
Risk & Control
risk-management
This Skill implements portfolio-level risk controls for crypto and Solana trading, enforcing a survival-first hierarchy (survival, capital preservation, growth).
Overview
This Skill implements portfolio-level risk controls for crypto and Solana trading, enforcing a survival-first hierarchy (survival, capital preservation, growth).
This Skill implements portfolio-level risk controls for crypto and Solana trading, enforcing a survival-first hierarchy (survival, capital preservation, growth). It provides configurable drawdown thresholds (conservative/moderate/aggressive), daily and weekly loss limits with automatic halts or size reductions, concentration caps per token tier, circuit breakers, and mandatory cooling periods and reviews. Crypto-specific considerations include liquidity, slippage, on-chain settlement, validator and network risk for Solana, and recovery math to quantify required gains after drawdowns. Use cases: discretionary traders, algo funds, exchanges, and risk teams integrating automated halts, alerts, and position-sizing constraints. Core advantages: prevents account blowups, enforces discipline across strategies, simplifies governance and backtesting of risk rules, and enables automated enforcement and monitoring across volatile crypto markets.
Skill.md
How this skill works
This Skill implements portfolio-level risk controls for crypto and Solana trading, enforcing a survival-first hierarchy (survival, capital preservation, growth).
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-analysisskill 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-modelingskill 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
Best used for
When to use it
This Skill implements portfolio-level risk controls for crypto and Solana trading, enforcing a survival-first hierarchy (survival, capital preservation, growth).

01 · PRE-MEETING
Prepare a decision brief
Turn scattered evidence into a structured case before an investment committee meeting.

02 · TEAM WORKFLOW
Standardize handoffs
Create consistent research outputs across analysts, portfolio managers, and agents.

03 · LIVE UPDATE
Refresh the thesis
Update scenarios after a new catalyst, KPI release, or earnings result.
Community notes
Built to improve with use.
Feedback will appear here as this skill is used and reviewed.
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