Stock Backtesting: A Data-First Guide
A rigorous workflow from research question to point-in-time data, execution assumptions, validation, and saved evidence.
Stock backtesting applies historical decision rules to the information and tradable prices that would have been available at each simulated time. A valid test needs a point-in-time universe, explicit price adjustments, event known-at times, realistic fills and costs, complete coverage, parameter discipline, and an untouched out-of-sample period.
Freeze the information set
Define the decision time and admit only data known by that cutoff. Later SEC amendments, revised earnings schedules, restated fundamentals, and current index membership must not leak into earlier simulations.
Resolve securities through historical identities and retain delisted names. Otherwise the universe excludes many failures and overstates performance.
Model what could have traded
Choose the bar and fill rule before examining results. Same-close fills after an after-hours event are impossible; thin volume and wide spreads make theoretical prices unreliable.
Include commissions where relevant, spread, slippage, borrow and locate assumptions for shorts, trading halts, and portfolio constraints. Sensitivity tests should show whether the result survives modestly worse execution.
- Lag every signal to public availability.
- Use point-in-time membership.
- Reject incomplete lookbacks.
- Test costs and fill delays.
Validate instead of optimizing forever
Separate research, validation, and final holdout periods. Limit the number of variations, report all tested choices, and compare with simple baselines.
Save code version, parameters, data query, source runs, coverage snapshot, trades, and metrics. A promising curve without its evidence bundle is not a reproducible result.
How DataCedar preserves the evidence
DataCedar separates acquisition from serving. Permitted source responses are retained with retrieval time and identifiers, normalized into DataCedar-owned tables, checked against expected coverage, and exposed through a stable versioned API. A collector can be replaced without changing the customer contract or making an upstream provider a runtime dependency.
Every research stream carries effective and known-at time where the distinction matters. Rights-restricted, unavailable, partial, stale, and genuinely empty states remain visible, so a backtest can fail closed and a buyer can see the product boundary before committing engineering time.
Key takeaways
- 01Simulate only the information known at the time.
- 02Include delisted securities and realistic execution.
- 03Reserve an untouched holdout.
- 04Save the full evidence bundle.
Query public company evidence through one stable API. Free Explorer tier, no card.
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