pflab_distributions: 4 tools.
| Tool | What it does | Notes |
|---|---|---|
pflab_univariate_distribution | Fits each asset’s returns to a normal, Student t, Johnson SU or normal inverse Gaussian distribution, or selects the best by AIC/BIC. | |
pflab_bivariate_copula | Fits a bivariate copula to two assets’ pseudo-observations (ranks): Gaussian, Student t, Clayton, Gumbel or Joe with rotations, or the best by AIC/BIC with an independence test. | |
pflab_vine_copula | Fits a regular vine copula: a marginal distribution per asset and a tree of pair copulas (Gaussian, Student t, Clayton, Gumbel, Joe, independent, with rotations) capturing non-Gaussian and tail dependence, then samples synthetic scenarios, optionally conditioned on some assets’ returns. | |
pflab_stress_test | Synthetic stress test: a vine copula fitted to the history is sampled conditionally on the stressed assets’ returns, so every other asset moves consistently with the fitted (non-Gaussian, tail-dependent) structure. |
fincept_describe_tool.