Direct answer: how risk reward limitations work in forex
Risk reward limitations in forex are not a guarantee of performance. They describe the constraints created when you translate an idea of “risk” and “reward” into numbers that depend on assumptions. In practice, those assumptions may not hold consistently because market movement, execution quality, and trading costs can change the realized loss and realized gain.
A clear way to understand the concept is: you start with a planned risk distance (how far price could move against you) and a planned reward distance (how far price could move in your favor). Then you map those distances to expected effects on the account using contract size and the instrument’s price units. Risk reward limitations appear when you evaluate how sensitive that mapping is to execution and cost details, and when you notice that a “good” risk-to-reward ratio does not remove the possibility of outcomes that do not match your plan.
Mechanism and definition: the building blocks
1) Define risk and reward as distances
In forex risk planning, “risk” is usually represented as a price distance from the entry level to a level where you would stop exiting (often called a stop level). “Reward” is represented as a price distance from the entry level to a target level where you would exit with profit.
Risk reward limitations start at this definition stage. If you define the distances, you are already assuming that:
- price reaches those levels in the order and in the form you expect;
- the execution occurs near the levels you modeled;
- the cost effects (spread and fees, if any) are accounted for in a stable way.
2) Convert price distance into account impact
To estimate account impact, traders commonly use a contract conversion approach:
- you choose a position size (how large the trade is);
- you translate the stop distance (in price terms) into a loss amount using that position size;
- you translate the target distance into a gain amount using the same position size.
This conversion relies on instrument-specific contract mechanics and on your broker’s quoting conventions. The key point for risk reward limitations is that the conversion is accurate only under the assumptions you used (for example, that the relevant price move corresponds closely to the modeled distance).
3) Compute a risk-to-reward ratio, then evaluate limitations
A risk-to-reward ratio compares the planned reward amount to the planned risk amount. Many people treat a higher ratio as “better.” Risk reward limitations explain why that reasoning can be incomplete:
- the ratio can look favorable even when total costs reduce both outcomes;
- execution effects can change the realized distances or the effective entry/exit prices;
- partial fills or non-ideal fills can alter the economics.
The limitation is therefore not the ratio itself. The limitation is the gap between the modeled distances/economics and the realized ones.
Evidence or example: scenario-impact with explicit assumptions
Consider a hypothetical setup used only to illustrate the sequence.
Assumptions (make these explicit):
- You plan an entry at a chosen price.
- You model a stop level at a fixed distance below entry (for a long position).
- You model a target level at a fixed distance above entry.
- You assume execution happens at your modeled levels.
- You ignore slippage for the moment, then reintroduce it.
Scenario A: idealized modeling
- Choose a position size.
- Compute estimated loss from the stop distance.
- Compute estimated gain from the target distance.
- Derive a risk-to-reward ratio from those estimates.
In this idealized case, risk reward limitations are minimal because the model’s assumptions match the realized execution.
Scenario B: add execution uncertainty (realistic divergence)
Now change only one aspect: assume the market reaches the target or stop, but your entry/exit prices are not exactly the modeled levels.
Possible effects:
- Slippage at exit: if your stop triggers but you exit at a worse price than the stop level, the realized loss becomes larger than the modeled loss.
- Slippage at entry: if you enter at a worse price than expected, both the effective stop distance and target distance can shift.
- Costs/spread impact: even if price hits your levels, spreads and any trading costs can reduce the net gain and can increase the net loss.
Material limitation: the risk-to-reward ratio computed from the planned distances may not reflect the ratio realized after execution and costs.
Scenario C: optimistic target vs. time and liquidity pressure
Keep execution uncertainty in mind, and assume the target is further away than the stop.
A common limitation or failure mode is:
- reward requires a longer or more specific path,
- while risk can be triggered quickly if price moves first against you.
Even when the reward distance is larger than the stop distance, the realized outcome distribution can still be dominated by execution and timing effects.
Limitations and risks: what can fail and how to verify
Material limitation: assumptions about level-reaching and execution
Risk reward limitations come from the assumption that the price move you modeled maps to the realized entry and exit economics. If your actual execution deviates, the account impact deviates.
Material failure mode: costs and effective spread are not constant
If you use a simplified calculation that treats spreads or costs as negligible or constant, you can overestimate the net reward and underestimate the net risk. This is especially relevant when you compute risk-to-reward using gross distances rather than net outcomes.
Material failure mode: changing conditions during order life
Markets can change in ways that affect how orders are filled before you reach the modeled levels. That can change both the effective risk and the effective reward.
What a reader can independently verify (no guarantees)
To verify the concept for themselves, a reader can:
- write down the exact assumptions used for converting price distances into account amounts;
- compare modeled net outcomes (after assumed costs) to what happens when execution deviates;
- test whether changing slippage and cost assumptions changes the risk-to-reward ratio materially.
A good verification question is: “If I adjust my assumed execution price and costs by plausible amounts, does my conclusion about risk-to-reward still hold?”