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Sharpe ratio: the ruler of trading efficiency
Two strategies both return 20%. One climbs steadily; the other swings wildly and lands at 20% by luck. Sharpe is the ruler that tells them apart: return divided by risk. Higher = smoother profits.
- Formula: (strategy return − risk-free rate) ÷ return volatility — plain: how much reward per unit of risk
- 1.0: decent — where most trend strategies sit
- 1.5–2.0: strong — respectable at institutional level
- 2.0+: elite — usually high-frequency or special regimes
- Warning: Sharpe from a short sample is meaningless — you need hundreds of trades
How to read the Sharpe ratio
Sharpe divides what you earned above the risk-free rate by how much the returns bounced around. A 1.0 means you earned one unit of reward per unit of risk — acceptable for most trend strategies. A 1.5-2.0 is strong enough to be institutionally respectable. Above 2.0, ask hard questions: it usually signals high-frequency trading, a special regime, or a calculation problem.
The ratio is only meaningful with enough trades. A Sharpe from a few dozen trades or a short window is noise with a number attached — demand hundreds of observations before believing any value.
Why a high Sharpe can still be fake
- Short sample: 30 trades and a 2.5 Sharpe is lottery luck, not edge.
- In-sample only: the Sharpe was computed on the data the strategy was optimized on.
- Lucky trades: two or three outsized winners can carry a weak strategy to an inflated ratio.
- No costs: Sharpe computed on gross returns ignores spreads and swaps that eat the edge.
- Multi-trial selection: if you tried 500 variants and show the best, its Sharpe is inflated — the deflated Sharpe ratio corrects exactly this.
Sharpe alone is not enough
Always read Sharpe together with three numbers: maximum drawdown (how bad it gets), trade count (how much evidence exists), and profit factor (how the wins and losses stack). A 1.5 Sharpe with a 30% drawdown and 40 trades is a very different risk profile from a 1.5 Sharpe with a 6% drawdown and 800 trades.
On EasyQuant, every strategy card pairs Sharpe with drawdown, trade count, walk-forward results and DSR/PBO verdicts — the context that makes the ratio trustworthy.
What is a realistic Sharpe for retail strategies?
For realistic, cost-inclusive, out-of-sample retail strategies, 0.5-1.0 is genuinely solid and 1.0-1.5 is strong. Anyone showing you 2.5+ on a retail backtest is either trading very special conditions or showing you a curve that will not survive live. Price in costs, validate out-of-sample, and let the ratio fall where it honestly lands.
FAQ
- Is higher Sharpe always better?
- Generally yes, but beware: tiny sample sizes, out-of-sample collapse, or returns driven by a few lucky trades can inflate it. Always read Sharpe together with drawdown and trade count.
- Is a 0.5 Sharpe usable?
- Yes, with realistic expectations: expect deep drawdowns and size positions accordingly. Many institutional trend strategies live between 0.5 and 1.0.
- Why is my strategy Sharpe negative?
- Negative Sharpe means you took risk and earned less than the risk-free rate. Before tuning parameters, check: look-ahead bias in data, missing costs, or overfitting.
- What is a good Sharpe ratio for a trading strategy?
- 1.0 is decent, 1.5-2.0 is strong, above 2.0 demands scrutiny. But sample size, costs and out-of-sample validation matter more than the number itself.
- What is the deflated Sharpe ratio?
- A version of Sharpe corrected for how many trials you ran, the track record length and non-normal returns. It answers: is this Sharpe real after pricing in selection bias?
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