A Backtesting Checklist Before You Trust a Strategy
A practical validation checklist for deciding whether a backtest result reflects a real workflow or just a comforting narrative.
A Backtesting Checklist Before You Trust a Strategy
Start with the data, not the result
- is the market data complete for the chosen period
- is the timeframe consistent with the strategy logic
- are symbols mapped correctly
- is missing or noisy data handled in a known way
Make the execution model explicit
- how positions are opened
- how size is determined
- how exits happen
- how stop-loss or take-profit logic behaves
- how fees, slippage, and exchange constraints are represented
Before applying this
- OKClarify the strategy assumptions
- OKReview backtest results across different market conditions
- OKDefine risk limits and position sizing before deployment
Turn isolated test runs into a validation workflow
See how Whaleer supports strategy iteration with backtests, metrics, archives, and structured review.
Read the documentationFAQ
What makes a backtest unreliable?
Weak data quality, vague execution logic, unrealistic friction assumptions, and unreviewed failure periods can all make a backtest misleading.
How do you know if a strategy result is repeatable?
A result is more trustworthy when the rules are explicit, the assumptions are realistic, weak regimes were reviewed, and similar conclusions survive comparison or reruns.
Turn isolated test runs into a validation workflow
See how Whaleer supports strategy iteration with backtests, metrics, archives, and structured review.
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