Direct answer: the percent is not a single fixed value
There is no universally agreed, independently verifiable “percentage of forex trades that go down” that applies to all traders, brokers, timeframes, and strategies. In practice, the observed share of closing trades that end up negative varies because “a trade” is defined differently (entry and exit rules), and the measurement depends on the chosen horizon (how long trades are held).
Within fixed percentage risk, the situation is even clearer: fixed percentage risk describes how position size is calculated relative to account risk. It does not, by itself, determine whether a trade closes up or down. So the sizing rule can be consistent while the down-percentage still changes due to strategy and market conditions.
Explanation: what “go down” can mean
To interpret “what percentage of forex trades go down,” you first need a precise, comparable definition. Common measurement choices include:
- Close outcome definition: Is “go down” based on net profit/loss after spread and fees, or based only on price movement?
- Time window: Are trades held for minutes, hours, or days? Shorter horizons often show different outcome shares than longer ones.
- Trade population: Are you measuring all executed trades, only completed trades, or trades filtered by a specific strategy rule?
- Execution and sampling: Trades measured from different brokers or different execution models may not be directly comparable.
Because these choices affect the denominator (what counts as a trade) and the numerator (how “down” is detected), any single percentage reported without those conditions is not a complete answer.
Mechanics (fixed percentage risk): what changes and what doesn’t
Fixed percentage risk typically means a trader risks a predetermined fraction of the account on each trade, using a stop distance to size the position. The key consequence is:
- The position size becomes proportional to the chosen risk fraction and the distance to the stop.
- The probability of a negative close is still driven by the market path and the entry/exit logic.
So within this framework, you can analyze money impact rules (how much loss is targeted if a stop level is reached), but you cannot derive a single, stable “percent of trades that go down” without also specifying the strategy and the evaluation setup.
Example checks and ways to verify your own percentage
If you want to know the “down-trade percentage” for a specific dataset, you can measure it directly from your chosen definitions:
- Pick a consistent trade definition (same entry rule, same exit rule, same holding rule).
- Choose a consistent outcome basis (net P/L including costs, or price-only).
- Use a complete sample window (for example, a fixed date range) and avoid mixing incompatible strategies.
- Count outcomes: down-trade percentage = (number of trades with net loss) / (total completed trades) × 100.
If you change only the exit timing (for example, tighter targets or different stop logic), you should expect the down-trade percentage to change, even while fixed percentage risk stays the same.
Limitations and uncertainty
- No single global percent: Without strict definitions and a specific trade population, the “percent that go down” cannot be pinned to one number.
- Costs and execution matter: Including spread, commissions, and slippage can convert some near-zero moves into net losses.
- Forward results are not guaranteed: Even if you compute a down-percentage historically, it does not guarantee the same percentage in future samples.
If someone states a precise percentage without explaining how trades are defined and measured, treat it as incomplete rather than universally true.