Share Modelling and Trading

Policy Workbench

Create, evaluate, compare, approve and activate candidate selection policies.
The Candidates tab builds lists from the active production policy only—not from drafts here.

Policy Evaluation and Approval

Select an evaluation, compare it to the active production policy, and approve when ready.

Policy Evaluations

Select a row to open the compare and approve panel below.

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Category Policy Status Score Δ Return Horizon
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Policy Creation or Change

Define the goal, tune the policy contract, then save before running or approving.

Policy context

Select an existing policy to revise its goal and contract, or create a new policy evaluation in the category.

Policy action Policy action
Goal
Write a brief, then interpret the goal before Save policy.
No interpreted goal yet.
Policy contract

Factor and trigger search ranges, scoring, run design, and evaluation window for the next run.

Trigger planner

Tune only persisted lane triggers and existing numeric thresholds. Trigger fields and operators remain fixed in v1.

Select a lane to load trigger controls.

Factor weight planner

Include lane factors in the search and set min / max / step. Unchecked = locked at baseline. Defaults may auto-lock factors to stay within the run budget.

Select a lane to load factor controls.

Scoring & planner
Planner controls

Preset, group tuning mode, and granularity write back to persisted search_space and planner_state; they are not a second source of truth.

Draft state: saved
Composite weights

Used only when the objective is Composite; persisted with the lane configuration.

Run design

Controlled mutation proposes bounded variants per generation. Grid optimisation walks the contract cross-product up to the run budget cap.

Evaluation
Evaluation window planner

Each evaluation run samples ranking dates inside this window. Lists define search grids; the first value mirrors lane scalars when you save or validate.

Sampling cadence Spacing between sampled ranking dates (fewer steps = denser history).
Final list planner

Variants for shortlist size, outcome horizon, and protective exit — each list expands the combination grid the search evaluates.

Advanced planner
Walk-forward split (TVT)

Train/validate/test ratios partition the ranking-date window for role-aware evaluation. Test is the residual.

Test ratio is computed as 1 − train − validate. Leave train/validate blank to use legacy single-split evaluation.
Search restrictions

Enumeration-time filters: required factors are always present, excluded ones are always absent. Same for triggers.

Survivor selection + checkpoint

Survivor mode chooses which top results seed the next mutation generation; checkpoint persistence saves run state every generation so timed-out runs can be resumed.

Select a policy, interpret the goal, tune the contract, then save.

Policy Optimisation Schedule

Configure scheduled policy evaluations and evaluation runs.

Scheduled Policy Evaluations

Select a row to edit its schedule or run the saved research objective setup now.

Category Policy Schedule Status Last Evaluation Actions
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Last Evaluation
-
Schedule Status
-
Last Status
Idle
Evaluation Budget
-
Select a policy
Select a policy to load scheduling status.

Approved Live Policies

The policies and versions used for live candidate selection.

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