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Sharpe ratio explained: the most-cited measure of risk-adjusted return

The Sharpe ratio measures excess return per unit of volatility — finance's most-cited risk-adjusted return metric. What it measures, what counts as 'good,' and why a high Sharpe can be either signal or artifact.

The Sharpe ratio measures how much return a portfolio or strategy generates above the risk-free rate, per unit of volatility. It's the single most widely-cited risk-adjusted return metric in finance and the standard reporting unit for strategy performance across academic papers, hedge funds, and institutional reports.

Developed by William Sharpe in 1966 (originally as the “reward-to-variability ratio”), it gives a single number that lets you compare strategies with very different return profiles on a common basis. A strategy returning 8% with 4% volatility is generally preferable to one returning 12% with 16% volatility — even though the second has a higher absolute return.

What the formula actually says

Sharpe = (Strategy return − Risk-free rate) ÷ Strategy volatility

The numerator is excess return over what you could earn risk-free (typically the T-bill rate). The denominator is the standard deviation of the strategy's returns over the same window. Both are usually annualized.

A Sharpe of 1.0 means the strategy earns one percentage point of excess return for every percentage point of volatility — historically, that's roughly the long-run market average.

What counts as “good”

Where the Sharpe ratio fails

Sharpe is useful but blunt. Three weaknesses worth knowing:

How QScoring uses it

Sharpe ratio isn't a per-stock metric, so it doesn't enter the individual QScore directly. Where it matters is validation: the QScoring pledge commits to publishing a long-short quintile-spread Sharpe of at least 1.5 before subscription billing turns on. That bar is deliberately conservative — Sharpe 1.5 is solidly in “good” territory for a publicly-disclosed factor strategy and high enough that surviving look-ahead bias scrutiny is meaningful.

Until the formal backtest publishes, the live performance pagetracks every QScore we compute as it's captured — locked into public source control so the eventual Sharpe calculation is transparent and auditable.

Common mistakes

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