Understanding yourtrading edge.
A profitable strategy does not produce profits in a predictable sequence. Losses cluster, streaks occur, and short periods can look very different from the long-run statistics. This page helps make that variance easier to understand — and easier to relate to your own trading.
The same edge can feel very different.
Imagine two traders taking the same 30 trades with the same 70% strike rate. Both finish with 21 wins and 9 losses. The order of those outcomes, however, can be completely different.
The final statistics can be identical while the experience of getting there is not.
A losing streak is not automatically evidence that your edge has disappeared.
When outcomes are uncertain, consecutive losses are a normal part of the distribution. The question is not whether a losing streak can happen, but how plausible different streak lengths are over the number of trades you actually take.
This distinction matters because a statistically ordinary period can feel extraordinary while you are living through it. Without context, a trader's confidence can fall during a statistically normal period, leading them to change strategy or alter execution in response to ordinary variance.
Use your own numbers.
Adjust the assumptions below. The purpose is not to predict your next sequence of trades, but to build a more realistic expectation of what normal variation can look like. Understanding that variation can help you maintain confidence in your process when results become difficult — and confidence is a trader’s most important commodity.
These figures describe probability, not certainty. A particular sequence can always be better or worse than the expected experience.
95% of comparable trade sequences are expected to remain at or below this maximum losing streak.
Experiencing a losing streak?
Use the current losing streak input below to see how unusual that streak actually is within your normal statistical distribution.
Probability of at least one losing streak of this length within the selected sample.
A four-trade losing streak may feel exceptional while it is happening, but it can still occur within normal variance.
What is an in-plan trade worth over time?
Strike rate tells you how often a trade wins. It does not tell you the value of the strategy by itself. Expectancy combines how often you win with the size of your average win and loss.
Think of expectancy as the long-run average return attached to each correctly executed, in-plan trade. It is not what the next trade will make. It is what each trade contributes on average when the same edge is repeated over a sufficiently large sample.
That means the individual trade is uncertain, but the repeated decision has a measurable long-run value.
The bronze boundary marks approximately zero expectancy. Move across the table to compare how strike rate and average reward-to-risk interact.
What is each of your in-plan trades worth?
Use your own realised statistics. The result describes the average R contributed by each in-plan trade over time — not the outcome of the next trade.
Using these assumptions, each correctly executed in-plan trade contributes +0.40R on average over a sufficiently large sample.
Why this matters
A losing trade can still be a good trade. If it followed the plan, it is one observation within the distribution that produces your long-run expectancy. This is why individual outcomes and decision quality should not be treated as the same thing.
Edge does not remove drawdown risk.
Positive expectancy describes the long-run average of a strategy. It does not tell you how difficult the path between trades may be, or how much risk can be absorbed before a drawdown becomes unacceptable.
Adjust the assumptions below to explore how strike rate, average win, drawdown tolerance, sample size and theoretical risk per trade interact. The results update immediately as you change the inputs.
Risk / trade is modelled as a fixed percentage of starting equity. Each in-plan loss is −1R and each win uses the selected average-win R multiple. No dollar amounts are calculated or implied.
Long-run average R per in-plan trade.
Mean of the maximum losing run across all possible sequences under these assumptions.
Exact finite-sample probability under the stated model.
Understanding Drawdown Tolerance
Drawdown tolerance is the maximum decline from starting equity used as the threshold in this model. It is not a recommended figure. The calculation asks how often that threshold is reached within the selected number of trades when risk is fixed as a percentage of starting equity.
Plan for variance before youexperience it.
Statistics are most useful when they change expectations. If a losing streak is plausible within your normal distribution, encountering one should not automatically trigger a change in strategy.
That does not mean every loss should be ignored. It means strategy performance and execution quality need to be evaluated separately. A planned trade that loses is not the same problem as a trade taken outside the plan.
But nobody trades perfectly all the time.
Normal variance can change the behaviour of the person experiencing it.
A losing streak may begin with perfectly valid, in-plan trades. But frustration, uncertainty or attempts to recover losses can introduce a second source of risk: out-of-plan trading.
The next case study examines what happens when behaviour begins to deteriorate alongside ordinary trading variance — and how a risk-management plan can be designed with that possibility in mind.
Explore the Risk Management Case Study →