Calculator
Sharpe vs Sortino Calculator
Paste daily returns; get Sharpe, Sortino, Calmar, and Omega side-by-side with a recommendation on which ratio fits your distribution.
- Inputs
- Form inputs / CSV
- Runtime
- Instant
- Privacy
- Client-side · no upload
- API key
- Not required
- Methodology
- Open →
Inputs
Sortino (annualized)
-0.83
μ_ann -12.7% · downside dev 15.2% · 504 obs.
Risk-adjusted return ratios
Sharpe
-0.61
μ / σ
Sortino
-0.83
μ / downside-σ
Calmar
-0.40
μ_ann / max DD
Omega
0.91
upside / downside ratio
Opinion
Use Sortino. Returns are positively skewed or asymmetrically distributed — penalizing total volatility (Sharpe) under-rewards a strategy whose volatility is mostly upside.
Max drawdown: 31.6% · Total volatility: 20.8%
What each ratio measures
- Sharpe — excess return per unit of total volatility.
- Sortino — excess return per unit of downside-only volatility.
- Calmar — annualized return per unit of max drawdown.
- Omega — gains-vs-losses ratio at the threshold (no normality assumption).
See methodology for formulas + references.
How to use
Step-by-step
- 1
Upload your return series.
- 2
Set target return for Sortino (default 0%; risk-free rate is another common choice).
- 3
Set the period frequency (daily/weekly/monthly) so annualization is correct.
- 4
Read Sharpe and Sortino side-by-side. The ratio between them tells you about return skew.
- 5
Compare against your strategy peer group. Long-only equity Sharpe typically 0.3-0.7; market-neutral 1.0-1.5; HF-style 1.5+.
Glossary references
Terms used by this tool
Questions people ask next
FAQ
When should I use Sharpe vs. Sortino?
Sharpe penalizes both upside and downside volatility — appropriate when you treat all volatility as risk. Sortino penalizes only downside (returns below a target threshold) — appropriate when upside volatility is desirable, like in long-volatility or trend-following strategies. The tool reports both side by side so you can see how they diverge.
What target return should I use for Sortino?
Common choices: 0% (penalize any negative return), risk-free rate (penalize sub-Treasury returns), or a strategy-specific MAR (minimum acceptable return). The tool defaults to 0% and lets you override. The methodology page documents how the choice changes interpretation.
Can Sortino be much higher than Sharpe?
Yes — for strategies with heavy positive skew. A trend-following CTA with most returns clustered near zero and occasional large wins might have Sharpe 0.5 and Sortino 1.2. The 2× ratio is real and informative; it says 'this strategy makes money in lumps, not smoothly'.
How is annualization handled?
Multiply Sharpe (and Sortino) by √(periods per year). For monthly data, ×√12. For daily, ×√252. The tool detects period frequency from input timestamps; you can override. The methodology page warns about the i.i.d. assumption underlying √-time scaling — it overstates ratios for serially correlated returns.
What's a 'good' Sharpe ratio?
Context-dependent: long-only equity Sharpes are 0.3-0.7 over decades; market-neutral hedge funds target 1.0-1.5; high-frequency strategies can sustain 3-5+ but capacity is constrained. Above 5 sustained over 5+ years is institutional-grade. Anything above 8 should make you skeptical of the data, not impressed.
Related deep dive
All articles →Read further
Long-form context behind the tool output.
- Methodology · Opinion·8 min
The Sharpe Ratio Trap
Sharpe ignores tail risk, assumes Gaussian returns, and is trivially gameable. Four metrics to report alongside it: Sortino, Calmar, tail, deflated Sharpe.
Read - Pillar · Guide·11 min
Deflated Sharpe Ratio
Bailey-López de Prado (2014) deflated Sharpe ratio, derived from extreme-value statistics, with a Monte Carlo confirmation and the full deflation table.
Read - Tutorial · Runnable·12 min
Did You Overfit? PBO and Deflated Sharpe
A practical tutorial on the two best-documented tests for backtest overfitting — PBO via CSCV and the Deflated Sharpe Ratio. Runnable Python + tool.
Read
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