By Keel Research Team · Updated May 12, 2026
Compute Sharpe and Sortino side-by-side from any returns series. Sharpe punishes all volatility; Sortino only punishes downside vol. The ratio between the two tells you whether your strategy has asymmetric upside — and which metric to lead with.
Per-period returns. Decimal (0.015) or with % (1.5%) — both work.
Annualized. Default 4% (~current T-bill yield).
Sortino's downside threshold. Usually 0.
> 1.0 means upside vol dominates downside vol (asymmetric positive).
Both Sharpe and Sortino take the same shape:
ratio = (mean_return − risk_free_rate) / risk_measureWhere they differ is in risk_measure. Sharpe uses standard deviation of all returns. Sortino uses downside deviation — the standard deviation of only those returns that fell below a minimum-acceptable-return threshold (typically zero).
sharpe_risk = stddev(returns)
sortino_risk = sqrt(mean of (r − MAR)² where r < MAR)Both ratios get annualized by multiplying by sqrt(N), where N is periods per year. Daily returns scale by sqrt(252); monthly by sqrt(12).
The practical implication: if your strategy has positive skew (fat winning trades, manageable losers), Sortino will be substantially larger than Sharpe. That ratio between them is a useful signal — Sortino/Sharpe > 1.3 says the upside meaningfully dominates the downside in risk-adjusted terms.
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Both measure risk-adjusted return as (excess return / risk). They differ in how they measure risk. Sharpe uses standard deviation — punishes all volatility, upside and downside equally. Sortino uses downside deviation — only counts returns below a target (usually zero). For asymmetric strategies that have big winners and small losers, Sortino is more forgiving and arguably more honest about real risk.
When the strategy has positive skew — fat upside tails, smaller downside. Trend-following, breakout, and many momentum strategies fit this; their best months are several times bigger than typical losses. Sharpe penalizes those upside months as "risk"; Sortino doesn't. For strategies with symmetric P&L (carry trades, market-making, mean-reversion at scale), Sharpe and Sortino are similar.
Rough guidance for trading strategies. <1: probably not worth the complexity over buy-and-hold. 1–2: real edge, but path-dependent. 2–3: institutional-grade. >3: usually too good to be true on a long sample — check for survivorship bias or look-ahead bias.
We multiply by sqrt(N) where N is periods-per-year. Daily returns → sqrt(252). Weekly → sqrt(52). Monthly → sqrt(12). This is the standard scaling assuming returns are roughly iid; for highly autocorrelated returns (e.g. monthly hedge-fund-of-funds), the scaling overstates risk-adjusted return. The calculator surfaces both ratios; pick periodicity to match your input sample.
It means upside volatility dominates downside volatility — your strategy has positive skew. Look at the Sortino / Sharpe ratio (shown on the result card). > 1.3 is meaningful asymmetry; > 2 is rare and worth investigating. Could be real edge (a trend strategy in a strong regime) or sample-size artifact (you got lucky on a few months).
Worst peak-to-trough loss — the path-dependent risk that ratios alone can't capture.
Optimal bet size given win rate and win/loss ratio. Pairs with risk-adjusted return analysis.
Live Keel backtest with Sharpe 2.17 over 20 months — see the ratios in context on a real strategy.