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Metrics· Glossary

What Is Standard Deviation in Trading? Formula and Data

Standard deviation measures how far a single trade lands from your average trade. Here is the formula we use, net of costs, and how to read it on thousands of accounts.

Standard deviation is the typical distance between a single trade's result and the account's average trade result. On ShowMyTrades it is reported in the account currency, so it answers a direct question: how much does one trade usually differ from the ordinary trade on this account? A small figure means results cluster; a large one means the history is made of outliers.

How it works

Standard Deviation = √( Σ (rᵢ − mean)² / n )

Where rᵢ is the net result of closed trade i, mean is the average of those results, and n is the number of closed trades. Four details decide what the number means:

  • Each trade enters net of costs. rᵢ is profit + commission + swap, so commission-heavy and swap-heavy trades widen the dispersion exactly as much as they narrow the profit.
  • Only closed buy and sell trades count. Deposits and withdrawals are filtered out before the series is built, so funding the account is not a giant outlier.
  • It is the population form, dividing by n rather than n − 1. With fewer than two closed trades the metric reads 0.00.
  • It is in currency, not percent. A $50 standard deviation on a $2,000 account and on a $200,000 account describe completely different behaviour. Always read it against the account balance.

Because distances are squared before averaging, one exceptional trade moves the figure far more than a dozen ordinary ones — which is what makes it catch the trade that does not belong.

Why it matters

Standard deviation is the honest test of the word "consistent": anyone can call an equity curve steady, and this puts a currency value on how steady the trades were.

It is also the denominator of our Sharpe ratio: Sharpe is the average trade expressed in units of this figure. And it is the natural companion to expectancy, which gives the average outcome per trade with no indication of how reliably that average is delivered.

The most useful reading is comparative, against the two averages sitting a few rows away:

  • Close to Avg. Win — results are tight. The account behaves the same way most of the time.
  • Several times Avg. Win — a handful of trades carries the history. Check Best Trade (P&L) and Worst Trade (P&L) before trusting the totals.
  • Much larger than Avg. Loss — at least one loss sits far outside the routine.

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.

Run our own definition backwards and that pairing is precise about dispersion: since Sharpe is the mean trade divided by this standard deviation, a median of 0.05 means the average trade on the middle account is worth roughly one twentieth of the standard deviation of its trades. Routine variation between one trade and the next is about twenty times larger than the edge extracted from them.

On a median trade length of 2.4 hours, that is why a full day of results teaches a trader nothing: a day sits well inside the dispersion. It is also why a low figure on a young account is not evidence of control — the sample may simply not contain the outlier the strategy can produce, and squared distances mean that when it arrives, it arrives loudly.

Where you see it on ShowMyTrades

Standard Deviation is the exact label, in the Advanced Statistics module of the account page, inside the Performance Metrics column, formatted in the account currency and carrying a tooltip. It sits directly above Sharpe Ratio, the ratio it divides, below Profit Factor, and is calculated on our servers from the stored closed trades. 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.

Read it across to the Trades column of the same module, where Avg. Win, Avg. Loss, Best Trade (P&L), Worst Trade (P&L) and Total Trades give the figure its context. The module's Duration view makes the dispersion visual: every closed trade is one point, holding time in hours across the bottom and profit or loss up the side, so the spread becomes a shape rather than a number. Custom Analysis recomputes the whole block on a filtered subset — Date Range, Symbols, Magic Numbers, Trade Type, Lot Size and more — which shows whether the dispersion belongs to the strategy or to one instrument.

Common misunderstandings

  • "It is a percentage." Ours is an amount of money per trade. Comparing it between accounts of different size is meaningless without the balance beside it.
  • "It measures market volatility." It measures the volatility of your results. A calm market traded with escalating size produces a large figure.
  • "Low standard deviation means low risk." Only closed trades enter it. Systems that hold losers open post uniformly small closed results while the real exposure sits in floating positions.
  • "A low figure on 30 trades is reassuring." Below a few hundred trades, treat it as provisional.

For how many trades a set of statistics needs before it means anything, see the guide on how much history a track record needs.