Risk Measurement and Stress Testing

Overview

Systematic risk-measurement methodology covering VaR/CVaR calculation, Monte Carlo simulation, stress-test design, and tail-risk analysis. It provides risk evaluation for backtest results and risk-control constraints for asset allocation.

The measures below are implemented once, with tests, in src/quantlib/risk.py. Call them; do not retype the formulas, because a hand-retyped VaR is where the sign convention silently flips.

from src.quantlib.risk import (
    historical_var, parametric_var, historical_cvar,
    max_drawdown_analysis, monte_carlo_gbm, analyze_mc_results, fit_gpd_tail,
)

Sign convention

A loss is a positive number, uniformly, across every function in the module: