QuantOracle

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.

Inputs

Calls the deterministic /v1/stats/sharpe-ratio endpoint server-side.

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
30
Compute time
19 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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