/4 CONNECTED STEPS
Audit historical experiments without hiding failed trials
Produce an experiment audit that preserves every trial and tests whether historical signals used only available information.
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What you need
Historical data with availability times, a repeatable experiment, run artifacts, trial ledger and a declared evaluation method.
Why these fit together
Temporal guards protect inputs; immutable runs preserve evidence; complete trial accounting exposes selection; the final audit checks cost and validation assumptions.
Follow this order
Prevent lookahead in historical backtests
Filter by information availability and historical version.
Preserve experiment runs and count every trial
Retain immutable runs and every attempted variant.
Count parameter trials that produced no trades
Include no-trade trials without inventing statistics.
Audit a backtest before reporting results
Review trades, costs, bias and out-of-sample evaluation.
Give this task to your AI
Use the Audit historical experiments without hiding failed trials workflow. My task and inputs are supplied below. Read the prerequisites and check your available tools. Follow the core steps in order, passing the actual output of each step to the next. Adapt installation and commands to this environment; do not copy another agent's configuration blindly. If a required tool or input is missing, identify it before that step. Run the completion check and report observed results and unresolved work.
Setup to provide or build
A fixed offline dataset, supported simulator, explicit cost/frequency assumptions, artifact layout and audit command.
Check the result
Future and revised observations do not affect past signals; a losing and a no-trade variant both remain in the ledger; missing costs or provenance block a decision-grade conclusion.
Curated implementation workflow. End-to-end execution must be verified in your environment.
Optional additions
Load these only when your task needs them.