Risk Manager

Position sizing, Value-at-Risk, stress testing, correlation analysis, and risk-adjusted performance metrics. Institutional-grade risk control for any portfolio.

When to Use

USE this skill when:

  • “how much should I allocate to ETH” / “position size”
  • “what’s my portfolio VaR” / “value at risk”
  • “stress test my portfolio” / “what if BTC drops 50%”
  • “correlation between my holdings”
  • “Sharpe ratio” / “risk-adjusted returns”
  • “am I too concentrated” / “diversification check”
  • “Kelly criterion for this trade”
  • “max drawdown analysis”

When NOT to Use

DON’T use this skill when:

  • User wants to execute a trade — use fin-trading
  • User just wants current prices — use fin-market-data
  • User wants asset research or analysis — use fin-expert
  • User wants to set up DCA plans — use fin-dca-strategy
  • User wants news or sentiment — use fin-news-intel

Tools

Existing Tools

  • fin_portfolio_positions — fetch current portfolio holdings
  • fin_portfolio_balances — fetch account balances
  • fin_portfolio_history — historical portfolio snapshots for drawdown analysis
  • fin_market_price — historical OHLCV data for VaR, correlation, and volatility calculations
  • fin_ticker_info — 24h metrics, volume, and market cap context

Risk-Specific Tools (Documented)

  • fin_risk_var — compute Value-at-Risk and Conditional VaR

    • Parameters: portfolio_id, confidence_level (0.95 | 0.99), method (historical | parametric), horizon_days (1 | 5 | 10)
    • Returns: VaR amount, CVaR (Expected Shortfall), contribution by position

  • fin_risk_stress_test — run stress scenarios against portfolio

    • Parameters: portfolio_id, scenario (crypto_winter | flash_crash | defi_contagion | rate_hike | black_swan | custom), custom_shocks (optional asset-level overrides)
    • Returns: portfolio P&L under scenario, per-position impact, margin call risk flag

  • fin_risk_correlation — rolling correlation matrix

    • Parameters: assets[], window (30 | 60 | 90 days), method (pearson)
    • Returns: correlation matrix, highly-correlated pairs (>0.85), effective diversification ratio

  • fin_risk_position_size — calculate optimal position size

    • Parameters: method (fixed_fractional | kelly | half_kelly | mean_variance), capital, risk_per_trade (%), win_rate, avg_win, avg_loss, target_asset
    • Returns: recommended position size, risk amount, expected value per trade

Risk Methodology

1. Position Sizing

Calculate optimal allocation using one of four methods:

  • Fixed Fractional Risk: Risk a fixed percentage (1-3%) of total capital per trade. Position size = (Capital x Risk%) / (Entry - StopLoss).
  • Kelly Criterion: f* = (bp - q) / b where b = avg_win/avg_loss, p = win_rate, q = 1 - p. Maximizes long-term geometric growth.
  • Half-Kelly (recommended): f*/2. Sacrifices ~25% of growth for ~50% less volatility. Default recommendation for most users.
  • Mean-Variance Optimization: MPT-based allocation targeting the efficient frontier. Requires return estimates and covariance matrix.

Always present all methods side-by-side and recommend Half-Kelly for most individual investors.

2. Value-at-Risk (VaR)

Three calculation approaches:

  • Historical VaR: Sort portfolio returns over lookback window, find the loss at the chosen percentile. Non-parametric, captures fat tails.
  • Parametric VaR: Assume normal distribution, VaR = mu - z * sigma. Fast but underestimates tail risk in crypto.
  • Conditional VaR (Expected Shortfall): Average of all losses beyond the VaR threshold. Always report CVaR alongside VaR — it answers “when things go wrong, how bad?”

Default: 95% confidence, 1-day horizon. Always report in both absolute ($) and percentage terms.

3. Stress Testing

Five predefined scenarios plus custom:

ScenarioBTCETHAltsStablesDescription
Crypto Winter-60%-70%-80%-1%Prolonged bear market (2022 analog)
Flash Crash-30%-35%-50%0%Sudden liquidation cascade
DeFi Contagion-20%-40%-60%-5%Smart contract exploit / protocol failure
Rate Hike Shock-15%-20%-30%0%Unexpected Fed tightening
Black Swan-50%-60%-90%-10%Exchange collapse / systemic event

For custom scenarios, accept per-asset percentage shocks and compute aggregate portfolio impact.

4. Risk-Adjusted Performance Metrics

Calculate and present in a summary table:

  • Sharpe Ratio: (Return - Rf) / StdDev. >1 acceptable, >2 good, >3 excellent.
  • Sortino Ratio: (Return - Rf) / DownsideStdDev. Penalizes only downside volatility.
  • Calmar Ratio: CAGR / MaxDrawdown. Measures return per unit of drawdown risk.
  • Max Drawdown: Largest peak-to-trough decline. Report magnitude, duration, and recovery time.
  • Beta: Portfolio sensitivity to BTC (crypto) or S&P 500 (traditional). Beta > 1 = amplified market risk.
  • Information Ratio: (Portfolio Return - Benchmark Return) / Tracking Error. Measures active management skill.

5. Correlation Analysis

  • Compute rolling Pearson correlation over 30/60/90-day windows.
  • Flag highly correlated pairs (r > 0.85) — these provide minimal diversification benefit.
  • Calculate the effective diversification ratio: (sum of individual VaRs) / (portfolio VaR). Higher = better diversified.
  • Visualize as a correlation matrix with color coding.

Response Guidelines

  • Always fetch the actual portfolio before running risk analysis — never assume holdings.
  • Present VaR and stress test results in clear tables with both dollar and percentage impact.
  • When recommending position sizes, show the calculation step-by-step so users understand the logic.
  • Compare multiple sizing methods and explain trade-offs (growth vs. safety).
  • Flag concentration risk: warn if any single position exceeds 25% of portfolio.
  • Flag correlation risk: warn if effective diversification ratio is below 1.5.
  • For stress tests, always show the worst-case scenario’s impact on total portfolio value.
  • Include actionable recommendations: “To reduce VaR by 20%, consider reducing Position X by Y%.”

Risk Disclosures

  • Risk metrics are based on historical data and statistical models. Past performance and historical correlations do not guarantee future results.
  • VaR does not capture the magnitude of losses beyond its threshold — always review CVaR alongside VaR.
  • Stress test scenarios are illustrative. Real market events may produce outcomes outside these ranges.
  • Position sizing recommendations are mathematical frameworks, not financial advice. Always consider your personal financial situation and risk tolerance.
  • Crypto markets exhibit higher volatility and fatter tails than traditional markets. Parametric VaR may significantly underestimate risk.