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    Backtest-Validator

    by Ifásola

    Stop trusting overfit backtests. One honest verdict: PASS / FAIL / INCONCLUSIVE.

    Updated Jun 2026
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    $5

    · or 25 credits

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    Included in download

    • Identify if a strategy's performance is statistically indistinguishable from luck.
    • Calculate the maximum trade cost a strategy can handle before becoming unprofitable.
    • Ready for Cursor
    • Instant install

    Sample input

    Analyze the trade logs in strategy_v4_backtest.csv. I tested about 12 different parameter sets before picking this one, and my broker charges 1.5 bps per round-trip.

    Sample output

    Backtest Verdict: FAIL

    • Reason: Failed Multiple-Testing Correction (Sidak).
    • Edge Probability: 62% (below 95% threshold).
    • Break-even Cost: 0.8 bps.
    • Analysis: Your real cost (1.5 bps) exceeds the break-even. The 'best' variant you found is likely a result of luck among 12 trials.

    About This Skill

    Validates whether a trading strategy has a real, tradeable edge by running the four checks most backtests skip: sample-size/power, realistic costs with break-even, luck (10k bootstrap), and multiple-testing (Sidak + PSR). Feed it a trades CSV; get a verdict plus the break-even cost, the level where the edge dies. For traders tired of strategies that look great and lose live.

    Use Cases

    • Identify if a strategy's performance is statistically indistinguishable from luck.
    • Calculate the maximum trade cost a strategy can handle before becoming unprofitable.
    • Correct for cherry-picking bias when multiple strategy variants were tested.
    • Determine if a trade log has a sufficient sample size for reliable deployment.

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    Permissions

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    Requires Python 3.8+ with numpy and pandas. Works with any SKILL.md-compatible agent (Claude Code, Cursor, Gemini CLI).

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