BEHAVIOR MODULE
Psychology in trading should be treated as operational data, not motivational commentary.
A framework is needed to capture state transitions, trigger conditions, and response quality during live execution.
With structured behavior mapping, correction actions can target root triggers instead of visible symptoms.
Emotional drift often remains undocumented while execution data appears complete. This creates false confidence in review quality.
Without standardized state tags, post-session analysis cannot distinguish stress response from setup error.
As a result, routine changes become reactive and inconsistent, especially after streak periods or sharp drawdowns.
A psychology framework solves this by forcing consistent state capture and trigger attribution before narrative bias appears.
The framework connects baseline readiness checks, live state tagging, and post-session trigger governance in one control loop.
01
Assess readiness and pre-session stress level before participating in the market.
Baseline audits reduce hidden carry-over bias from prior sessions.
02
Tag urgency, fear, hesitation, and override impulses at decision time.
Live logging preserves context and avoids post-outcome reinterpretation.
03
Reconstruct how state shifted across the session and where rule adherence changed.
Sequence reconstruction reveals trigger chains instead of isolated emotional labels.
04
Apply one behavioral correction mechanism per cycle and validate it across fixed windows.
Single-change protocols prevent self-sabotage through over-correction.
TradeReality operationalizes psychology controls with structured tagging, pattern filters, and correction continuity tools.
Relate behavior-state frequency to adherence quality across review cycles.
This quantifies whether emotional regulation efforts produce process-level improvement.
Capture state transitions in short-duration environments where pressure intensity is high.
Binary-focused logs preserve behavior context in compressed decision windows.
Detect conflicts between planned behavior standards and recorded live responses.
Conflict detection enables focused interventions on recurring trigger pathways.
Evidence is derived from recurring behavior metrics and correction consistency, not discretionary storytelling.
Logic 1
Structured state tagging improves trigger visibility under real pressure.
Logic 2
Improved trigger visibility enables precise and proportional corrections.
Logic 3
Precise corrections improve behavioral stability over repeated session cycles.
No broker connection required.
TradeReality supports process-first journaling, review workflows, and behavioral diagnostics for discretionary traders.
