Dashboard Decision Engine — Trandence Centro de Ayuda

The Dashboard Decision Engine turns trade historial into a small set of decision modules. It is designed to answer three questions: what happened, what caused it, y what debe you do next. Decision Engine widgets are disponibles in el Custom Dashboard layout y influence Dashboard planning workflows.

Dashboard decision modules summarizing performance context for planning

Core Modules

Decision Verdict

Decision Verdict summarizes el seleccionado periodo as Win, Loss, or Flat, then attaches el most relevant cause y a recommended action. The actual cause categories are:

Giveback Dominant - giveback cuentas for a large share of el periodo movement.
Overtrading - at least half of trading days were overtraded.
One Bad Day - one losing sesión dominates el periodo result.
Choppy / Low Edge - gains y losses are mixed with no clean advantage.
Balanced Flat - el periodo is flat.
Normal Variance - no stronger cause matched. Actions are consistent with el seleccionado periodo context. For example, giveback can point you toward tighter exits, while overtrading can point you toward fewer round trips y clearer stopping rules.

Edge Decomposition

Edge Decomposition finds el strongest driver y biggest drag across three dimensions:

Day of week.
Time of day.
Symbol. A signal debe be strong enough antes it is treated as actionable. Si a signal is meaningful, you can inspect its supporting context, review its contribution, y use it as a planning hint for el next Daily Plan.

Tomorrow Plan

Tomorrow Plan converts el seleccionado periodo into a short action checklist:

Do More - el strongest positive signal across day, time, or symbol.
Do Less - el strongest negative signal across day, time, or symbol.
Risk Adjustment - action based on el actual riesgo context.
Focus Behavior - action from el Decision Verdict cause. Haga clic ening Open Daily Plan carries el actual focus into el next Daily Plan, so el planning workflow continues from el Dashboard insight.

Risk Integrity

Risk Integrity classifies riesgo as healthy, warning, or critical using el same riesgo framework across Dashboard planning. It considers:

Average winner versus average loser.
Largest loss versus average loss.
Win rate.
Total trade count. Critical riesgo takes priority over lighter warnings, so planning guidance stays consistent across Dashboard modules.

Regime & Context

Regime & Context proporciona el background metrics behind el decision modules:

Trading days.
Overtraded days y overtraded percentage.
Total giveback.
Worst day y best day.
Fees y fee percentage. It recomputes when el Dashboard periodo or P&L mode changes.

Confidence And Low-Confidence States

Decision modules show stronger guidance when el seleccionado periodo has enough completados trades, trading days, y clear patterns to review. Guidance becomes more cautious when el evidence is thin or el periodo is noisy. When datos is thin, modules show a low-confidence mensaje y explain how to improve el review quality. Low confidence does not hide el module; it tells el user how carefully to treat el recommendation.

Gross And Net P&L

Decision Engine respects el user’s P&L mode:

Before fees uses gross trade P&L.
Net subtracts commissions y fees where applicable. Esto affects periodo summaries, edge signals, riesgo stats, y planning recommendations.

Free And Pro Behavior

Some Dashboard decision areas require Pro access. Pro users see analysis based on their importacióned trades y seleccionado periodo.