| id | drawdown-playbook |
| name | drawdown-playbook |
| description | Drawdown taxonomy, tiered response protocols (caution to emergency), equity curve health analysis, recovery mathematics, and pre-drawdown preparation. Use for drawdown, equity curve, max drawdown, recovery protocol, drawdown management, or any drawdown-related analysis. |
| title | Drawdown Playbook |
| domain | trading/risk-and-portfolio |
| level | advanced |
| version | 1 |
| depends_on | ["risk-of-ruin"] |
| unlocks | ["real-time-risk-monitor","risk-of-ruin"] |
| tags | ["drawdown","recovery","equity-curve","max-dd","protocols"] |
| status | active |
| created | 2025-01-15 |
| updated | 2025-01-15 |
| context_cost | medium |
| load_priority | 0.8 |
| kind | reference |
| category | trading/risk |
Skill: Drawdown Playbook | Domain: trading/risk-and-portfolio | Category: risk | Level: advanced
Tags: drawdown, recovery, equity-curve, max-dd, protocols
Drawdown Playbook
1. Drawdown Taxonomy
Types
| Type | Definition | Typical Cause |
|---|
| Strategy DD | Expected drawdown within strategy parameters | Normal variance |
| Behavioral DD | Drawdown from rule violations | Revenge trading, FOMO |
| Regime DD | Drawdown from regime change | Strategy-regime mismatch |
| Black Swan DD | Drawdown from extreme events | Flash crash, gap, liquidity vacuum |
Measurement
Max Drawdown (MDD):
MDD = (Peak - Trough) / Peak × 100
Average Drawdown:
Avg of all drawdown periods in lookback window
Drawdown Duration:
Time from peak to recovery (not just to trough)
Ulcer Index:
UI = sqrt(mean(DD²)) — penalizes deep AND long drawdowns
2. Drawdown Thresholds & Responses
Tiered Response Protocol
LEVEL 1: CAUTION (DD = 3-5% of account)
├── Review: Check if within strategy expected DD
├── Action: Reduce position size by 25%
├── Monitor: Tighten review frequency to per-trade
└── Journal: Document what's happening in market
LEVEL 2: WARNING (DD = 5-10% of account)
├── Review: Full strategy audit — is this regime change?
├── Action: Reduce position size by 50%
├── Restrict: No new strategy experiments
├── Require: Every trade needs written thesis before entry
└── Timeline: If no recovery in 10 sessions, escalate
LEVEL 3: CRITICAL (DD = 10-15% of account)
├── Action: Reduce to 1 instrument, 1 strategy, minimum size
├── Pause: No trading for 24-48 hours minimum
├── Audit: Full performance review with data
│ ├── Win rate vs historical
│ ├── Average R vs historical
│ ├── Are losses from stops or blowups?
│ └── Regime classification check
├── Require: Paper trade for 5 sessions before resuming
└── Consider: Is the strategy broken or am I broken?
LEVEL 4: EMERGENCY (DD > 15% of account)
├── Action: STOP TRADING. Full stop.
├── Close: All open positions at market
├── Duration: Minimum 1 week away from screens
├── Requirement: Complete written post-mortem before resuming
├── Review: Account sizing — is total capital at risk appropriate?
└── Return: Restart at LEVEL 1 position sizes for 20+ trades
3. Equity Curve Analysis
Health Indicators
HEALTHY EQUITY CURVE:
✓ Drawdowns are shallow relative to advances
✓ Recovery time < 2× drawdown duration
✓ New equity highs every 20-40 trades
✓ Ulcer Index < 5%
✓ Consistent slope (not spike-dependent)
DETERIORATING EQUITY CURVE:
✗ Drawdowns deepening over time
✗ Time between new highs increasing
✗ Equity curve flattening (winners shrinking)
✗ Large gap between gross and net P&L (overtrading)
Rolling Performance Windows
def equity_health_check(trades: list[Trade], window: int = 50) -> dict:
"""Run on last N trades to detect deterioration early."""
recent = trades[-window:]
metrics = {
'win_rate': len([t for t in recent if t.pnl > 0]) / len(recent),
'avg_r': mean([t.r_multiple for t in recent]),
'max_dd_pct': max_drawdown(recent),
'profit_factor': sum(wins) / abs(sum(losses)),
'expectancy': win_rate * avg_win - (1 - win_rate) * avg_loss,
'sqn': (avg_r / std_r) * sqrt(len(recent)),
}
baseline = compute_metrics(trades)
alerts = []
if metrics['win_rate'] < baseline['win_rate'] * 0.85:
alerts.append('WIN_RATE_DEGRADATION')
if metrics['avg_r'] < baseline['avg_r'] * 0.75:
alerts.append('R_MULTIPLE_COMPRESSION')
if metrics['max_dd_pct'] > baseline['max_dd_pct'] * 1.5:
alerts.append('DRAWDOWN_EXPANSION')
if metrics['sqn'] < 1.6:
alerts.append('SYSTEM_QUALITY_LOW')
return {'metrics': metrics, 'alerts': alerts}
4. Recovery Protocols
Mathematical Reality of Recovery
Loss Required Gain to Recover
───── ────────────────────────
5% → 5.3%
10% → 11.1%
15% → 17.6%
20% → 25.0%
25% → 33.3%
30% → 42.9%
50% → 100% ← Point of no practical return
Recovery Rules
1. Never try to recover fast. Increasing size during drawdown accelerates ruin.
2. Recovery position size = Normal size × (1 - DD%/MaxAllowableDD%)
3. Track recovery separately. When equity returns to 95% of peak, you're "recovered."
4. Time-based recovery. After emergency stop, require N profitable paper trades before live.
5. Pre-Drawdown Preparation
Account Structure
Total Capital: $X
├── Trading Account: 60-70% of X
│ ├── Active margin: ≤50% of trading account
│ └── Reserve: ≥50% as buffer
├── Opportunity Reserve: 20-30% of X
│ └── Deploy only in high-conviction setups after drawdown recovery
└── Emergency Fund: 10% of X (NEVER trade this)
Pre-Commitment Device
Write this BEFORE you start trading, sign it, review monthly:
My maximum account drawdown is ____%
At ____% DD I reduce size by ____%
At ____% DD I stop trading for ____ days
I will not increase size during drawdown
I will not add funds to cover drawdown (throwing good money after bad)
6. Drawdown Journaling Template
## Drawdown Event: [DATE]
**Current DD:** ___% | **Level:** 1/2/3/4
**Duration:** ___ trading days since peak
**Peak Equity:** $___ | **Current Equity:** $___
### What happened?
- [] Normal strategy variance
- [] Regime change
- [] Rule violation
- [] Unexpected event
- [] Overtrading
- [] Position sizing error
### My mental state:
- [] Calm, following protocol
- [] Frustrated but controlled
- [] Anxious, wanting to make it back
- [] Tilted / revenge trading impulse
### Actions taken:
1. ___
2. ___
3. ___
### Review date: [DATE + 3 days]
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