Sharpe ratio calculator

Raw return tells you nothing without the risk behind it. Paste a strategy's periodic returns to get its annualized Sharpe and Sortino ratios, mean return and volatility — the standard measures of risk-adjusted performance.

By Mustafa Bilgic · Published 2026-06-27 · Last updated 2026-06-27

Sharpe & Sortino Ratio Calculator

Paste your periodic returns to get risk-adjusted return

LIVE · client-side
Sharpe (annualized)
Sortino (annualized)
Mean return
Std deviation

Educational tool — not financial advice. The Sharpe ratio assumes roughly normal returns and needs a meaningful sample; strategies with rare large losses can show a flattering Sharpe until they fail. Automated trading carries a real risk of financial loss from slippage, fees, gaps and drawdowns. Never trade money you cannot afford to lose. Review the SEC investor.gov and CFTC resources before trading.

How the Sharpe ratio is calculated

The Sharpe ratio, introduced by Nobel laureate William F. Sharpe in 1966, measures how much excess return a strategy earns per unit of volatility — in other words, how much you are paid for the risk you take. Its formula is:

Sharpe = (mean return − risk-free rate) / standard deviation of returns

This calculator computes the per-period Sharpe from the returns you paste, then annualizes it by multiplying by the square root of the number of periods per year (252 for daily returns, 52 for weekly, 12 for monthly). It uses the sample standard deviation (dividing by n−1), the convention for a series of observations. A higher Sharpe means smoother, more efficient returns; a strategy that earns 30% with stomach-churning swings can have a worse Sharpe than one earning 15% steadily.

Sharpe, Sortino, and what counts as "good"

The catch with Sharpe is that it penalises all volatility, including the upside surprises you actually want. The Sortino ratio fixes this by dividing excess return only by downside deviation — the volatility of losing periods — so it rewards strategies whose swings are mostly to the upside. This tool shows both. As a rough industry guide, an annualized Sharpe below 1 is generally considered weak, around 1 to 2 is solid, 2 to 3 is very good, and above 3 is exceptional (and worth double-checking for overfitting or a too-short sample).

Sharpe needs enough data to mean anything

A Sharpe ratio from a dozen trades is mostly noise. It also assumes returns are roughly normally distributed, which strategies with rare large losses (selling options, martingales) violate — they can show a flattering Sharpe right up until they blow up. Read the full explainer in Sharpe ratio explained, and pair it with the drawdown picture before trusting any single number.

Frequently asked questions

How do I calculate the Sharpe ratio?

Subtract the risk-free rate from your mean periodic return, then divide by the standard deviation of those returns. To annualize, multiply by the square root of the number of periods per year — 252 for daily, 52 for weekly, 12 for monthly returns.

What is a good Sharpe ratio for a trading bot?

As a rough guide, an annualized Sharpe under 1 is weak, 1 to 2 is solid, 2 to 3 is very good and above 3 is exceptional. Very high values from short samples often reflect overfitting rather than genuine skill, so treat them with caution.

What is the difference between Sharpe and Sortino?

Sharpe divides excess return by total volatility, penalising upside and downside swings equally. Sortino divides only by downside deviation, so it does not punish a strategy for large gains. Sortino is often a fairer measure for strategies with asymmetric, upside-skewed returns.

Is my data sent anywhere?

No. The returns you paste are processed entirely in your browser with client-side JavaScript. Nothing is uploaded or stored, and there is no signup.

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Mustafa Bilgic

Algorithmic trading practitioner · Founder, AutomatedTradeBot.com

Mustafa builds and tests automated trading systems and writes about them without the hype. Every tool on this site is free, runs entirely in your browser, and shows its formula so you can check the math. Based in Adıyaman, Türkiye. Read more about this site and its methodology →