What Is the Sharpe Ratio? Formula, Limits and Real Data

The Sharpe ratio is average return divided by the standard deviation of those returns: how much return an account produced per unit of volatility. Two accounts that finish a year at the same gain can carry very different Sharpe ratios, and the higher one got there on a smoother path.

How it works

The textbook definition uses periodic returns and subtracts a risk-free rate:

Sharpe Ratio = (Mean return − Risk-free rate) / Standard deviation of returns

ShowMyTrades computes it on closed trades rather than on calendar periods, and does not subtract a risk-free rate:

Sharpe Ratio = Mean per-trade result / Standard deviation of per-trade results

Each trade enters the series as profit + commission + swap, so the inputs are already net of costs. Only closed buy and sell trades count: deposits, withdrawals and balance operations are filtered out before the series is built. The denominator is the population standard deviation of that same series — squared distances divided by the number of trades, not by that number minus one — which is why standard deviation sits immediately above the ratio in our statistics table: it is literally the divisor. An account with fewer than two closed trades reads 0.00.

Measuring per trade rather than per month means the figure is not annualised, so the usual conventions do not transfer. "Above 1.0 is good, above 2.0 is excellent" describes an annualised Sharpe on periodic returns. On a per-trade series, 1.00 would mean the average trade is worth a full standard deviation of trade outcomes — almost no account with a meaningful trade count reaches it.

Why it matters

Gain alone says where an account ended. Sharpe says something about how it travelled. A strategy with a small, dependable edge repeated often will show a modest but positive ratio; a strategy carried by two lucky trades will show a large mean sitting on an even larger dispersion, and the ratio collapses.

It is also the honest counter to a chart that merely looks smooth, built from the same closed trades that produce profit factor.

What it cannot do is distinguish good volatility from bad. A trade that overshoots to the upside raises the denominator exactly as much as one that overshoots to the downside. That objection is the reason the Sortino ratio exists.

What the data shows

The figures below describe accounts published on ShowMyTrades, not traders in general. Across the published accounts that have trading history (August 2026), the median Sharpe ratio is 0.05, on a median of 171 closed trades and a median trade length of 2.4 hours.

Read through our own formula, 0.05 says something concrete: on the median account the average trade is worth about one twentieth of a standard deviation of trade results. Roughly twenty parts noise to one part signal. That is not a failing set of accounts — the median time-weighted return is +3.2% and 63.0% of them are positive over time. It is what a real edge looks like at the level of a single trade.

It also explains why short samples prove nothing. At that signal-to-noise ratio, a run of twenty green trades is an ordinary outcome for an account with no edge at all, and a week of red says nothing about an account that has one.

Where you see it on ShowMyTrades

Sharpe Ratio is the exact label, in the Advanced Statistics module of the account page, inside the Performance Metrics column and carrying a tooltip. It sits directly under Standard Deviation — its own denominator — and beside Profit Factor, Z-Score (Probability), Expectancy, AHPR and GHPR. It is calculated on our servers from the stored closed trades, printed to two decimals, and coloured green from 1.00 up, yellow from 0 to 1, red below zero. The module is shown by default on published account pages, though the owner can hide it, and it is not part of the embeddable widgets.

One warning about our own page: the tooltip on that label still quotes the conventional bands, above 1.0 good and above 2.0 excellent. Those bands belong to an annualised Sharpe on periodic returns, not to the per-trade figure printed beside them.

The same module offers Table, Weekday, Hourly and Duration views, and Custom Analysis recomputes the whole block on a filtered subset — Date Range, Symbols, Magic Numbers, Trade Type, Trading Hours, Lot Size and more. Recomputing Sharpe without an account's best symbol shows whether the ratio describes a system or an episode.

Common misunderstandings

• "Above 1.0 is good." True of an annualised Sharpe on periodic returns. Ours is per trade, so the threshold does not apply.
• "Sharpe measures risk." It measures dispersion of closed trade results. It knows nothing about how deep the account fell — that is drawdown, reported separately.
• "A high Sharpe means a safe account." Grid and averaging systems post tight, uniform closed trades precisely because they refuse to realise losers. Floating losses never enter the series.
• "I can compare my Sharpe with any account." Only at comparable trade frequency and holding period: a scalper closing 200 trades a month and a swing trader closing 8 are measured in different units.

For how Sharpe reads next to every other number on an account page, see the guide to reading a trading account dashboard.

Related terms