Run & evaluate

The multi-instrument screener

The screener fans one approved strategy across many instruments and timeframes in a single run, then ranks the results side by side. It answers a different question than a single backtest: not just does this work? but where does it work — and is that a real edge or a handful of correlated markets moving together?

What a screen is

A screen takes one approved strategy version and runs it across every (instrument × timeframe) pair you pick, over a single date window — one launch, one ranked readout.

• Entitlement-filtered instruments. You can only screen instruments your account is entitled to; the rest never appear.
• A cost estimate before you launch. The whole-sweep estimate (per-item cost × the number of items) is shown up front, so there are no surprises.
• A dead instrument is an error row, never a dead sweep. If one item fails, it is recorded as an error row with its reason and the rest of the screen carries on.

Launching a screen

Pick a project, a workspace and an approved plugin version, then choose the entitled instruments, the timeframes, and the date window. A few controls shape the readout:

• Rank by the metric you care about (for example Sharpe).
• Min trades — a floor a row must clear before it is allowed to compete for a rank.
• Layer-2 confirm top-K — re-run the top K items under conservative fills to confirm the idealized numbers.
• Fills tier — explore quickly with idealized Layer-1 fills, or apply the full conservative cost model to every item.

Reading the ranked readout

The ranked table shows one row per item with its metric, trade count, win rate, net, max drawdown and a worst realistic cost cell, plus a confirmation chip when a row has been re-checked on Layer-2 fills. Two rules keep it honest:

• The min-trades floor binds before ranking. A row below the floor never competes; it drops to a separate filtered out before ranking section instead of padding the leaderboard with thin samples.
• Every row is a real run. Each item is a normal saved run you can open to read its full scorecard, gates and provenance.

Two charts summarize the sweep: a performance-ordered instrument × timeframe heatmap (the strongest fits cluster together) and a robustness scatter of win rate versus max drawdown, where bubble size is the trade count and color is net return — four dimensions of where a strategy fits, at a glance.

Correlated instruments count once

Some instruments track the same underlying market — for example a full-size contract and its micro sibling. A strategy that “works on both” of those has really been confirmed once, not twice. The screener flags these correlated baskets and tells you plainly: a fit across a basket is one confirmation, not several.