# Sharpe Ratio

> The Sharpe ratio measures return per unit of risk. Learn the formula, how to annualise it, what counts as a good Sharpe ratio, its limitations and common mistakes.

Source: https://learn.tradelabsai.com/portfolio/sharpe-ratio/  
Track: Portfolio and Performance · Level: Intermediate · Updated: 2026-10-03  
Publisher: TradeLabs AI (https://tradelabsai.com). Education, not financial advice.  
Cite as: TradeLabs Learn, "Sharpe Ratio", https://learn.tradelabsai.com/portfolio/sharpe-ratio/

The Sharpe ratio is the most widely used measure of risk adjusted performance. Developed by economist William F. Sharpe in 1966, it divides a strategy's excess return over a risk free rate by the volatility of its returns. A higher Sharpe ratio means more return for each unit of risk taken. It lets you compare a calm strategy earning 8% with a wild one earning 20% on equal terms, and it is the first number most professional allocators look at.

## The formula

```
Sharpe ratio = (Portfolio return - Risk free rate) / Standard deviation of returns
```

- **Portfolio return:** usually annualised.
- **Risk free rate:** typically the yield on short term government bills. See [Treasury Bills, Notes and Bonds](https://learn.tradelabsai.com/bonds-credit/treasury-bills-notes-and-bonds/).
- **Standard deviation:** the annualised volatility of returns. See [Variance and Standard Deviation](https://learn.tradelabsai.com/math/variance-and-standard-deviation/).

**Example: Comparing two strategies**
Strategy A returns 12% a year with 16% volatility. Strategy B returns 9% with 8% volatility. With a risk free rate of 4%, A's Sharpe ratio is (12 minus 4) divided by 16, or 0.50. B's is (9 minus 4) divided by 8, or about 0.63. B delivers more return per unit of risk. If you wanted A's higher return, you could in principle use modest leverage on B: doubling B's exposure (ignoring borrowing cost above the risk free rate) gives 14% return with 16% volatility, beating A at the same risk. See [Leverage](https://learn.tradelabsai.com/markets/leverage/).

## Annualising the Sharpe ratio

When working with daily returns, compute the mean and standard deviation of daily excess returns, divide, then multiply by the square root of 252 (trading days). With a mean daily excess return of 0.04% and daily volatility of 1%, the daily Sharpe is 0.04, and the annualised Sharpe is 0.04 times about 15.87, or roughly 0.63. Use monthly data with the square root of 12. Try the numbers in the [Sharpe and Sortino Calculator](https://learn.tradelabsai.com/tools/sharpe-and-sortino-calculator/).

## What is a good Sharpe ratio?

| Sharpe ratio | Typical interpretation |
|---|---|
| Below 0 | Worse than the risk free rate |
| 0 to 0.5 | Weak, similar to many long only equity holdings over long periods |
| 0.5 to 1.0 | Decent |
| 1.0 to 2.0 | Very good, especially if sustained live |
| Above 2.0 | Exceptional; in backtests, often a sign of overfitting or missing costs |

Broad stock market indices have historically delivered long run Sharpe ratios roughly in the 0.3 to 0.5 range, depending on the period. Context matters: high frequency strategies can sustain much higher ratios with limited capacity. See [Alpha Capacity and Crowding](https://learn.tradelabsai.com/research/alpha-capacity-and-crowding/).

## Limitations

| Limitation | Why it matters |
|---|---|
| Treats upside and downside volatility equally | Penalises big gains. See [Sortino Ratio](https://learn.tradelabsai.com/portfolio/sortino-ratio/) |
| Assumes returns are roughly normal | Ignores fat tails and skew. See [Fat Tails](https://learn.tradelabsai.com/math/fat-tails/) |
| Can be gamed | Selling options produces smooth returns until a crash. See [Short Put](https://learn.tradelabsai.com/options/short-put/) |
| Sensitive to measurement period | Short records give unreliable estimates |
| Smoothed or illiquid prices | Understated volatility inflates the ratio |

## Statistical uncertainty

The Sharpe ratio is an estimate with error. Roughly, the standard error of an annualised Sharpe ratio is about the square root of (1 divided by the number of years) for modest ratios. With 4 years of data, that is about 0.5, so a measured Sharpe of 1.0 could plausibly reflect a true value anywhere from near 0 to 2. Long track records matter. See [Sampling and Standard Error](https://learn.tradelabsai.com/math/sampling-and-standard-error/) and [Statistical Significance in Trading](https://learn.tradelabsai.com/math/statistical-significance/).

## Common mistakes

1. **Annualising incorrectly,** for example multiplying the daily ratio by 252 instead of its square root.
2. **Ignoring costs** in backtest Sharpe ratios.
3. **Comparing Sharpe ratios** from different periods or frequencies.
4. **Trusting very high backtest ratios.** See [Overfitting and Curve Fitting](https://learn.tradelabsai.com/research/overfitting-and-curve-fitting/).
5. **Using it alone** without drawdown and tail measures. See [Maximum Drawdown](https://learn.tradelabsai.com/portfolio/maximum-drawdown/).

## Frequently asked questions

### What does the Sharpe ratio measure?

Excess return over the risk free rate per unit of volatility, showing how much return a strategy earns for the risk it takes.

### What is a good Sharpe ratio for a trading strategy?

Above 1.0 sustained in live trading is very good; backtest figures above 2.0 deserve scepticism.

### How do I annualise a Sharpe ratio from daily returns?

Divide the mean daily excess return by the daily standard deviation, then multiply by the square root of 252.

Next, learn a version that only penalises downside risk in [Sortino Ratio](https://learn.tradelabsai.com/portfolio/sortino-ratio/).

## Continue learning

- Next lesson: [Sortino Ratio](https://learn.tradelabsai.com/portfolio/sortino-ratio/)
- Previous lesson: [Measuring Returns and CAGR](https://learn.tradelabsai.com/portfolio/measuring-returns-and-cagr/)
- Related: [Measuring Returns and CAGR](https://learn.tradelabsai.com/portfolio/measuring-returns-and-cagr/): Learn how to measure trading and investment returns correctly: simple and log returns, CAGR, arithmetic versus geometric averages, and money weighted returns.
- Related: [Sortino Ratio](https://learn.tradelabsai.com/portfolio/sortino-ratio/): The Sortino ratio divides excess return by downside deviation, penalising only harmful volatility. Learn the formula, a worked example and when to prefer it.
- Related: [Sharpe and Sortino Calculator](https://learn.tradelabsai.com/tools/sharpe-and-sortino-calculator/): Free Sharpe and Sortino ratio calculator. Paste your monthly, weekly or daily returns and get annualised return, volatility, Sharpe and Sortino ratios.
- Related: [Information Ratio and Tracking Error](https://learn.tradelabsai.com/portfolio/information-ratio/): The information ratio divides active return by tracking error to measure how consistently a portfolio beats its benchmark. Learn the formulas, values and uses.
- Related: [Treynor Ratio](https://learn.tradelabsai.com/portfolio/treynor-ratio/): The Treynor ratio divides excess return by beta to measure reward for market risk. Learn the formula, a worked comparison and how it differs from the Sharpe ratio.