Risk Management

Portfolio-level risk controls for crypto and Solana trading. This skill provides frameworks for drawdown management, exposure limits, circuit breakers, and crypto-specific risk considerations.

Risk Management Hierarchy

Every decision must respect this priority order:

Survival — Never risk account ruin. No single trade, day, or week should threaten your ability to continue trading.
Capital preservation — Protect what you have. Losses compound geometrically; recovery requires outsized gains.
Growth — Only after survival and preservation are secured, pursue returns.

Violating this hierarchy (chasing growth at the expense of survival) is the primary cause of account blowups.

Portfolio-Level Controls

1. Maximum Drawdown Limits

Halt trading when portfolio drawdown from equity peak reaches a threshold:

Account Type	Max Drawdown	Action
Conservative	-15%	Full stop, review all strategies
Moderate	-20%	Full stop, reduce to minimum size on recovery
Aggressive	-25%	Full stop, mandatory cooling period

Recovery math makes this critical: a -20% drawdown requires +25% to recover. A -50% drawdown requires +100%. See references/drawdown_management.md for the full recovery table.

2. Daily Loss Limits

Stop opening new positions after daily P&L (realized + unrealized) hits:

Conservative: -3% of account
Moderate: -4% of account
Aggressive: -5% of account

Reset at midnight UTC. Three consecutive days hitting the daily limit triggers a weekly halt.

3. Weekly Loss Limits

Reduce size or halt after weekly P&L reaches:

Reduce size by 50%: -5% weekly loss
Minimum size only: -7% weekly loss
Full halt: -10% weekly loss

4. Concentration Limits

Maximum allocation to any single dimension:

Dimension	Max Concentration
Single token (blue chip)	10% of account
Single token (mid-cap)	5%
Single token (small-cap)	2%
Single token (PumpFun/micro)	0.5%
Single sector/narrative	30%
Single strategy	40%

5. Exposure Limits

Total deployed capital constraints:

Normal conditions: 50–80% deployed, 20–50% cash reserve
Elevated risk: 30–50% deployed
Drawdown >10%: 20–30% deployed
Max concurrent positions: 5–10 depending on account size

6. Correlation Management

Crypto assets correlate >0.7 during sell-offs. Effective diversification requires:

Treat all meme tokens as a single correlated bucket
Limit total meme exposure to one position-size equivalent
Diversify across strategies (trend, mean-reversion, scalp), not just tokens
Monitor rolling correlation and reduce when correlations spike

See references/exposure_limits.md for detailed limits by token type and strategy.

Drawdown Management

Response Framework

Drawdown	Status	Response
0–5%	Normal	Continue trading at full size
5–10%	Caution	Reduce position sizes by 25–50%
10–15%	Warning	Minimum position sizes only
15–20%	Critical	Halt new trades, manage existing positions only
>20%	Emergency	Full stop, review everything before resuming

Recovery Requirements

Loss	Required Gain to Recover
-5%	+5.3%
-10%	+11.1%
-15%	+17.6%
-20%	+25.0%
-30%	+42.9%
-40%	+66.7%
-50%	+100.0%

The asymmetry accelerates rapidly. Managing small drawdowns prevents them from becoming catastrophic. See references/drawdown_management.md for the full framework.

Circuit Breakers

Automated controls that restrict trading when conditions are met:

Time-Based

No trading for 24 hours after hitting daily loss limit
48-hour cooling period after weekly loss limit
Mandatory weekly review day (no new positions)

Loss-Based

3 consecutive losses → reduce size 50%
5 consecutive losses → minimum size only
7 consecutive losses → halt 24 hours, full review

Volatility-Based

Portfolio volatility >2× rolling average → reduce exposure 50%
Market-wide liquidation events → pause all new entries
Individual token volatility spike → exit or tighten stops

Emotional (Self-Assessed)

Recognize tilt: anger after losses, urge to "make it back"
FOMO: rushing entries without proper analysis
Overconfidence: increasing size after a win streak without justification

See references/circuit_breakers.md for implementation details.

