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Portfolio-level risk controls, drawdown management, exposure limits, and circuit breakers for crypto trading

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trading-skills
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$ npx -y skills add agiprolabs/claude-trading-skills --skill risk-management --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/risk-management

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Portfolio-level risk controls, drawdown management, exposure limits, and circuit breakers for crypto trading

SKILL.md

risk-management.SKILL.md
name: risk-management
description: Portfolio-level risk controls, drawdown management, exposure limits, and circuit breakers for crypto trading

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:

1. **Survival** — Never risk account ruin. No single trade, day, or week should threaten your ability to continue trading. 2. **Capital preservation** — Protect what you have. Losses compound geometrically; recovery requires outsized gains. 3. **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
Read more
Ships withtrading-skills

A comprehensive collection of 67 ready-to-use trading, DeFi, and quantitative finance Agent Skills. Works with Claude Code, Cursor, Codex, Gemini CLI, and 30+ other tools.

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Repo: agiprolabs/claude-trading-skills