" alternative — usually the US 10-year Treasury yield (currently ~4.5%) or 3-month T-bill rate (currently ~5%). For non-USD portfolios use the equivalent local sovereign yield: Singapore 10Y, UK gilt, German Bund, etc.
Get the Sharpe ratio
Formula: (Return − Risk-free) ÷ Std dev. A higher number means more return per unit of risk taken. Negative Sharpe means you underperformed the risk-free alternative — cash would have been better.
Compare against benchmarks
The benchmark table shows where canonical asset classes land: T-bills ≈ 0, S&P 500 long-term ≈ 0.3-0.5, top-decile hedge funds ≈ 1-2, Renaissance Medallion (legendary) ≈ 3.4. Sustained Sharpes above 2 are extraordinarily rare.
Sharpe Ratio — the most-used (and most-abused) risk metric in finance
William Sharpe published "Mutual Fund Performance" in 1966 with one elegant insight: returns are meaningless without context for risk. A 20% return earned with extreme volatility is not the same as a 20% return earned smoothly. He proposed a simple measure — excess return per unit of standard deviation — that lets you compare any two investments on a like-for-like basis. The metric carries his name, won him a Nobel Prize in Economics (1990), and is now the single most-cited risk-adjusted-return measure in finance. Every hedge fund prospectus, every mutual fund factsheet, every robo-advisor portfolio analysis shows a Sharpe number.
The math
Sharpe Ratio = (R_p − R_f) / σ_p. R_p is the portfolio's return over a period. R_f is the risk-free rate over the same period — usually short-term government debt (T-bills). σ_p is the standard deviation of the portfolio's returns, measuring volatility. The numerator captures "did I beat cash?" The denominator captures "how bumpy was the ride?" Divide and you have "return per unit of risk." Higher = better risk-adjusted returns. Negative = you took risk for less than what cash would have paid you (terrible — you'd have been better off in T-bills).
Renaissance Technologies' Medallion Fund has produced a Sharpe ratio of ~3.4 over 30+ years — possibly the highest sustained risk-adjusted return in financial history. Most hedge funds run 0.5-1.0. The S&P 500 long-term runs ~0.5.
Where Sharpe ratio leads astray
Sharpe assumes symmetric risk (treats upside volatility the same as downside). That's mathematically tidy but real investors only fear downside. A strategy that pays off small most of the time but occasionally explodes ("picking up nickels in front of a steamroller" — LTCM, AIG sub-prime, many crypto algorithms) shows a beautiful Sharpe right up until the crash. Other limitations: (1) requires normally-distributed returns — fails for fat-tailed strategies; (2) sensitive to sample period — Sharpe varies enormously across 1-, 5-, 10-year windows; (3) doesn't capture liquidity risk — illiquid investments look better than they should. Better metrics: Sortino ratio (downside std dev only), Calmar ratio (return ÷ max drawdown), tail-risk measures (VaR, CVaR).
The APAC portfolio use case
Sharpe ratio is fundamental in Singapore's sovereign wealth investing (GIC, Temasek both publish risk-adjusted returns), every Hong Kong hedge fund's marketing deck, and Malaysia's EPF + KWAP portfolio reports. ASEAN equity markets historically run higher returns AND higher volatility than developed markets — Sharpes typically land in similar 0.3-0.7 range as US/EU. The exception: low-correlation strategies (ASEAN small-cap, certain commodity exposures) can post higher Sharpes when sized and timed correctly. Use Sharpe as one of multiple metrics — never alone.
Sharpe 1966, the √12 annualisation, Sortino's downside variant, and Medallion's 3.4
William Sharpe published the original metric in 1966 in "Mutual Fund Performance." He won the Nobel Prize in Economics in 1990 (shared with Markowitz + Miller for portfolio theory).
The S&P 500's long-term Sharpe is ~0.4-0.6 (10% return, 4.5% risk-free, 16% std dev). Most equity strategies hover here despite marketing claims.
