The journal is where raw execution data becomes actionable intelligence. Pre-trade intent captures your thesis before the market moves. Post-trade reflection locks in the lesson. Emotions, screenshots, and tags add the context that no broker statement can provide — and they power the AI Copilot.
The journal lives at /dashboard/trades/journal and opens as a side-by-side view. The left panel shows the trade detail (instrument, P&L, entry/exit), and the right panel is the journal editor.
Left: trade details with metrics, tags, and screenshots. Right: journal editor with pre/post notes, emotion selector, and AI suggestions.
Your analysis, plan, and reasoning before entering the trade. Capture the thesis — what you expect to happen and why. These notes anchor your post-trade review against your original intent.
What actually happened, what went right/wrong, and what you would change. Structured fields for execution quality, plan adherence, and lessons learned.
Visual emotion selector with 6 core states (focused, confident, anxious, frustrated, excited, neutral). Rate intensity 1-10. Track how emotional state correlates with P&L over time.
Pre-trade confidence (1-10) and post-trade discipline score (1-10). The gap between these two is one of the most powerful metrics the Copilot tracks.
Organize setups with custom tags (breakout, reversal, scalp, momentum). Create tag groups (Setups, Mistakes, Market Conditions). Tags power every filter, statistic, and Copilot insight.
Attach chart screenshots, trade plans, or any image. Up to 50 per trade. Thumbnails appear inline in the journal view. Full images open in a lightbox.
The Copilot can auto-generate a post-trade debrief based on the execution data and your pre-trade notes. Review, edit, and approve — or write your own.
The distinction between pre-trade and post-trade is the single most important concept in behavioral journaling. Pre-trade captures your intention. Post-trade captures the outcome. The gap between them is where the learning lives.
Written before the trade is entered. Include your analysis, the specific setup you see, your entry/exit plan, risk parameters, and confidence level. Pre-trade notes are timestamped and immutable — once saved, they cannot be edited to prevent revisionist bias.
Written after the trade is closed. Compare outcome vs plan. Rate your discipline honestly. Note what you did well and what you would change. Post-trade reviews are editable to refine insights as you gain perspective.
Select from 6 core emotional states with intensity sliders:
Every emotion log creates a data point on the Mood Timeline — a heatmap overlay on the P&L calendar. See at a glance which emotional states precede your best and worst trading days. The Copilot analyzes patterns like "Frustrated → revenge trade → loss" or "Confident → disciplined → win."
Learn about Behavioral Analysis →Upload your entry chart, exit chart, or any analysis image. Drag-and-drop or paste from clipboard. Images are automatically compressed to WebP for fast loading. Each trade supports up to 50 screenshots.
Thumbnails appear inline in the journal. Click any to open the full lightbox viewer with zoom, pan, and fullscreen. Navigate between images with keyboard arrows. Right-click to download original resolution.
Rename, reorder, or delete screenshots. Add captions to each image. Copy images from one trade to another. Use screenshots as evidence in your post-trade review — a picture of a bad entry tells a story numbers alone cannot.
Every journal entry — emotions, tags, pre/post notes — is mapped to the P&L Calendar. This is the heatmap widget on the Dashboard that shows daily P&L with color intensity. Hover any day to see a summary: P&L, trade count, notes, and emotional state. Click a day to filter the entire dashboard to that session's trades.
The calendar supports month-by-month navigation, weekly aggregates, and year-to-date views. Days with no journal entries are visually distinct from days with rich notes. This visual feedback encourages consistent journaling.
Every note, emotion score, tag, and screenshot caption you add becomes part of the Copilot's context. When you ask "Why did my win rate drop this month?" the AI correlates your emotional state trends, pre-trade confidence levels, and tag distributions against P&L to find the real cause.
After a trading session, the Copilot can auto-generate a structured debrief that references your pre-trade notes against actual outcomes. It highlights trades where your plan was correct (intent matched outcome) and trades where it was not (plan violations, setup drift).
The AI reads across all your journal entries to detect recurring patterns: "Your last 10 'breakout' trades on ES had a 70% win rate, but your 'reversal' trades on NQ only 30%." These patterns are surfaced in Smart Insights on the Dashboard.
The Copilot can suggest pre-fill journal entries based on your trade data and historical patterns. For example, if you consistently journal "Breakout above resistance, high volume" for similar setups, the AI will offer that as a draft pre-trade note. Review, edit, and approve in one click.
Read full Analytics & Copilot documentation →Your first pre-trade note takes 10 seconds. The insight lasts a career.
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