The Sharpe ratio quantifies how much return a trading strategy generates per unit of risk. By subtracting the risk-free rate from portfolio returns and dividing by volatility, it produces a single number that makes comparing strategies with different risk profiles straightforward. The calculator above computes this instantly from your inputs.
How to Use
| Input | What to Enter | Example |
|---|---|---|
| Portfolio Return | Annualized return of your trading strategy | 18% |
| Risk-Free Rate | Current US Treasury bill yield | 5% |
| Standard Deviation | Annualized standard deviation of your returns | 12% |
The output is a single ratio. Interpret it against these benchmarks: below 1.0 is subpar, 1.0-2.0 is good, 2.0-3.0 is very strong, and above 3.0 is exceptional. A higher number means better risk-adjusted performance.
Formula Explained
Sharpe Ratio = (Rp - Rf) / σp
Rp (Portfolio Return) is your annualized return. If your strategy returned 3% per month, annualize it to approximately 36%. Consistency matters here — use the same time frame for all three inputs. Most traders track this in their trading journal over at least a full market cycle.
Rf (Risk-Free Rate) represents what you could earn with zero risk. The 3-month US Treasury bill yield is the standard benchmark. As of early 2026, this sits around 4.5-5%. This baseline ensures the Sharpe ratio only credits returns that exceed what a risk-free asset delivers. Choosing a rate that matches your measurement period avoids distortion.
σp (Standard Deviation) measures the volatility of your returns. High standard deviation means returns swing widely between periods. A strategy returning 2% every month with minimal variation has a low standard deviation, while one swinging between -8% and +15% has a high one. This is the denominator that punishes inconsistency — two strategies with identical returns will have different Sharpe ratios if one is more volatile.
Example Calculations
Scenario 1: Steady Swing Trading
- Portfolio Return: 18% annualized
- Risk-Free Rate: 5%
- Standard Deviation: 12%
- Result: Sharpe Ratio = (18% - 5%) / 12% = 1.08
This strategy earns 1.08 units of excess return per unit of risk. Solid performance that outpaces the risk-free rate with moderate volatility — typical of a disciplined swing trading approach on large-cap stocks.
Scenario 2: Aggressive Momentum Strategy
- Portfolio Return: 42% annualized
- Risk-Free Rate: 5%
- Standard Deviation: 28%
- Result: Sharpe Ratio = (42% - 5%) / 28% = 1.32
Despite much higher raw returns than Scenario 1, the Sharpe ratio is only modestly better because the volatility is substantially higher. This is why raw returns alone are misleading — the drawdown calculator reveals the pain behind those swings.
Scenario 3: Conservative Options Selling
- Portfolio Return: 14% annualized
- Risk-Free Rate: 5%
- Standard Deviation: 4%
- Result: Sharpe Ratio = (14% - 5%) / 4% = 2.25
The lowest raw return of the three, yet the highest Sharpe ratio by far. Tight consistency in returns compresses the denominator, rewarding the strategy’s predictability. This illustrates why many professional funds favor lower-volatility approaches.
When to Use the Sharpe Ratio
- Comparing two strategies — When deciding between a high-return volatile approach and a steady lower-return one, the Sharpe ratio provides an apples-to-apples comparison that raw P&L cannot.
- Evaluating strategy changes — After modifying entry rules, position sizing, or risk parameters, recalculate the Sharpe ratio to confirm the change improved risk-adjusted performance, not just returns.
- Portfolio allocation decisions — When running multiple strategies simultaneously, allocating more capital to higher-Sharpe strategies optimizes the overall portfolio’s risk-adjusted return.
- Performance reviews — Monthly or quarterly reviews should track the Sharpe ratio alongside total return. A declining Sharpe ratio with stable returns means volatility is increasing, which often precedes larger drawdowns.
- Benchmarking against the market — The S&P 500 has historically delivered a Sharpe ratio between 0.3 and 0.5. Consistently exceeding this confirms your active trading adds value beyond passive investing.
Related Tools
- Expectancy Calculator — Calculates the expected dollar return per trade based on win rate and average win/loss size. Use alongside the Sharpe ratio to understand both expected value and consistency.
- Drawdown Calculator — Measures peak-to-trough decline in your account. A high Sharpe ratio with deep drawdowns may indicate fat-tail risk the standard deviation misses.
- Profit & Loss Calculator — Computes raw P&L from entry and exit prices. Feed these results into the Sharpe ratio calculation for a complete performance picture.
Frequently Asked Questions
What is a good Sharpe ratio for a trading strategy?
A Sharpe ratio above 1.0 is considered good, meaning you earn more excess return than the volatility you take on. Above 2.0 is very strong, and above 3.0 is exceptional. Most professional hedge funds target a Sharpe ratio between 1.0 and 2.0.
What risk-free rate should I use for the Sharpe ratio?
Use the yield on short-term US Treasury bills matching your measurement period. As of early 2026, the 3-month T-bill yield near 4.5-5% is the standard choice. For non-US traders, use your country’s equivalent government short-term bond yield.
Can the Sharpe ratio be negative?
Yes. A negative Sharpe ratio means your portfolio returned less than the risk-free rate. You would have been better off holding Treasury bills. This signals the strategy is not compensating you for the risk taken.
How is the Sharpe ratio different from the Sortino ratio?
The Sharpe ratio penalizes all volatility equally, including upside moves. The Sortino ratio only penalizes downside deviation, making it more relevant for traders who care specifically about loss risk rather than total variance.
How many trades do I need for an accurate Sharpe ratio?
A minimum of 30 trades or 12 months of return data provides a statistically meaningful Sharpe ratio. Fewer observations make the standard deviation unreliable, producing a Sharpe ratio that can swing dramatically with each new data point.
