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name: risk-assessment description: Assess portfolio risk using volatility, drawdown, and other risk metrics. Use when evaluating the risk characteristics of a portfolio or comparing risk profiles.

Risk Assessment Skill

Key Risk Metrics

Risk Assessment Process

Step 1: Analyze Volatility

Copyimport numpy as np

returns = prices.pct_change().dropna()
volatility = returns.std() * np.sqrt(252)  # Annualized
print(f"Annualized Volatility: {volatility:.2%}")

Step 2: Calculate Maximum Drawdown

Copydef calculate_max_drawdown(returns):
    cumulative = (1 + returns).cumprod()
    rolling_max = cumulative.expanding().max()
    drawdown = (cumulative - rolling_max) / rolling_max
    return drawdown.min()

max_dd = calculate_max_drawdown(portfolio_returns)
print(f"Maximum Drawdown: {max_dd:.2%}")

Step 3: Compute Sharpe Ratio

Copyrisk_free_rate = 0.02  # 2% annual
excess_return = portfolio_return - risk_free_rate
sharpe = excess_return / volatility
print(f"Sharpe Ratio: {sharpe:.3f}")

Risk Tolerance Mapping

Risk Flags

Warn the investor if:

• Volatility exceeds their stated tolerance by > 20%
• Max drawdown exceeds tolerance threshold
• Sharpe ratio < 0.5 (poor risk-adjusted returns)
• Single position exceeds max_position constraint