Sizing Targets to Recent Range Instead of Fixed Pips
Posted: Tue Oct 27, 2026 11:18 pm
A fixed target of, say, five pips looks tidy, but market movement is not fixed. The same target that is realistic during an active hour may be far out of reach during a quiet one. A fixed number therefore implies a constantly changing probability of success.
Range-scaled targets attempt to correct this. The target is set as a fraction of a recent measure of movement, such as the average range over the last several candles of the trading timeframe. When the market is active the target widens; when it is quiet it tightens. Stops are scaled in the same proportion, so the reward-to-risk relationship stays consistent.
This approach has a cost-related benefit. In quiet conditions the scaled target may become so small that the spread consumes most of it. The method then reveals, objectively, that the setup is not worth taking, functioning as a built-in filter.
There are drawbacks. Volatility measures lag, so the target may be calibrated to conditions that have already changed. Choosing the lookback period also involves a trade-off between responsiveness and stability. Testing should compare fixed and scaled approaches over the same entries, using actual spread data, with attention to average result per trade and the number of trades that scaling removes.
Range-scaled targets attempt to correct this. The target is set as a fraction of a recent measure of movement, such as the average range over the last several candles of the trading timeframe. When the market is active the target widens; when it is quiet it tightens. Stops are scaled in the same proportion, so the reward-to-risk relationship stays consistent.
This approach has a cost-related benefit. In quiet conditions the scaled target may become so small that the spread consumes most of it. The method then reveals, objectively, that the setup is not worth taking, functioning as a built-in filter.
There are drawbacks. Volatility measures lag, so the target may be calibrated to conditions that have already changed. Choosing the lookback period also involves a trade-off between responsiveness and stability. Testing should compare fixed and scaled approaches over the same entries, using actual spread data, with attention to average result per trade and the number of trades that scaling removes.