What is Strategy Review?
Strategy review is a structured look at how a trading plan behaved in practice and what that means for future decision-making. It usually focuses on process and rules (for example, entry/exit logic, position sizing rules, and risk controls), then connects those rules to observed outcomes. The key idea is to distinguish what you can learn reliably—such as whether your rule set was applied consistently—from what varies over time, such as market regime and execution quality.
Common mistakes people make during Strategy Review
1) Treating past performance as a forecast
A frequent misunderstanding is to assume that because a rule set worked historically, it will keep working in the same way. Relationships between signals and outcomes can shift when volatility, liquidity, spreads, or order execution change. A neutral check is to ask: “Did the strategy’s performance change when conditions changed, or did it stay stable?” If the answer is unclear, the review is incomplete.
2) Mixing stable mechanics with variable conditions
Strategy review goes wrong when the mechanics of the plan are compared against outcomes without separating variables. For example, you may attribute gains to your selection rules, while the real driver could have been execution during low-cost periods or unusually favorable market movement. A clearer approach is to separate (a) rule behavior you can document from (b) costs and conditions you cannot fully control.
3) Ignoring fees, slippage, and spread assumptions
Another common error is to compute returns using idealized prices or ignoring trading frictions. Even if you use historical trades, costs and execution timing can materially affect results. The neutral check is to state assumptions explicitly: which price source was used, how spreads were treated, and whether slippage was modeled or excluded. Without stated assumptions, any conclusion is hard to verify.
4) Using inconsistent or biased data selections
People often review “the good subset” while excluding messy periods, or they change the dataset after seeing results. That can inflate perceived effectiveness. A neutral check is to define the review window, include all trades that meet pre-set criteria, and ensure that results are reproducible from the same data definitions.
5) Focusing only on outcomes, not rule application
Outcomes are not the same as process. A strategy can show strong results while the rules were not consistently followed, or it can show weak results while the rules were applied correctly and the market simply did not match the plan’s assumptions. A material limitation is that you may not know whether the rule set caused the outcome or whether the outcome occurred despite correct or incorrect execution.
Limitations and risks to keep in mind
A strategy review can explain what happened, but it cannot guarantee future performance. Outcomes vary with market conditions, execution quality, and costs. Historical relationships do not establish future results, and incomplete assumptions (for example, about spread or slippage) can lead to overconfident conclusions.
To reduce these risks, build a “clear-if-then” mindset: if you change a specific input—like fees, execution timing, or the review window—does your interpretation remain reasonable? If the conclusion flips easily, it is a sign that the review needs stronger controls and clearer definitions.
Verification checks and what to ask next
A useful control-checklist approach is to verify four items in the review: (1) rule consistency (were rules applied as defined?), (2) stated assumptions (what exact prices/costs were used?), (3) variable separation (what changed besides the rules?), and (4) failure modes (under what conditions did the approach struggle?).
If any of these are missing, treat the review as incomplete rather than decisive. For deeper improvement, consider aligning your review method with a worked example so you can see how assumptions, data definitions, and limitations are handled in a fully checkable way.