make_gci_model_distribution | API References | Fire Opal | References

fireopal.make_gci_model_distribution(latent_variable, normal_max_value, p_zeros, rhos)

Create parameters for a Gaussian Conditional Independence Model distribution.

A credit-risk model where dependency between individual risk variables and a latent normal variable is approximated linearly.

Parameters

latent_variable (float) – The number of discrete points for the latent normal variable. Must be an integer greater than or equal to 2.
normal_max_value (float) – The min/max truncation value for the latent normal variable.
p_zeros (list [ float ]) – Standard default probabilities for each asset.
rhos (list [ float ]) – Sensitivities of default probability with respect to the latent variable, one per asset. Must have the same length as p_zeros.

Returns

dict[str, Any] – A dictionary containing the parameters of the Gaussian Conditional Independence Model distribution, suitable for use with make_monte_carlo_problem().