Direct answer: what data to assess a risk reward target
To assess a risk reward target, you need four categories of data: (1) the definition and calculation method, (2) the inputs used for the method, (3) the provenance and timeliness of those inputs, and (4) quality checks that confirm assumptions and surface failure modes. If any category is missing, the assessment becomes hard to verify.
Mechanism and definition: separate stable mechanics from variable conditions
A risk reward target usually expresses a relationship between a planned “risk” distance and a planned “reward” distance. The most important data here is the precise measurement rule: what values represent risk and reward, and whether they are measured in points, pips, price distance, or monetary terms.
Stable mechanics (generally reusable across markets and providers) include:
- The formula you will use (for example, a ratio of reward to risk, or an expected payoff expression based on a chosen mapping).
- The unit convention (price distance versus account currency value).
- How you treat costs and execution details (either as included assumptions or as separate adjustments).
Variable conditions (data you must supply and re-check) include:
- The specific price references used for entry and for the stop and target reference levels.
- Any provider-specific contract details that affect conversions to account currency.
- The timing of when levels are set versus when execution occurs.
Because different tools and documents may define risk reward differently, the definition data is not optional: it determines what you must collect and what you can verify.
Evidence or example: an assessable checklist of inputs
Use an input checklist that you can reproduce without relying on live market feeds.
- Calculation definition (no numbers yet)
- Define “risk” and “reward” using the same measurement rule.
- State whether the target is expressed as a level, a distance, or a ratio.
- State your assumptions about direction and reference points (for example, which level is used as the baseline for distance).
- Trade-level inputs (the values you plug into the method)
- Entry price reference (the price level you assume for the position).
- Risk reference level (the stop reference level that determines “risk” distance).
- Reward reference level (the take-profit or target reference level that determines “reward” distance).
- Position size or a mapping rule from price distance to value (if you evaluate in monetary terms).
- Cost and execution assumptions (explicitly separated)
- Assumptions about spreads, commissions, or fees, if your calculation includes them.
- A note on whether execution is assumed to occur exactly at the stated reference prices or whether you treat deviation as a separate risk.
- Provenance and timeliness (where the numbers came from)
- Identify the source of each price reference you used (platform quote, user-provided level, or an archived value).
- Note the timestamp or at least the order in which values were obtained relative to each other.
- Record the instrument specification version (for example, contract size and any conversion rules), since these can vary by instrument and jurisdiction.
Limitations and risks: what can break the assessment
Even with complete data, a risk reward target assessment can fail for material reasons. At least one key limitation to consider is that planned levels often differ from execution outcomes.
Material limitations and failure modes to account for:
- Slippage and partial fills: actual execution may occur at prices different from the reference inputs.
- Cost mismatch: if fees or spread assumptions differ from reality, the computed risk/reward in value terms can change.
- Liquidity and market regime changes: the relationship between price movement and your reference distances may behave differently under stress.
- Inconsistent definitions: if you mix units (price distance versus value) or mix direction conventions, the result may be mathematically correct but not comparable.
Also, historical relationships between similar setups do not guarantee future results. Treat any back-tested or prior observation as context, not proof.
Verification and next question: how to independently check the facts
To verify your assessment, you should be able to reproduce the calculation from recorded inputs and confirm that every assumption is documented.
A practical verification approach:
- Recalculate the risk and reward components directly from your recorded entry/stop/target references. - Check unit consistency: confirm that the method uses the same units for risk and reward.