What is a "good" Sharpe ratio?

For a long-only equity strategy or fund, a Sharpe of 0.5-1.0 is typical, 1.0-1.5 is good, and above 1.5 is excellent. Quant funds with diversified, market-neutral strategies often run Sharpes of 1.5-3.0. Sharpes above 3 over long periods are rare and usually reflect either undisclosed leverage, infrequent rebalancing (which understates volatility), or short track records (luck).

How does the annualization factor work?

The Sharpe ratio scales with the square root of the number of periods per year. For daily returns, multiply by sqrt(252). For weekly returns, sqrt(52). For monthly, sqrt(12). The annualization factor in this calculator is the number of periods per year (e.g. 252 for daily) — the calculator does the square-root scaling internally.

What confidence interval should I trust?

The Sharpe ratio has a standard error that depends on the number of observations and the Sharpe value itself. With only 30 daily returns, the 95% confidence interval is so wide it is almost useless — a sample Sharpe of 2.0 might really be anywhere from -1 to 5. You usually need 2-3 years of daily data (500-750 observations) to estimate a Sharpe with reasonable precision. The CI in the results tells you the range.

Should I use simple or log returns?

Either, but be consistent within a series. For daily data they are nearly identical because the values are small. For longer-period returns, log returns are generally preferred because they sum across periods, but Sharpe is most often quoted on simple returns by convention. Whatever you pick, do not mix.

What is the Probabilistic Sharpe Ratio?

The Probabilistic Sharpe Ratio (PSR), introduced by Marcos Lopez de Prado, is the probability that the true Sharpe is above a benchmark (e.g. zero, or 1.0) given the observed sample. It accounts for non-normal return distributions. The QuantOracle API exposes it at /v1/stats/probabilistic-sharpe.

What about Sortino ratio? Calmar ratio?

The Sortino ratio uses downside deviation instead of total standard deviation, so it does not penalize upside volatility. The Calmar ratio uses max drawdown instead of standard deviation. Both are alternatives to Sharpe that are more relevant for asymmetric strategies. They are computed by the QuantOracle composite endpoint /v1/risk/full-analysis.

Why is my Sharpe so high — is something wrong?

Implausibly high Sharpes (above 4-5 from real strategies) usually indicate one of: (1) a sample period too short to be meaningful; (2) returns that are autocorrelated (smoothed via infrequent valuations), which understates volatility; (3) survivorship bias in the data; or (4) an actual bug in the return calculation, like double-counting or missing dividends. Check these before celebrating.

How many returns do I need to enter?

Mathematically, two. Practically, you want at least 30-60 for the calculation to mean anything. For statistical significance you want 250+ (one trading year of daily data). The calculator works with any positive count; the results just become less reliable with fewer observations.

Is this calculator free?

Yes. Free for unlimited human use; backed by the QuantOracle API which provides 1,000 free calls per IP per day with no signup or API key.

Sharpe Ratio Calculator

Compute the Sharpe ratio of any return series with a configurable risk-free rate. Includes the 95% confidence interval, which most calculators omit but matters a lot for short samples.

Results

Annualized Sharpe ratio

3.440

95% CI: [-2.31, 9.19]· CI contains zero — not statistically distinguishable from no edge

Annualized return

45.02%

Annualized vol

11.92%

Excess return

41.02%

Std error of Sharpe

2.932

Observations

Compute time

10 ms

What does this mean?

The annualized Sharpe ratio of 3.44 is extremely high — verify the data is clean, but the 95% confidence interval (-2.31 to 9.19) crosses zero — with only 30 observations the result is not statistically significant. The strategy returned an annualized 45.02% at 11.92% volatility.

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Frequently asked questions

The Sharpe ratio measures risk-adjusted return: how much excess return a strategy generates per unit of volatility. It is the mean of the strategy returns minus the risk-free rate, all divided by the standard deviation of the returns. Higher is better. It was introduced by William Sharpe in 1966 and earned him the Nobel Prize in 1990.

Why Sharpe matters

Two strategies that returned 20% in a year are not equivalent if one ran at 10% volatility and the other at 40%. The first is twice as efficient with risk; over many years the lower- vol strategy will compound more reliably and have shallower drawdowns. The Sharpe ratio captures that distinction in one number: excess return per unit of volatility.

The formula

Per-period Sharpe = (mean return − risk-free rate) / std deviation. Annualized Sharpe scales by the square root of the number of periods per year: per-period Sharpe × √(periods per year). For daily data with 252 trading days, that means multiplying by ~15.87.

What the confidence interval tells you

Most online calculators just give you a Sharpe number. That is misleading: with 30 daily returns, a sample Sharpe of 2.0 might really be anywhere from -1 to +5. The 95% CI shown here uses Lo's 2002 standard error formula. A wide CI means "not enough data to say." A narrow CI that excludes zero means "there really is something here."

What Sharpe does NOT capture

Asymmetry. Sharpe penalizes upside volatility just as much as downside volatility. The Sortino ratio fixes this by using downside deviation only.
Tail risk. Sharpe assumes returns are roughly normal. Strategies that look great by Sharpe but have fat-tailed losses (e.g. selling out-of-the-money options) can blow up despite a high reported Sharpe.
Drawdown. The peak-to-trough loss along the way is invisible in Sharpe. Calmar ratio (return divided by max drawdown) addresses this.
Survivorship and selection bias. A backtest run on the current S&P 500 constituents has a higher Sharpe than the live strategy will, because failed companies were dropped from the index over time.

For more depth

For a fuller risk picture, the QuantOracle composite endpoint /v1/risk/full-analysis returns Sharpe alongside Sortino, Calmar, max drawdown, VaR, CVaR, and Kelly in a single call. For just downside risk, see the Value at Risk calculator.

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