Sharpe, Sortino, and Calmar ratio calculator
Compute the three institutional risk-adjusted return metrics in one pass. Sharpe (excess return per unit of total volatility), Sortino (excess return per unit of downside volatility), and Calmar (return per unit of maximum drawdown). Each output includes a plain-English quality grade benchmarked against hedge fund and CTA track records. AUD-default risk-free rate sourced from current Australian government 10-year bond yield. The three metrics together are how institutional allocators evaluate any trading strategy or fund manager.
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Sharpe ratio
The original risk-adjusted return metric, introduced by Nobel laureate William F. Sharpe in 1966. Computed as:
Sharpe = (R - Rf) / σ
Where R is your annualised return, Rf is the risk-free rate, and σ is the annualised standard deviation of returns. The numerator captures excess return over a risk-free benchmark. The denominator captures the total volatility of the return series, treating upside and downside swings symmetrically.
Interpretation: a Sharpe of 1.0 means every unit of volatility produced one unit of excess return. A Sharpe of 2.0 means twice that efficiency. Higher is better. The metric is dimensionless and comparable across strategies of any size, time horizon, or asset class.
The Sharpe ratio is the default metric on every hedge fund tearsheet, every prop firm performance dashboard, and every Morningstar fund report. If you are pitching a strategy to allocators or assessing your own track record, Sharpe is what they will see first.
Sortino ratio
The Sortino ratio, introduced by Frank Sortino in the 1980s, addresses the main criticism of the Sharpe ratio: upside volatility is not risk. A strategy that occasionally has very large winning days has high total volatility but no investor would call those large winning days "risk". The Sortino ratio replaces total volatility with downside deviation in the denominator:
Sortino = (R - Rf) / σ_downside
Where σ_downside is the standard deviation computed only over returns below some target (typically zero or the risk-free rate).
For a normally-distributed return series, downside deviation is roughly 70 percent of total volatility, so Sortino is roughly 1.4 times Sharpe. For strategies with positive skew (trend-following, momentum, options long-volatility), downside deviation is much smaller than total volatility, and Sortino is significantly higher than Sharpe. For strategies with negative skew (mean-reverting, options short-volatility, martingale), downside deviation can exceed normal-distribution expectations, and Sortino is close to or below Sharpe.
The Sortino ratio is the more honest metric for asymmetric strategies (most retail trading systems, all crypto strategies, all options-based strategies). The Sharpe will systematically understate the risk-adjusted quality of a positive-skew strategy; the Sortino captures it correctly.
Calmar ratio
The Calmar ratio, introduced by Terry Young in 1991 (named after his California Managed Account Reports newsletter), takes a different approach: instead of using volatility (which is a statistical abstraction), it uses maximum drawdown (the worst peak-to-trough decline in the equity curve over the period). Computed as:
Calmar = R_annualised / |MaxDD|
Where R_annualised is the compound annual return and |MaxDD| is the absolute value of maximum drawdown over the same period (expressed as a positive percentage).
Interpretation: Calmar tells you how many years of compound return it takes (on average) to recover from the worst drawdown the strategy has historically experienced. A Calmar of 1.0 means one full year. A Calmar of 3.0 means roughly 4 months. The metric captures the client-experience dimension that pure-volatility metrics miss: investors do not fire managers because of standard deviation; they fire managers because the equity curve drew down and stayed down.
Calmar is the favourite metric of managed futures and trend-following CTAs because their return profiles are characterised by long periods of small grinding gains punctuated by short violent drawdowns. The Sharpe ratio of a quality CTA can look mediocre; the Calmar ratio can be very strong. Allocators in that space know to weight Calmar heavily.
Which ratio should I use?
Use all three. They capture different dimensions of risk and the combination tells you what the individual metrics cannot:
- High Sharpe + high Sortino + high Calmar. Genuinely strong strategy. Low total volatility, positive skew, manageable drawdowns. This is the institutional-grade profile.
