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IntermediateRisk & PerformancePython

Run this module

cd "Risk Metrics - Drawdown Analysis"
python "drawdown_analysis.py"

View source on GitHub

Drawdown Analysis

Comprehensive drawdown metrics for quantifying portfolio loss risk over time. Drawdown measures capture both the depth and duration of losses — dimensions VaR ignores.

Functions

Function Description
drawdown_series(returns) Drawdown at each point in time
max_drawdown(returns) Largest peak-to-trough decline
calmar_ratio(returns, periods) Annualized return / Max drawdown
ulcer_index(returns) RMS of drawdown depths
ulcer_performance_index(returns, rf) Mean excess return / Ulcer index
average_drawdown(returns) Mean depth across all drawdown periods
max_drawdown_duration(returns) Longest continuous drawdown in periods
drawdown_summary(returns, periods) All metrics in one dict

Key Concepts

  • Max Drawdown: The worst loss from a peak. MDD of 0.25 = portfolio dropped 25% from its high before recovering.
  • Calmar Ratio: Return per unit of drawdown risk. Like Sharpe but uses MDD instead of std dev. Higher is better.
  • Ulcer Index: Named for the "ulcer-inducing" anxiety of prolonged losses. RMS penalizes long drawdowns heavily.
  • UPI (Martin Ratio): Return / Ulcer Index. Better than Calmar for comparing strategies with similar MDD but different recovery times.

Example

from drawdown_analysis import drawdown_summary
import numpy as np

returns = np.random.normal(0.0005, 0.015, 504)
summary = drawdown_summary(returns)
# {'max_drawdown': 0.142, 'calmar_ratio': 0.87, 'ulcer_index': 0.032, ...}

Benchmarks

Strategy Typical Max Drawdown
Long-only equity 30–60%
60/40 portfolio 20–35%
Market-neutral HF 5–15%
Trend following 15–30%

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