Exit Analysis Tab Guide

~6 min – the exit post-mortem that finally proves whether your “gut feel” closes are genius… or just expensive therapy sessions disguised as trading

You’ve already seen exit quality scores in Council reviews and PEE Analytics. Now open Exit Analysis (sixth tab in CharterElite, Brain icon).

This tab zooms in exclusively on how you exit: types, quality grades, plan adherence, auto-detected patterns, regime filters, and validation behaviors. It answers the question most traders avoid: “Am I exiting like a sniper… or like someone who just wanted the pain to stop?”

Every sub-tab uses completed trades only—because only closed trades have exits.

Where to Find It

• Sidebar → CharterElite
• Sixth tab → Exit Analysis (Brain icon)
• Expand tab help accordion (top) for benchmarks + pro tips (“favor high-PnL exit types, reduce emotional ones”)

Filters – Same CharterElite Controls

• Portfolio — All or single
• Setup — Multi-select
• Side — LONG / SHORT / Both
• From / To — Date range (exit_date)
• Exit Behavior — Multi-select EXIT taxonomy tags (appears when exit tags exist)
• Market Regime — Multi-select regimes (appears when regime data exists)

All sub-tabs respect filters.

How Exit Type Is Resolved

From custom_stats array/object:

• Looks for stat with name “Exit Type”, “exit_type”, or “exitType”
• Uses its value (e.g. “Target Hit”, “Stop Loss”, “Manual Exit”, “Time Exit”)
• No match? → “Unknown”

Add “Exit Type” custom stat when closing trades for meaningful data.

The Five Sub-Tabs – Your Exit Forensics Workflow

1. Exit Types (Start Here)

• Summary cards:
• Best Exit Type (highest PnL)
• Worst Exit Type (lowest PnL)
• Most Used
• Least Used

• Charts:
• Exit Type Distribution — Bar: trade count per type (tooltip: count, %, win rate)
• PnL by Exit Type — Bar: total PnL per type (tooltip: total, count, avg PnL); green/red bars

• Alert if all “Unknown”: “Add ‘Exit Type’ to custom stats when completing trades”

Use this to see which exit methods actually print vs bleed.

1. Exit Quality (PEE-Powered Patterns)

• Requires PEE data (MFPE/MAPE/pee_sequence/pee_data)
• Outcome Type Distribution — Pie + table: outcome name, count, %, avg R; severity emoji
• Most Common Pattern alert (top outcome + % + avg R)
• Validation Patterns — Tables: Stop/Target/Trade validation ranges, count, %
• Most Common Recommendations — Table: recommendation text, frequency, %, avg R; Top Recommendation alert

Use this to see what the market says about your exits (e.g. “Early exit most common – targets too small?”)

1. Plan Adherence (How Often You Stuck to the Script)

• Same PEE source as Exit Quality
• Plan Adherence Patterns cards: labels (“Stopped out as planned”, “Target hit”, “Early exit”, etc.), count, %
• Summary Statistics: Total trades, trades with PEE, avg realized R

Use this to quantify rule-following at exit.

1. Quality Scores (0–100 + Grades)

• Requires exit_quality_score (0–100) on trades
• Summary cards: Avg Quality Score (+ grade), Median Score (+ grade), Trades with Scores (count + %)
• Exit Quality Grade Distribution — Bar chart + table: grade (A+ to F), count, avg R, % of total; colored by grade

Grades: A+ (95+), A (90+), B+ (85+), B (80+), C+ (75+), C (70+), D (60+), F (<60)

Use this to see if your exits are consistently high-quality or erratic.

1. Auto Tags & Regime (Patterns + Context)

• Auto-Detected Exit Patterns — Table: tag, frequency (count + %), win rate, avg PnL, avg R; colored badges

(Only if auto_exit_tags exist on trades)

• Performance by Market Regime — Table: regime, count (%), win rate, avg PnL, avg R, avg quality (score + grade)

(Only if market_regime exists)

Use this to see which exit tags or regimes correlate with better/worse exits.

No Data State (Whole Tab)

If no exit types AND no PEE data AND no quality scores AND no auto tags/regime:

• Single empty state: “No Exit Data Available”
• Guidance: add “Exit Type” to custom stats, add PEE in Execution Details, complete trades with exit quality, tag regimes

Otherwise, sub-tabs appear (each may show its own empty/alert).

Quick Workflow – Exit Murder Ritual

1. Open Exit Analysis → set filters (last 6–12 months, main setups)
2. Exit Types → best/worst types? Favor high-PnL exits, reduce low ones
3. Exit Quality → most common pattern? (Early exit? → targets too small)
4. Plan Adherence → low adherence? → tighten exit rules
5. Quality Scores → avg grade low? → back to PEE for rule sims
6. Auto Tags & Regime → bad regime exits? → filter setups by regime
7. Action: top bad exit type/tag? → add Playbook tag or setup rule → kill it next week

Quick Reality Checks

• All “Unknown” types? → Add “Exit Type” custom stat when closing
• No PEE data? → Fill MAE/MFE/MAPE/MFPE + sequence in Execution Details
• Low avg quality score? → Early fear or greedy holds—check PEE Analytics
• No correlations? → Tag exit taxonomy, regime, or use scaled position management
• All green exits? → Small sample or elite—protect it in Evolution

Next: Episode 29 – Full Flywheel Mastery: Integrating Weekly Alpha → Calendar Analytics → CharterElite (Exit Analysis, R Distribution, Temporal, Performance Ratios, PEE) → Council (Kill List, Reality Check, Setup DNA) → Evolution into the self-reinforcing compounding loop that turns monthly audits into weekly micro-kills and quarterly A-grade upgrades—without ever increasing risk % or chasing new shiny setups.

Or open CharterElite → Exit Analysis right now. Set last 6 months + your main setups.

Look at Exit Types → worst PnL type?

That’s your money walking away.

Now check Quality Scores → avg grade low?

That’s the proof.

Cross to Exit Quality sub-tab → most common pattern?

That’s the name of your killer.

Tag it. Rule it. Kill it.

Your exits aren’t fate. They’re data.

Rewrite the ending.

One close at a time.

The market doesn’t grade on effort. It grades on R.

Make the grade go up.

Your future PnL is waiting. 😈