The Renaissance Medallion Fund reportedly has a Sharpe ratio of ~3.4 over 30+ years — possibly the highest sustained risk-adjusted return in financial history. Closed to outside investors since 1993.
"Annualised" Sharpe = monthly Sharpe × √12 (assuming returns are independent). Sharpes are usually quoted annually for comparability.
The Sortino ratio (Frank Sortino, 1994) is a variant that only uses downside volatility in the denominator — argues that upside variance shouldn't count as "risk."
Bitcoin's 10-year Sharpe ratio (2014-2024) is roughly 0.6-0.8 — high return (~60% annualised) but extreme volatility (~80%) make the risk-adjusted picture more modest.
The Sharpe ratio paradox: a strategy that frequently delivers small gains and occasionally blows up (e.g., selling out-of-the-money options) can look great on Sharpe until the crash arrives. LTCM had a Sharpe of ~4 the year before it imploded.
Sharpe assumes normally-distributed returns. Real financial returns have fat tails (more extreme outliers). For tail-heavy strategies, use Sortino, Calmar, or Omega ratios.
To "game" Sharpe: pick periods of low realised volatility, use a stale risk-free rate, or smooth returns through illiquid asset marks. Many hedge fund Sharpes presented to LPs are inflated this way.
Sharpe ratio is scale-invariant: doubling all returns and volatilities leaves it unchanged. This is why it's used to compare funds of different sizes and leverages on equal footing.
Frequently Asked Questions
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Rough guide: below 0 = bad (worse than cash). 0-0.5 = sub-par. 0.5-1.0 = acceptable, typical of broad equity indices. 1-2 = good, top-quartile hedge funds. 2-3 = excellent, rare. Above 3 = exceptional or suspicious — verify methodology.
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Match the duration of your investment. Short-term portfolio analysis → 3-month T-bill. Long-term retirement portfolio → 10-year Treasury. For non-USD investments, use the equivalent local sovereign yield (Singapore SGS 10Y, German Bund, UK gilt).
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Sample (n-1 divisor, Bessel correction) for actual return series — that's what this tool uses. Population (n divisor) only if you somehow have the entire infinite population of returns, which you don't in finance.
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Multiply by √12 (square root of periods per year). Daily Sharpe × √252 (trading days). The √ assumes returns are independent across periods, which is approximately true for liquid markets. For autocorrelated returns the adjustment is more complex (use Newey-West).
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Because the portfolio's return is below the risk-free rate. You took risk and earned less than cash would have paid. Common during bear markets (2008, 2022) or for poorly-allocated portfolios. Negative Sharpe → cash would have been objectively better.
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By construction, the risk-free rate has zero volatility (that's why it's "risk-free"). The denominator only needs the portfolio's σ. For more rigour use the std dev of "excess return" (portfolio return − risk-free), but the difference is small in practice.
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When the upside volatility doesn't bother you. Sortino only uses DOWNSIDE std dev — penalises losing volatility, ignores winning volatility. Useful for asymmetric-return strategies (long options, venture investing, anything with positive skew).
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For statistical significance: at least 36 monthly returns (3 years). For confident judgement: 5+ years. Sharpes computed on 12 months or less are highly noisy — they reflect the specific period more than the strategy.
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Sharpe still works mathematically. Bitcoin's high returns combined with high volatility produce Sharpes that aren't catastrophic (~0.6-0.8 long-term). But Sharpe alone doesn't capture the "I could lose 80% in a year" reality — supplement with max drawdown analysis (Calmar ratio).
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No. All calculation happens entirely in your browser via JavaScript. Open DevTools → Network and watch — there's zero outbound traffic. Safe for confidential portfolio analysis.
Method & sources
What this tool implements
- Excess return over the risk-free rate divided by standard deviation of returns.
- Annualisation multiplies the periodic ratio by the square root of periods, assuming independent returns.
Sources
- Sharpe WF. Mutual Fund Performance. Journal of Business 1966;39(1):119-138.
- Sharpe WF. The Sharpe Ratio. Journal of Portfolio Management 1994;21(1):49-58.
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