Invitation-only beta
Turn a research question into a test.
Browse references in SA Hub, then choose an instrument and a supported strategy in Lab. Set the configuration, then follow the backtest from submission to result. Lab keeps the experiment close to the evidence.
The run record
Read the record before the result.
Inspect the fields recorded for the run. A missing input, assumption or measurement stays unavailable; do not fill it in from a different experiment.
- Data window and configuration
Check the strategy, instrument, historical window and configuration. Keep evaluation data separate from the data used to choose or tune the candidate.
- Status and available evidence
Follow a supported hosted backtest from submission to its final state. A failed job is not a completed evaluation; missing evidence is not a result.
- Assumptions and limitations
Read the recorded assumptions and limitations beside the result. Consider data coverage, costs and risk before deciding what deserves another test.
- What to try next
Keep failed and unsuccessful experiments in view. Change a deliberate part of the question and test again.
Compare available runs
Put two records beside the same question.
In Backtests, select two completed hosted backtests available to your team. Review their recorded evaluation windows, configuration, cost assumptions and limitations before treating them as comparable.
Failed and incomplete hosted jobs stay in the record but cannot be selected for comparison. Team runs supports a separate comparison of two available received runs. Choose the view that matches the evidence you want to inspect. Team permissions and available evidence determine what you can review.
A failed or incomplete experiment remains part of the record. Missing measurements are unavailable, and a backtest does not establish future performance.
Follow the public walkthroughTest beyond the data you tuned on.
Use validation data to compare candidates. Keep final test data separate from development and tuning. The diagram explains the method; it is not a strategy result.
optimize (in-sample) prove out (never fitted)
fold 1Fold 1: optimized on 2019.0 to 2022.0, proven out on 2022.0 to 2023.0.
fold 2Fold 2: optimized on 2019.6 to 2022.6, proven out on 2022.6 to 2023.6.
fold 3Fold 3: optimized on 2020.2 to 2023.2, proven out on 2023.2 to 2024.2.
fold 4Fold 4: optimized on 2020.8 to 2023.8, proven out on 2023.8 to 2024.8.
fold 5Fold 5: optimized on 2021.4 to 2024.4, proven out on 2024.4 to 2025.4.
fold 6Fold 6: optimized on 2022.0 to 2025.0, proven out on 2025.0 to 2026.0.
Illustrative geometry, not results. An idea has to survive the window it was never fitted to — the ones that don’t get retired.
Illustrative process diagram. No investment performance is represented.
Read about walk-forward evaluationModels in the research loop
Let the evidence guide what you train.
The direction is a connected loop: select strategies, test them, choose model-training experiments and evaluate what changes. Tuning strategy parameters is distinct from training a model.
Customer model training is not available in the hosted app today. Our internal model research is informing that workflow; a backtest or catalog selection does not start training.
Hosted Lab access is by invitation and depends on team permissions and supported research configurations.
Risk disclosure
- Trading involves substantial risk of loss and is not suitable for everyone.
- Hypothetical and backtested results have inherent limitations: they are prepared with the benefit of hindsight and do not represent actual trading.
- Past performance does not guarantee future results.
- Nothing on this site is investment advice, or a recommendation to buy or sell any security, futures contract or other instrument.
For your team
Start with your research workflow.
Tell us what your team wants to test and how you work today. We will walk through the hosted platform and the access available for your team.
Request beta access- Tell us about your team.
- Walk through the platform with a person at 115.
- Agree your team’s access and onboarding.