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IntermediateRisk & PerformancePython

Run this module

cd "Risk Metrics"
python "risk_tutorial.py"

View source on GitHub

Risk Metrics Summary Utility

This module gives you quick, professional stats about risk in any list or array of investment returns. It's used by investors, analysts, and students everywhere!

What Stats Does This Cover?

  • Volatility: How much returns bounce around (standard deviation)
  • Downside Volatility: Like volatility, but only counts when the returns fall below zero (focuses on bad swings)
  • Max Drawdown: The biggest drop from a peak to a low—"worst valley" for your money
  • Skew: If returns are more to one side (positive for big upswings, negative for big downswings)
  • Kurtosis: How "chunky" the extremes are (higher means more big outliers)

Why Bother?

  • Professionals use these stats to judge downside risk, stability, and surprise-risk
  • "Max drawdown" matters a lot to actual investors (painful losses!)
  • Skew and kurtosis give you clues about possible crashes or windfalls

How to Use

from risk_summary import risk_metrics
import numpy as np
daily_returns = np.random.normal(0.0005, 0.01, 252)
risk_stats = risk_metrics(daily_returns)
for key, value in risk_stats.items():
    print(key, value)

Learn More

  • Try this on stocks, crypto, or any investment series
  • Combine with Sharpe/Sortino ratios, VaR, and portfolio tools from other UTILS folders for deep analysis

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