Sharpe Ratio Calculator
Calculate the Sharpe ratio to measure risk-adjusted portfolio returns.
What this calculator does
The Sharpe ratio, developed by William Sharpe in 1966, addresses the fact that raw returns tell you nothing about what was risked to get them. It divides excess return — the return above the risk-free rate — by the standard deviation of those returns.
The result is a return-per-unit-of-risk figure. A portfolio returning 20 percent with wild swings may be a worse holding than one returning 12 percent steadily, because the second requires far less tolerance for drawdown and is far easier to hold through a bad year without abandoning.
When to use it
The Sharpe ratio is most useful comparing two strategies or funds with genuinely different volatility profiles, where a raw return comparison would be misleading. It is also the standard way to test whether a manager's outperformance came from skill or simply from taking more risk than the benchmark.
It matters most when leverage is involved. Leverage can turn almost any positive-return strategy into a high-return strategy, but it barely moves the Sharpe ratio, because both numerator and denominator scale together. That property makes Sharpe an effective filter against returns that are merely borrowed.
Understanding the inputs
Portfolio return should be the annualized return over the measurement period, and it needs to be net of fees to mean anything. The risk-free rate should be a Treasury yield matched to the same horizon.
Standard deviation is annualized volatility. If you are computing it from monthly returns, take the monthly standard deviation and multiply by the square root of twelve. Use a measurement window of at least three years, and preferably five or more — shorter periods produce ratios dominated by chance rather than by any real property of the strategy.
How is this calculated?
Sharpe Ratio = (Portfolio Return − Risk-Free Rate) / Standard Deviation
A worked example
Portfolio A returned 9.2 percent annually with a standard deviation of 12.5 percent. With a risk-free rate of 4.3 percent, its excess return is 4.9 percent, giving a Sharpe ratio of 0.39.
Portfolio B returned only 7.5 percent, but with a standard deviation of 6 percent. Its excess return of 3.2 percent divided by 6 gives a Sharpe of 0.53. B produced less return but was substantially more efficient with risk. An investor able to use leverage could scale B up toward A's return while still taking less total risk.
Limitations and assumptions
Standard deviation treats upside and downside volatility identically and assumes normally distributed returns, which markets consistently violate — large moves happen far more often than the model implies. Strategies with hidden tail risk, such as option selling, can post excellent Sharpe ratios for years before failing badly.
The ratio is backward-looking and past returns do not predict future ones. It says nothing about maximum drawdown, liquidity, or leverage embedded in a strategy, and the calculator assumes a flat return with no volatility in its projections. This is not investment advice.
Common Questions
- What does the Sharpe ratio measure?
- How much return a portfolio earned above the risk-free rate, per unit of volatility taken. Portfolio return minus the risk-free rate, divided by standard deviation. It answers whether a high return came from skill and sensible risk-taking or simply from holding something that swung around a great deal.
- What is a good Sharpe ratio?
- As a rough guide, below 1.0 is unremarkable, 1.0 to 2.0 is good, above 2.0 is excellent, and above 3.0 should invite scepticism about the data. For context, the S&P 500's long-run Sharpe ratio sits at roughly 0.4 to 0.5 — good ratios are harder to achieve than the scale suggests.
- Which risk-free rate should I use?
- A Treasury yield matched to your measurement horizon — the 3-month T-bill for short periods, a longer maturity for multi-year analysis. The choice matters more than people assume: when T-bills paid 5 percent rather than near zero, every portfolio's Sharpe ratio dropped without anything changing in the portfolio itself.
- Why is standard deviation a flawed measure of risk?
- Because it penalizes upside volatility identically to downside. A fund that occasionally jumps 15 percent is scored as risky as one that occasionally drops 15 percent. It also assumes returns are normally distributed, which understates the frequency of extreme moves that markets actually produce.
- What is the Sortino ratio?
- A variant that divides excess return by downside deviation only, ignoring upside volatility. For strategies with asymmetric return profiles it gives a fairer picture than Sharpe. A fund with a mediocre Sharpe but a strong Sortino is one whose volatility mostly happens in the right direction.
- Can the Sharpe ratio be gamed?
- Readily. Selling out-of-the-money options produces steady small gains and an outstanding Sharpe ratio right up until a tail event erases years of returns. Illiquid assets marked infrequently show artificially low volatility for the same reason. A very high Sharpe on a short track record deserves suspicion, not admiration.
- Can it be negative?
- Yes, whenever the portfolio returned less than cash. A negative Sharpe means you took volatility risk and were paid less than a Treasury bill for it. The magnitude of a negative Sharpe is not very informative though — higher volatility makes a negative ratio smaller, which is perverse.
- How does time period affect the ratio?
- Substantially, and the annualization convention matters. Monthly Sharpe ratios are typically annualized by multiplying by the square root of twelve, which assumes returns are independent across months. Where returns are serially correlated, as in many hedge fund strategies, this overstates the annualized figure.
- Should I use the Sharpe ratio to pick funds?
- As one input over a long window, yes. Over three years or less it is mostly noise. It also cannot compare across risk profiles usefully on its own — a bond fund and an equity fund with similar Sharpe ratios are not interchangeable, because absolute return levels differ enormously.