Direct answer
Strategy Review is a structured review of a forex trading approach that checks whether its rules and assumptions match what happened in practice. It is used to learn from completed trades or past periods, improve the quality of the process, and identify which parts of the approach are robust versus which depend heavily on changing conditions.
Strategy Review differs from performance “judgment” in that it tries to be systematic: it looks at the plan first, then compares expected behavior to observed behavior, and it makes the review criteria explicit.
Mechanism or definition
A common Strategy Review starts with a few stable inputs:
- The strategy’s stated logic (for example: entry conditions, invalidation/exit rule, and position sizing method).
- The assumptions behind that logic (for example: expected movement size, typical trading frequency, or how transaction costs will affect results).
- The review window (a defined set of trades or time periods).
Then the review measures outcomes in two layers:
- Outcome layer: what happened financially and operationally (wins/losses, drawdown magnitude, and how costs affected results).
- Process layer: whether the strategy was followed as written and executed consistently (rule adherence, order handling, and whether decisions deviated from the plan).
A key part is separating relatively stable mechanics from variable conditions. For example, the strategy’s rule-set may be stable, but actual results can shift due to spreads, commissions, slippage, liquidity, platform execution differences, and broader market regime changes. Strategy Review explicitly treats these as changing factors, rather than assuming the same behavior will repeat automatically.
For comparison, “backtesting” is mainly about simulating outcomes from historical data under a model. Strategy Review is wider: it can include backtest evaluation, but it also focuses on what happened when execution, costs, and real-world decision-making were present.
Evidence or example
Suppose a strategy’s plan assumes that a certain type of move occurs often enough to justify the risk per trade. In a Strategy Review, you would check:
- Did those move conditions actually appear in the selected period?
- When they appeared, did the entry/exit logic trigger as intended?
- Were costs (spread and commissions) and execution effects material compared with the expected edge?
- Did the strategy’s risk sizing method remain consistent, especially during fast market changes?
A worked-example mindset often helps: you can map each trade to (a) what the plan predicted in rule terms, (b) what the market actually did, and (c) where execution or decision deviations occurred. The goal is not to “find a reason” after the fact, but to validate which assumptions held.
Limitations and risks
Strategy Review has important limitations:
- No real-time certainty: The review describes what happened in a chosen window, not what will happen next.
- Historical relationships do not guarantee future outcomes: Even if a strategy behaved consistently before, market structure and participant behavior can change.
- Variable conditions can dominate: If the review omits or underestimates transaction costs, or if execution quality differed across periods, conclusions can become misleading.
Common failure modes include:
- Confirmation bias: focusing only on trades that support the desired narrative.
- Changing assumptions mid-review: adjusting the strategy logic or thresholds based on results rather than evaluating the original plan.
- Overfitting to a small sample: concluding an “edge” exists when it may be a coincidence within a limited dataset.
Because these risks are real, a Strategy Review should treat conclusions as hypotheses to test, not as proof of future performance.
Verification or next question
To independently verify a Strategy Review, you can check whether the review clearly states:
- what rules were evaluated,
- what assumptions were used,
- what data range was reviewed,
- what costs and execution factors were included or excluded,
- and what failure modes were considered.
A useful next question is: Which parts of the strategy are rule-driven and stable, and which parts rely on conditions that can realistically change? If you can answer that, the review becomes more actionable while still staying informational rather than predictive.