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FRAMEWORK MODULE

Performance Review for Traders

Performance review is a procedural quality-control system, not a retrospective narrative exercise.

Its function is to evaluate routine adherence, classify deviations, and govern correction decisions through fixed criteria.

When review standards remain stable, process changes become testable and operational confidence increases.

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The Real Problem

Many traders review outcomes without reviewing the decision process that generated them. This leads to action plans based on surface-level impressions rather than repeatable diagnostics.

Without explicit review structure, deviations are either overemphasized or ignored depending on emotional state and recent result sequence.

As a consequence, correction cycles become inconsistent: too many variables change at once, and causal interpretation collapses.

A formal review framework solves this by anchoring every correction to documented evidence, fixed scoring logic, and controlled validation windows.

Framework Breakdown

This framework standardizes review into repeatable stages that preserve evidence quality and support stable correction governance.

01

Pre-Review Calibration

Define review scope, scoring dimensions, and evidence sources before reading session outcomes.

Calibration reduces result-driven bias and keeps analysis anchored to process integrity.

App bridge: TradeReality review templates enforce fixed scoring fields before summary interpretation begins.

02

Session Reconstruction

Rebuild decision sequence from logs, tags, and context markers to identify exact deviation events.

Sequence reconstruction limits hindsight distortion and clarifies whether a deviation was planned or reactive.

App bridge: In-app timeline records preserve event ordering and link deviations to contextual markers.

03

Deviation Classification

Classify deviations by type, frequency, and condition cluster to separate isolated mistakes from systemic drift.

Classification prevents emotional overreaction to single events and supports proportional corrections.

App bridge: TradeReality filters group deviations by pattern so correction priorities can be ranked objectively.

04

Correction Governance

Implement one correction variable at a time and evaluate its impact over predefined review intervals.

Controlled correction cadence preserves causality and prevents destabilizing strategy churn.

App bridge: Correction notes are tied to future checkpoint tasks for structured follow-through.

In-App Integration

TradeReality bridges review theory into operational workflow by connecting session logs, classification filters, and correction checkpoints.

Metric-based discipline tracking

Review scores are anchored to adherence dimensions, not generalized outcome summaries.

This keeps correction decisions tied to measurable process behavior across equivalent contexts.

Binary Mode execution log

Binary sessions can be reconstructed with expiry-pressure tags and timing rationale records.

That enables review logic to account for short-duration stress variables without introducing ad hoc criteria.

Alignment conflict detection

The app highlights conflicts between declared session intent and recorded decision behavior.

Conflict visibility improves correction precision and avoids broad, non-actionable recommendations.

Logical Evidence

This section uses process logic, not promotional claims. Evidence quality is based on repeatability and causal coherence.

Logic 1

Structured review protocols increase diagnostic reliability across sessions.

Logic 2

Reliable diagnostics reduce correction noise and routine instability.

Logic 3

Reduced correction noise improves long-term expectancy stability through consistent process control.

Build Process. Not Hope.

No broker connection required.

TradeReality supports process-first journaling, review workflows, and behavioral diagnostics for discretionary traders.

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