01 / THE PRACTICAL QUESTION
A decision, before a model.
Two assets look diversified on ordinary days, yet can fall together during a crisis.
Challenge the dependence model while holding individual asset distributions comparable.
02 / DATA & COMPARISON
The idea in plain language.
A copula describes how outcomes line up across assets separately from each asset's distribution. Ordinary correlation does not fully describe the chance of joint extremes.
- Tail dependence
- The tendency for one asset to have an extreme outcome when another does.
Data. Correlated simulations and transformed marginal return samples.
Baseline. Gaussian dependence with matched marginal distributions.
03 / THE EXPERIMENT
What the saved experiment shows.
The saved 5,000-sample check estimates correlation 0.592 from a generating value of 0.600. Separate tests verify differences in tail dependence and portfolio VaR across copula families; correlation recovery alone does not validate crisis behavior.
Inspect the supporting resultEvidence record: research-validation.json#numerical_checks/06
Explore the related lab04 / RESULTS & LIMITATIONS
Evidence with its boundaries attached.
The related lab is a cross-project demonstration. Read this investigation’s evidence and limits before transferring its conclusions.
Inspect numerical checks and validation records
Loading validation evidence…
Dependence assumptions may dominate estimated joint losses during stress.
05 / REPRODUCE
Reproduce and challenge the result.
Code, configuration, and reproduction
The project contains its implementation, configuration, tests, and walkthrough. Download the lab configuration to record the exact parameters used in an interactive run.
Project code and walkthrough