IntermediateRisk & PerformancePython

Run this module

cd "Risk Metrics - Stress Testing"
python "stress_testing.py"

Portfolio Stress Testing¶

Stress tests answer: "What happens if 2008 repeats?" or "How big a shock kills the portfolio?" Required by Basel III, CCAR, and most institutional risk frameworks.

Functions¶

Function	Description
`apply_scenario(weights, shocks, V)`	Apply per-asset return shocks
`historical_scenario(weights, name, V)`	Replay 2008 GFC, 2020 COVID, etc.
`sensitivity_analysis(weights, range, idx)`	Univariate shock sweep
`reverse_stress_test(weights, direction, loss)`	Find shock magnitude that breaches loss
`worst_case(weights, scenarios, V)`	Worst P&L across scenario set

Built-in Historical Scenarios¶

Name	Equity	Credit	Rates	Commodity	FX
`2008_GFC`	-50%	-30%	-2%	-40%	-15%
`2020_COVID`	-34%	-20%	-1.5%	-55%	-10%
`1987_Black_Monday`	-22.5%	-5%	+0.5%	-10%	-5%
`2000_DotCom`	-49%	-10%	-3%	+5%	-8%
`2022_Inflation`	-20%	-13%	+4%	+30%	+12%

Example¶

from stress_testing import historical_scenario, reverse_stress_test

res = historical_scenario(
    {"equity": 0.6, "credit": 0.3, "rates": 0.1},
    "2008_GFC",
    portfolio_value=10_000_000,
)
print(res["portfolio_pnl"])

# How big an equity-only shock to lose 25%?
k = reverse_stress_test([1.0], [-1.0], 0.25, 1.0)  # -> 0.25

Practical Notes¶

Shocks are return shocks, not price shocks (use -0.50, not 0.50).
Combine with VaR/ES for a complete tail-risk picture.
Reverse stress tests reveal what scenario is plausible enough to breach risk limits.

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