SuperQuant feature tutorial · fixed teaching example
Backtesting engine
Test explicit rules against a frozen historical sample.
Before you begin: A run uses the selected Playbook and dataset. Save your own rules before editing.
How to use it
- Open Research Lab’s Workbench and Select Playbook.
- Inspect Data & coverage, signal rules, protection and costs.
- Deliberately run the backtest; inspect sample dates, net result, drawdown and trades.
- Open result evidence and record the exact assumptions and one limitation.
Worked example and expected outcome
Teaching case: a positive gross result becomes negative after modeled costs.
This is a fixed teaching example, not a current quote, personal account result or trade recommendation.
Check your understanding
Can you trace the result to the same Playbook and dataset?
If it does not work
Missing coverage or an out-of-date result requires a corrected sample or a new run; it is not a forecast.
Try it in SuperQuant
Sign in or create an account to open this lesson in the Academy, then use its safe in-app handoff when the feature is available to your workspace.
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