- High Sharpe + high Sortino + low Calmar. Suspicious. The volatility numbers look good but the worst drawdown is disproportionate. Often a sign of hidden tail risk (a strategy that looked great until one fat-tail event ate years of returns).
- Low Sharpe + high Sortino + high Calmar. Classic positive-skew strategy (trend-following, crisis-alpha). Total volatility is high because of large positive moves; downside is contained. Allocators in trend-following space know to weight Sortino + Calmar over Sharpe here.
- High Sharpe + low Sortino + low Calmar. Negative-skew strategy. Total volatility looks normal because losses are infrequent, but when they come they are large and slow to recover. Often options-selling, mean-reversion, or yield-chasing in disguise.
- Low across all three. The strategy is not producing risk-adjusted edge. Either the alpha is illusory or fees and frictions are eating it.
Institutional benchmarks (reference)
| Benchmark | Typical Sharpe | Typical Sortino | Typical Calmar |
|---|---|---|---|
| AU balanced super fund (10y) | 0.5 - 0.8 | 0.7 - 1.1 | 0.4 - 0.7 |
| S&P 500 (long-term) | 0.4 - 0.6 | 0.6 - 0.9 | 0.3 - 0.5 |
| 60/40 portfolio (long-term) | 0.5 - 0.8 | 0.7 - 1.1 | 0.5 - 0.8 |
| Median hedge fund | 0.6 - 1.0 | 0.9 - 1.4 | 0.5 - 0.9 |
| Top-decile hedge fund | 1.5 - 2.5 | 2.0 - 3.5 | 1.5 - 3.0 |
| Top trend-following CTA | 0.8 - 1.4 | 1.5 - 2.5 | 1.0 - 2.0 |
| Top market-neutral hedge fund | 2.0 - 4.0 | 2.5 - 5.0 | 3.0 - 6.0 |
| Bitcoin buy-and-hold (10y) | 0.7 - 1.0 | 0.9 - 1.3 | 0.2 - 0.4 |
| Typical retail trader | -0.5 to 0.3 | -0.5 to 0.4 | 0.1 - 0.4 |
Two observations from the benchmark table:
- Bitcoin's Sharpe is competitive with hedge funds, but its Calmar is poor. The 80 percent peak-to-trough drawdowns in 2015, 2018, and 2022 destroy the Calmar even though the multi-year return is strong. Allocators who weight Calmar (which is most institutional allocators) penalise Bitcoin heavily for this. Allocators who weight Sharpe more heavily allocate to Bitcoin readily.
- Sharpe ratios above 4 are virtually never sustained over 10+ year track records. If you see one, it is either a short window, hidden leverage, illiquid assets that under-report volatility, or measurement error. Persistent 4+ Sharpes belong to a tiny set of strategies (high-frequency market-making, statistical arbitrage at very short horizons) that retail traders cannot replicate.
Related tools
- Risk of Ruin Calculator - probability of blowing up given edge and risk per trade. Pair with Sharpe to assess survival under any given Sharpe.
- Kelly Criterion Position Sizer - optimal bet size for long-run log-equity growth. The Sharpe ratio is the input that determines whether Kelly even produces a positive bet size.
- Expectancy + Profit Factor Calculator - per-trade edge math feeding the Sharpe numerator.
- Drawdown Recovery Calculator - the non-linear math behind why Calmar matters.
- Prop Firm EV Projector - Monte Carlo across FTMO, FundedNext, The 5%ers, FunderPro, Funding Pips with edge inputs that feed the Sharpe formula.
Frequently asked questions
The Sharpe ratio is the most common risk-adjusted return metric. It is computed as (annualised return minus risk-free rate) divided by annualised standard deviation of returns. The numerator is excess return over a risk-free benchmark (typically a short-term government bond yield). The denominator is total volatility, capturing both upside and downside swings. Higher is better. A Sharpe of 1.0 is generally considered the threshold of an acceptable institutional strategy; 2.0 is exceptional; under 0.5 is weak. The metric was introduced by William Sharpe in 1966 and remains the default for any hedge fund pitch deck or fund tearsheet.
