Mistake Journal

Learn from your trading mistakes. Track patterns in your bad decisions.

Mistake Journal is a CLI trade journal that focuses on what went wrong and why. Log your trades with emotions, reasoning, and outcomes - then analyze patterns in your losing trades to become a better trader.

Features

• Trade Logging: Record entries with emotions, reasoning, market conditions
• Mistake Tagging: Categorize errors (FOMO, revenge trade, no stop loss, etc.)
• Pattern Analysis: AI identifies recurring mistakes in your history
• Emotion Tracking: Correlate emotional state with trade outcomes
• Weekly Reports: Summarize wins, losses, and lessons learned
• Export: JSON/CSV export for external analysis

Installation

pip install mistake-journal

Quick Start

# Log a new trade
mistake-journal log

# Quick log with inline data
mistake-journal log --symbol BTC --action buy --price 45000 --emotion anxious

# Review your journal
mistake-journal review

# Analyze your mistakes
mistake-journal analyze

# Weekly summary
mistake-journal report --week

Example Session

$ mistake-journal log

NEW TRADE ENTRY
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Symbol: DOGE
Action [buy/sell]: buy
Entry price: 0.15
Position size ($): 500
Date (enter for now):

PRE-TRADE STATE
How are you feeling? [1-5 scale]
  1=Fearful  2=Anxious  3=Neutral  4=Confident  5=Euphoric
Emotion level: 5

Why did you enter this trade?
> Elon tweeted and it's pumping, don't want to miss out

Did you have a plan before entering? [y/n]: n
Stop loss set? [y/n]: n
Take profit target? [y/n]: n

Tags (comma-separated): fomo, no-plan, social-media
Notes: Saw it on Twitter, jumped in without thinking

Entry logged! Remember to close this trade later with:
  mistake-journal close --id 47

$ mistake-journal close --id 47

CLOSING TRADE #47 (DOGE)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Exit price: 0.11
Exit date (enter for now):

OUTCOME: -$133.33 (-26.7%)

POST-TRADE REFLECTION
What went wrong (or right)?
> Bought the top, it dumped right after. Classic.

What would you do differently?
> Wait for a pullback, set a stop loss, don't trade on tweets

Lesson learned: Don't chase pumps based on social media

Trade closed and saved!

Analyze Your Patterns

$ mistake-journal analyze

MISTAKE PATTERN ANALYSIS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Total trades: 47
Win rate: 38%
Avg winner: +$234
Avg loser: -$189

TOP MISTAKE PATTERNS:

1. FOMO (12 trades, 83% loss rate)
   - Avg loss: -$201
   - Usually occurs when: emotion level 4-5
   - Common symbols: DOGE, SHIB, meme coins

2. No Stop Loss (18 trades, 67% loss rate)
   - Avg loss when wrong: -$312 (vs -$98 with stops)
   - "Let me just hold and see" → usually gets worse

3. Revenge Trading (6 trades, 100% loss rate)
   - Always follows a losing trade within 1 hour
   - Avg loss: -$287

4. Overconfidence (8 trades, 62% loss rate)
   - Emotion level 5, large position sizes
   - Avg position: 15% of portfolio (vs your 5% rule)

INSIGHTS:
• You perform best when emotion level is 2-3 (neutral/slightly cautious)
• Your worst day is Monday (42% win rate vs 51% other days)
• Trades with a written plan: 58% win rate
• Trades without a plan: 24% win rate

RECOMMENDATION:
Stop trading meme coins on social media hype. Your win rate on
these is 12%. Consider a 24-hour waiting rule for high-emotion trades.

Mistake Tags

Built-in tags (or add your own):

Commands

mistake-journal log                  # Log new trade
mistake-journal close --id <ID>      # Close a trade
mistake-journal review               # Browse journal entries
mistake-journal analyze              # Pattern analysis
mistake-journal report [--week/--month]  # Performance report
mistake-journal tags                 # Manage custom tags
mistake-journal export --format csv  # Export data
mistake-journal stats                # Quick statistics

Use as Library

from mistake_journal import Journal

journal = Journal()

# Log a trade
trade_id = journal.log_trade(
    symbol="BTC",
    action="buy",
    price=45000,
    size=1000,
    emotion=4,
    reasoning="Breakout pattern",
    tags=["technical", "planned"]
)

# Close it
journal.close_trade(
    trade_id,
    exit_price=48000,
    reflection="Stuck to the plan, took profits at target"
)

# Analyze
analysis = journal.analyze()
print(analysis.top_mistakes)
print(analysis.recommendations)

Storage

Journal data stored locally in ~/.mistake-journal/:

• trades.json - All trade entries
• config.json - Settings
• tags.json - Custom tags

Philosophy

The goal isn't to track P&L (use a spreadsheet for that). The goal is to:

1. Force reflection on every trade
2. Identify patterns you can't see in the moment
3. Build self-awareness about emotional trading
4. Create accountability through written records

Most traders repeat the same 3-4 mistakes. Find yours. Fix them.

License

MIT License