Risk Metrics

Value at Risk (VaR)

95th-percentile daily loss estimate using historical returns:

import numpy as np

def historical_var(returns: list[float], confidence: float = 0.95) -> float:
    """Calculate historical VaR at given confidence level."""
    sorted_returns = sorted(returns)
    index = int((1 - confidence) * len(sorted_returns))
    return abs(sorted_returns[index])

# Example: 95% VaR of 3.2% means on 95% of days, loss won't exceed 3.2%

Expected Shortfall (CVaR)

Average loss in the worst (1 - confidence)% of scenarios:

def expected_shortfall(returns: list[float], confidence: float = 0.95) -> float:
    """Average loss beyond VaR threshold."""
    sorted_returns = sorted(returns)
    index = int((1 - confidence) * len(sorted_returns))
    tail = sorted_returns[:index]
    return abs(sum(tail) / len(tail)) if tail else 0.0

Maximum Drawdown

def max_drawdown(equity_curve: list[float]) -> float:
    """Peak-to-trough decline as a fraction."""
    peak = equity_curve[0]
    max_dd = 0.0
    for value in equity_curve:
        peak = max(peak, value)
        dd = (peak - value) / peak
        max_dd = max(max_dd, dd)
    return max_dd

Additional Metrics

Win/loss streak tracking: Detect hot/cold streaks for circuit breaker logic
Rolling Sharpe ratio: 30-day rolling risk-adjusted returns
Calmar ratio: Annualized return / max drawdown
Sortino ratio: Return / downside deviation (penalizes only negative volatility)

Crypto-Specific Risks

Smart Contract Risk

Never allocate >5% of account to a single unaudited protocol
Diversify across audited protocols for yield strategies
Monitor exploit databases and social channels for emerging threats

Rug Pull Risk

Size inversely with token age: newer tokens get smaller positions
Verify: locked liquidity, renounced mint authority, holder distribution
Cross-reference with token-holder-analysis skill for red flags

Bridge and Custody Risk

Don't hold >20% on any single platform or bridge
Self-custody the majority of trading capital
Budget for bridge fees and delays in execution planning

MEV and Execution Risk

Budget 1–3% for MEV/slippage on Solana DEX trades
Use priority fees during congestion
See slippage-modeling skill for detailed cost estimation

Correlation Spikes

In crashes, crypto correlations approach 1.0
Your "diversified" portfolio may behave as one position
Stress-test portfolio assuming all positions drop simultaneously

PumpFun Risk Framework

PumpFun and similar meme token platforms require a distinct risk approach:

Core Principle

Treat every PumpFun trade as a potential 100% loss. Size accordingly.

Position Limits

Per-token maximum: 0.1–0.5 SOL
Daily PumpFun budget: Fixed allocation (e.g., 2 SOL/day)
Never exceed budget: When daily allocation is gone, stop

Tracking

Track PumpFun P&L separately from main portfolio
Calculate PumpFun win rate and expectancy independently
Don't let PumpFun losses affect main portfolio risk limits

Risk Adjustments

No stop-losses on PumpFun (assume 100% loss at entry)
Take profits aggressively: 2×, 3×, 5× partial exits
Time-based exit: close within hours, not days

Integration with Other Skills

position-sizing: Use risk limits from this skill to constrain position sizes
exit-strategies: Circuit breakers override exit strategies (forced exits)
portfolio-analytics: Feed portfolio metrics back for risk assessment
liquidity-analysis: Adjust position limits based on available liquidity
slippage-modeling: Factor execution costs into risk calculations

Files

References

references/drawdown_management.md — Drawdown math, response framework, causes, and remediation
references/exposure_limits.md — Position limits by token type, portfolio limits, correlation management
references/circuit_breakers.md — Implementation details for all circuit breaker types

Scripts

scripts/risk_dashboard.py — Portfolio risk dashboard with limit checking and color-coded status
scripts/drawdown_analyzer.py — Equity curve drawdown analysis with response recommendations

Quick Start

# Run the risk dashboard with demo data
python scripts/risk_dashboard.py --demo

# Analyze drawdowns on a demo equity curve
python scripts/drawdown_analyzer.py --demo

risk-management