The Sortino ratio improves on the Sharpe by replacing total volatility with downside deviation in the denominator. Downside deviation is the standard deviation of only the negative returns (or returns below a target threshold). The intuition: upside volatility is not risk; only downside volatility is risk. A strategy with high upside variance and low downside variance has a high Sortino but a moderate Sharpe. Higher is better. A Sortino of 1.5 is the rough threshold of an acceptable institutional strategy; 2.5 is exceptional. Use Sortino when the return distribution is asymmetric (most retail trading strategies, options strategies, momentum strategies, and most crypto strategies).
The Calmar ratio is computed as annualised return divided by the absolute value of maximum drawdown (peak-to-trough decline) over the same period. Higher is better. A Calmar of 1.0 means your annual return equals your worst drawdown (taking 12 months of good performance to recover from the worst loss). A Calmar of 3.0 is exceptional (recovering from the worst drawdown in 4 months on average). The metric is favoured by trend-following CTAs and managed futures funds because drawdown duration is the dominant client-experience variable in those strategies. The name comes from California Managed Account Reports (Terry Young's 1991 newsletter), where the metric was first popularised.
Use all three. Each captures a different dimension of risk. Sharpe is the standard for symmetric return distributions and broad comparisons (it is what your investors will see first). Sortino is better for asymmetric distributions where upside variance should not be penalised. Calmar is the honest metric for the client experience because drawdown duration and depth is what makes clients fire managers. A genuinely good strategy scores well on all three. A strategy that scores well on Sharpe but poorly on Calmar has a hidden tail-risk problem. A strategy that scores well on Calmar but poorly on Sharpe and Sortino has a low-variance grinding return profile that may not deliver enough absolute return to justify allocation.
Industry benchmarks: 1.0 is the threshold of professional acceptability; 1.5 is solid; 2.0 is exceptional; 3.0 is the rare territory of top-decile market-neutral hedge funds or very high-frequency strategies. Sharpe ratios above 4.0 are vanishingly rare over multi-year track records and frequently turn out to be measurement artifacts (short windows, hidden leverage, illiquid assets that under-report volatility). Most retail strategies finish below 0.5 because spread, commissions, and slippage destroy most of the raw edge. The Australian Superannuation industry's typical balanced fund runs a Sharpe of roughly 0.5 to 0.8 over rolling 10-year windows; an industry super fund Sharpe above 1.0 is unusually strong.
The Sharpe and Sortino ratios are excess return metrics: the numerator is return above what you could earn risk-free. The default risk-free rate is set to a reasonable Australian-resident proxy (the 10-year government bond yield). If you ran the calculation with risk-free equal to zero, you would overstate the risk-adjusted return because you would not be penalising the strategy for the opportunity cost of not just holding government bonds. Set the risk-free rate to match your preferred benchmark: 30-day BBSW for short-horizon strategies, 10-year ACGB for long-horizon strategies, or the AUD-hedged S&P 500 return if you want to compare against equity passive.
Total volatility (the denominator of Sharpe) is the standard deviation of all returns (positive and negative). Downside deviation (the denominator of Sortino) is the standard deviation of only the returns below some target (typically zero or the risk-free rate). For a normally-distributed return series, downside deviation is roughly 0.7 times total volatility (the calculator uses this as a fallback when you do not supply downside deviation directly). For strategies with positive skew (cut losses short, let winners run), downside deviation is smaller than that, and Sortino exceeds Sharpe meaningfully. For strategies with negative skew (martingale, sell-options-pick-up-pennies), downside deviation is larger, and Sortino is closer to Sharpe.
Maximum drawdown is the largest percentage decline from a peak to a subsequent trough in your equity curve, expressed as a positive number. If your account peaked at $100,000 and then fell to $72,000 before recovering, the maximum drawdown is 28 percent. You supply this number directly. To compute it from a return series, track the running maximum (peak) at every point and the percentage decline from that peak; the maximum drawdown is the largest such decline observed across the full series. Most retail platforms (MetaTrader, TradingView strategy backtests, prop firm dashboards) report this metric directly.
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